update

README.md

@@ -1,5 +1,5 @@
 ---
-title: PaccMann^GP
+title: PaccMann
 emoji: 💡
 colorFrom: green
 colorTo: blue
@@ -7,7 +7,7 @@ sdk: gradio
 sdk_version: 3.9.1
 app_file: app.py
 pinned: false
-python_version: 3.8.13
+python_version: 3.7.16
 pypi_version: 20.2.4
 duplicated_from: GT4SD/paccmann_gp
 ---

app.py

@@ -1,91 +1,105 @@
 import logging
 import pathlib
-from typing import List
+from typing import List, Optional
 
+from rdkit import Chem
+from tqdm import tqdm
 import gradio as gr
+from submission import submission
 import pandas as pd
-from gt4sd.algorithms.controlled_sampling.paccmann_gp import (
-    PaccMannGPGenerator,
-    PaccMannGP,
-)
-from gt4sd.algorithms.controlled_sampling.paccmann_gp.implementation import (
-    MINIMIZATION_FUNCTIONS,
-)
-
-from gt4sd.algorithms.registry import ApplicationsRegistry
-
-from utils import draw_grid_generate
+from configuration import GENE_EXPRESSION_METADATA
 
 logger = logging.getLogger(__name__)
 logger.addHandler(logging.NullHandler())
 
-
-MINIMIZATION_FUNCTIONS.pop("callable", None)
-MINIMIZATION_FUNCTIONS.pop("molwt", None)
+site_mapper = {
+    "central_nervous_system": "CNS",
+    "haematopoietic_and_lymphoid_tissue": "Haema_lymph",
+    "upper_aerodigestive_tract": "digestive",
+    "autonomic_ganglia": "ganglia",
+}
 
 
 def run_inference(
-    algorithm_version: str,
-    targets: List[str],
-    protein_target: str,
-    temperature: float,
-    length: float,
-    number_of_samples: int,
-    limit: int,
-    number_of_steps: int,
-    number_of_initial_points: int,
-    number_of_optimization_rounds: int,
-    sampling_variance: float,
-    samples_for_evaluation: int,
-    maximum_number_of_sampling_steps: int,
-    seed: int,
+    smiles: Optional[str],
+    smiles_path: Optional[str],
+    omic_path: Optional[str],
+    confidence: bool,
 ):
-
-    config = PaccMannGPGenerator(
-        algorithm_version=algorithm_version.split("_")[-1],
-        batch_size=32,
-        temperature=temperature,
-        generated_length=length,
-        limit=limit,
-        acquisition_function="EI",
-        number_of_steps=number_of_steps,
-        number_of_initial_points=number_of_initial_points,
-        initial_point_generator="random",
-        number_of_optimization_rounds=number_of_optimization_rounds,
-        sampling_variance=sampling_variance,
-        samples_for_evaluation=samples_for_evaluation,
-        maximum_number_of_sampling_steps=maximum_number_of_sampling_steps,
-        seed=seed,
-    )
-    target = {i: {} for i in targets}
-    if "affinity" in targets:
-        if protein_target == "" or not isinstance(protein_target, str):
-            raise ValueError(
-                f"Protein target must be specified for affinity prediction, not ={protein_target}"
+    # Read SMILES
+    if not isinstance(smiles_path, (str, type(None))):
+        raise TypeError(
+            f"SMILES file pass has to be None or str, not {type(smiles_path)}"
+        )
+    if smiles is None and smiles_path is None:
+        raise TypeError(f"Pass either single SMILES or a file")
+    elif smiles is not None:
+        smiles = [smiles]
+    elif smiles_path is not None:
+        smiles_data = pd.read_csv(smiles_path, sep="\t", header=False)
+        smiles = smiles_data[0]
+        for smi in smiles:
+            if Chem.MolFromSmiles(smi) is None:
+                raise ValueError(f"Found invalid SMILES {smi}")
+
+    # Read omics and otherwise load baseline
+    if not isinstance(omic_path, (str, type(None))):
+        raise TypeError(f"Omics file pass has to be None or str, not {type(omic_path)}")
+
+    # ToDo: Add progress bar for multiple smiles
+    results = {}
+    for smi in tqdm(smiles, total=len(smiles)):
+        result = submission(
+            drug={"smiles": smi},
+            workspace_id="emulated_workspace_id",
+            task_id="emulated_task_id",
+            estimate_confidence=confidence,
+            omics_file=omic_path,
+        )
+        # For the moment no attention analysis
+        result.pop("gene_attention")
+        result.pop("smiles_attention", None)
+        result.pop("IC50")
+
+        results[f"IC50_{smi}"] = result["log_micromolar_IC50"].squeeze().round(3)
+        results[f"IC50_{smi}"].shape
+        if confidence:
+            results[f"aleatoric_confidence_{smi}"] = (
+                result["aleatoric_confidence"].squeeze().round(3)
+            )
+            results[f"epistemic_confidence_{smi}"] = (
+                result["aleatoric_confidence"].squeeze().round(3)
             )
-        target["affinity"]["protein"] = protein_target
+    print(results)
+    predicted_df = pd.DataFrame(results)
+
+    # Prepare DF to visualize
+    if omic_path is None:
+        df = GENE_EXPRESSION_METADATA
+        print(df.columns)
+        df.drop(
+            [
+                "histology",
+                "cell_line_name",
+                "IC50 (min/max scaled)",
+                "IC50 (log(μmol))",
+            ],
+            axis=1,
+            inplace=True,
+        )
+        df["site"] = df["site"].apply(lambda x: site_mapper.get(x, x))
+        df["cell_line"] = df["cell_line"].apply(lambda x: x.split("_")[0])
     else:
-        protein_target = ""
-
-    model = PaccMannGP(config, target=target)
-    samples = list(model.sample(number_of_samples))
+        pass
 
-    return draw_grid_generate(
-        samples=samples,
-        n_cols=5,
-        properties=set(target.keys()),
-        protein_target=protein_target,
+    result_df = pd.concat(
+        [df["cell_line"], predicted_df, df.drop(["cell_line"], axis=1)], axis=1
     )
 
+    return result_df, result_df
 
-if __name__ == "__main__":
 
-    # Preparation (retrieve all available algorithms)
-    all_algos = ApplicationsRegistry.list_available()
-    algos = [
-        x["algorithm_version"]
-        for x in list(filter(lambda x: "PaccMannGP" in x["algorithm_name"], all_algos))
-    ]
+if __name__ == "__main__":
 
     # Load metadata
     metadata_root = pathlib.Path(__file__).parent.joinpath("model_cards")
@@ -93,7 +107,6 @@ if __name__ == "__main__":
     examples = pd.read_csv(
         metadata_root.joinpath("examples.csv"), header=None, sep="|"
     ).fillna("")
-    examples[1] = examples[1].apply(eval)
 
     with open(metadata_root.joinpath("article.md"), "r") as f:
         article = f.read()
@@ -102,63 +115,26 @@ if __name__ == "__main__":
 
     demo = gr.Interface(
         fn=run_inference,
-        title="PaccMannGP",
+        title="PaccMann",
         inputs=[
-            gr.Dropdown(algos, label="Algorithm version", value="v0"),
-            gr.CheckboxGroup(
-                choices=list(MINIMIZATION_FUNCTIONS.keys()),
-                value=["qed"],
-                multiselect=True,
-                label="Property goals",
-            ),
             gr.Textbox(
-                label="Protein target",
-                placeholder="MVLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTT",
+                label="SMILES",
+                placeholder="COc1cc(O)c2c(c1)C=CCC(O)C(O)C(=O)C=CCC(C)OC2=O",
                 lines=1,
             ),
-            gr.Slider(minimum=0.5, maximum=2, value=1, label="Decoding temperature"),
-            gr.Slider(
-                minimum=5,
-                maximum=400,
-                value=100,
-                label="Maximal sequence length",
-                step=1,
-            ),
-            gr.Slider(
-                minimum=1, maximum=50, value=10, label="Number of samples", step=1
-            ),
-            gr.Slider(minimum=1, maximum=8, value=4.0, label="Limit"),
-            gr.Slider(minimum=1, maximum=32, value=8, label="Number of steps", step=1),
-            gr.Slider(
-                minimum=1, maximum=32, value=4, label="Number of initial points", step=1
-            ),
-            gr.Slider(
-                minimum=1,
-                maximum=4,
-                value=1,
-                label="Number of optimization rounds",
-                step=1,
-            ),
-            gr.Slider(minimum=0.01, maximum=1, value=0.1, label="Sampling variance"),
-            gr.Slider(
-                minimum=1,
-                maximum=10,
-                value=1,
-                label="Samples used for evaluation",
-                step=1,
+            gr.File(
+                file_types=[".smi", ".tsv"],
+                label="List of SMILES (tab-separated file with SMILES in first column)",
             ),
-            gr.Slider(
-                minimum=1,
-                maximum=64,
-                value=4,
-                label="Maximum number of sampling steps",
-                step=1,
+            gr.File(
+                file_types=[".csv"],
+                label="Transcriptomics data with cell lines in rows and genes in columns",
             ),
-            gr.Number(value=42, label="Seed", precision=0),
+            gr.Radio(choices=[True, False], label="Estimate confidence", value=False),
         ],
-        outputs=gr.HTML(label="Output"),
+        outputs=[gr.DataFrame(label="Output"), gr.File()],
         article=article,
         description=description,
-        examples=examples.values.tolist(),
+        # examples=examples.values.tolist(),
     )
     demo.launch(debug=True, show_error=True)

artifacts/dump_cos_data.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+
+mc cp chcls-cos/paccmann-storage/model.pt model.pt
+mc cp chcls-cos/paccmann-storage/model.json model.json
+mc cp chcls-cos/paccmann-storage/gene_expression_standardization.pkl gene_expression_standardization.pkl
+mc cp chcls-cos/paccmann-storage/genes.pkl genes.pkl
+mc cp chcls-cos/paccmann-storage/gene_expression.csv.zip gene_expression.csv.zip
+mc cp chcls-cos/paccmann-storage/smiles_language.pkl smiles_language.pkl
+

artifacts/gdsc_1_2_ccle.smi

@@ -0,0 +1,893 @@
+CN(C)CCNC(=O)c1cc2CSc3cc(Cl)ccc3-c2s1	CIL55
+CC(C)N1C(=O)S\C(=C\c2ccc(Sc3nc4ccccc4[nH]3)o2)C1=O	BRD4132
+C(Cn1c2ccccc2c2ccccc12)c1nc2ccccc2[nH]1	BRD6340
+C1CN(CCO1)c1nnc(-c2ccccc2)c(n1)-c1ccccc1	ML006
+OC(CN1CCNCC1)Cn1c2ccc(Br)cc2c2cc(Br)ccc12	Bax channel blocker
+CC(C)(C)c1ccc2cc(C#N)c(cc2c1)C#N	BRD9876
+CC(=CC=CC(=CC(=O)O)C)C=CC1=C(C)CCCC1(C)C	tretinoin
+CC(=C)[C@@H]1CC[C@@]2(CC[C@]3(C)[C@H](CC[C@@H]4[C@@]5(C)CC[C@H](O)C(C)(C)[C@@H]5CC[C@@]34C)[C@@H]12)C(O)=O	betulinic acid
+Oc1ccc(CCC(=O)c2c(O)cc(O)cc2O)cc1	phloretin
+O=C1N(C2CCC(=O)NC2=O)C(=O)c2ccccc12	thalidomide
+CC(C)c1c(O)c(O)c(C=O)c2c(O)c(c(C)cc12)-c1c(C)cc2c(C(C)C)c(O)c(O)c(C=O)c2c1O	gossypol
+OC(=O)CCCc1ccc(cc1)N(CCCl)CCCl	chlorambucil
+Fc1c[nH]c(=O)[nH]c1=O	fluorouracil
+Oc1ccc(cc1)\C=C\C(=O)c1ccc(O)cc1O	isoliquiritigenin
+CN\C(NCCSCc1nc[nH]c1C)=N/C#N	cimetidine
+Nc1ncn([C@@H]2O[C@H](CO)[C@@H](O)[C@H]2O)c(=O)n1	azacitidine
+CN1CCN(CCCN2c3ccccc3Sc3ccc(cc23)C(F)(F)F)CC1	trifluoperazine
+CC(=O)O[C@@H]1C2=C(C)[C@H](C[C@@](O)([C@@H](OC(=O)c3ccccc3)C3[C@@]4(CO[C@@H]4C[C@H](O)[C@@]3(C)C1=O)OC(C)=O)C2(C)C)OC(=O)[C@H](O)[C@@H](NC(=O)c1ccccc1)c1ccccc1	paclitaxel
+CC\C(c1ccccc1)=C(/c1ccccc1)c1ccc(OCCN(C)C)cc1	tamoxifen
+O=C1O[Pt]OC(=O)C11CCC1	carboplatin
+COc1cc(cc(OC)c1O)[C@H]1[C@@H]2C(COC2=O)C(O[C@@H]2O[C@@H]3CO[C@H](OC3[C@H](O)[C@H]2O)c2cccs2)c2cc3OCOc3cc12	teniposide
+CCCc1nn(C)c2C(=O)NC(=Nc12)c3cc(ccc3OCC)S(=O)(=O)N4CCN(C)CC4	sildenafil
+CCC(C)(C)C(=O)O[C@H]1C[C@@H](C)C=C2C=C[C@H](C)[C@H](CC[C@@H]3C[C@@H](O)CC(=O)O3)[C@@H]12	simvastatin
+CCCCc1ccc2[nH]c(NC(=O)OC)nc2c1	parbendazole
+CNNCc1ccc(cc1)C(=O)NC(C)C	procarbazine
+COc1cc(C=CC(=O)CC(=O)C=Cc2ccc(O)c(OC)c2)ccc1O	curcumin
+Cc1cc(C2CCCCC2)n(O)c(=O)c1	ciclopirox
+Oc1cc(O)c2C[C@@H](OC(=O)c3cc(O)c(O)c(O)c3)[C@H](Oc2c1)c1cc(O)c(O)c(O)c1	epigallocatechin-3-monogallate
+Oc1cc(O)c2c(c1)oc(-c1cc(O)c(O)c(O)c1)c(O)c2=O	myricetin
+CN(Cc1cnc2nc(N)nc(N)c2n1)c1ccc(cc1)C(=O)N[C@@H](CCC(O)=O)C(O)=O	methotrexate
+CCC(C)C(=O)OC1CC(C)C=C2C=CC(C)C(CCC(O)CC(O)CC(O)=O)C12	lovastatin
+Cc1onc(c1-c1ccc(cc1)S(N)(=O)=O)-c1ccccc1	valdecoxib
+ClCCN(CCCl)P1(=O)NCCCO1	cyclophosphamide
+CN(C)\N=N\c1[nH]cnc1C(N)=O	dacarbazine
+Oc1ccc(Cl)cc1C(=O)Nc1ccc(cc1Cl)[N+]([O-])=O	niclosamide
+CN1CCN(CCCN2c3ccccc3Sc3ccc(Cl)cc23)CC1	prochlorperazine
+ClCCNP1(=O)OCCCN1CCCl	ifosfamide
+COc1cccc2C(=O)c3c(O)c4C[C@](O)(C[C@H](O[C@H]5C[C@H](N)[C@H](O)[C@H](C)O5)c4c(O)c3C(=O)c12)C(=O)CO	doxorubicin
+C[C@@H]1O[C@@H](O[C@H]2C[C@@H](O)[C@]3(CO)[C@H]4[C@H](O)C[C@]5(C)[C@H](CC[C@]5(O)[C@@H]4CC[C@]3(O)C2)C2=CC(=O)OC2)[C@H](O)[C@H](O)[C@H]1O	ouabain
+COc1ccc(cc1)N(C(=O)c1ccccc1)S(=O)(=O)c1cc(OC)ccc1OC	BRD9647
+COc1cc(cc(OC)c1OC)\C=C\C(=O)N1CCC=CC1=O	piperlongumine
+COc1cc(CCC(=O)N2CCC=CC2=O)cc(OC)c1OC	BRD-K26531177
+CCN(CC)CCCC(C)Nc1nc(C)cc(Nc2ccc3nc(C)cc(N)c3c2)n1	NSC23766
+O=C1c2ccccc2-c2n[nH]c3cccc1c23	pyrazolanthrone
+CCCCCCCCCCCCC\C=C\[C@@H](O)[C@H](CO)NC(=O)CCCCC	C6-ceramide
+CC[C@@]1(O)C(=O)OCc2c1cc1-c3nc4ccc(O)c(CN(C)C)c4cc3Cn1c2=O	topotecan
+CC(C)n1cnc2c(NCc3ccccc3)nc(NCCO)nc12	N9-isopropylolomoucine
+CC(Nc1nc(nc2ccccc12)N1CCCC1)c1ccccc1	importazole
+COc1cc(cc(OC)c1O)[C@H]1[C@@H]2[C@H](COC2=O)[C@H](O[C@@H]2O[C@@H]3CO[C@@H](C)O[C@H]3[C@H](O)[C@H]2O)c2cc3OCOc3cc12	etoposide
+OCC1(CO)N2CCC(CC2)C1=O	PRIMA-1
+CO[C@H]1C[C@H](C)CC2=C(NCC=C)C(=O)C=C(NC(=O)\C(C)=C\C=C/[C@H](OC)[C@@H](OC(N)=O)\C(C)=C\[C@H](C)[C@H]1O)C2=O	tanespimycin
+Cc1ccc2N=C3N(CCC3(O)C(=O)c2c1)c1ccccc1	blebbistatin
+C[C@H]1[C@H]2[C@H](Cc3ccccc3)NC(=O)[C@]22OC(=O)\C=C\[C@H](O)CCC[C@@H](C)C\C=C\[C@H]2[C@H](O)C1=C	cytochalasin B
+OCCSC1=C(SCCO)C(=O)c2ccccc2C1=O	NSC95397
+CCCC[C@@H](C)\C=C(C)\C=C(/C)C(=O)NC1=C[C@@](O)(\C=C\C=C\C=C\C(=O)NC2C(=O)CCC2=O)[C@@H]2O[C@@H]2C1=O	manumycin A
+CO[C@]12[C@H]3N[C@H]3CN1C1=C([C@H]2COC(N)=O)C(=O)C(N)=C(C)C1=O	mitomycin
+CO[C@@H]1C[C@@H](CC[C@H]1O)\C=C(/C)[C@H]1OC(=O)[C@@H]2CCCCN2C(=O)C(=O)[C@]2(O)O[C@@H]([C@H](C[C@H]2C)OC)[C@H](C[C@@H](C)C\C(C)=C\[C@@H](CC=C)C(=O)C[C@H](O)[C@H]1C)OC	tacrolimus
+Cc1ccc(cc1)C(=O)Cn1c2CCCCc2sc1=N	pifithrin-alpha
+NC(=O)c1ccc(cc1)-c1nc(c([nH]1)-c1ccccn1)-c1ccc2OCOc2c1	SB-431542
+CN[C@@H]1C[C@H]2O[C@@](C)([C@@H]1OC)n1c3ccccc3c3c4CNC(=O)c4c4c5ccccc5n2c4c13	staurosporine
+Oc1cc(ccc1NC(=O)Nc1ccccc1Br)[N+]([O-])=O	SB-225002
+COc1cc2ncnc(Nc3cccc(Br)c3)c2cc1OC	PD 153035
+C\C=C\C\C=C\CCC(=O)[C@H]1O[C@H]1C(N)=O	cerulenin
+C1CCC(CC1)n1cnc2c(Nc3ccc(cc3)N3CCOCC3)nc(Oc3cccc4ccccc34)nc12	purmorphamine
+O\N=C1/C(Nc2ccccc12)=C1/C(=O)Nc2cc(Br)ccc12	GSK-3 inhibitor IX
+Cc1nc(Nc2ncc(s2)C(=O)Nc2c(C)cccc2Cl)cc(n1)N1CCN(CCO)CC1	dasatinib
+COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CCOCC1	gefitinib
+COCCOc1cc2ncnc(Nc3cccc(c3)C#C)c2cc1OCCOC	erlotinib
+COCCOC(=O)N1C(=O)[C@]2([C@@H]([C@@H]3N([C@@H]2c2ccccc2OCCO)[C@H]([C@H](OC3=O)c2ccccc2)c2ccccc2)C(=O)NCC=C)c2cc(ccc12)C#CCC(C(=O)OC)C(=O)OC	BRD-K94991378
+COc1cc2nc(nc(NC3CCN(Cc4ccccc4)CC3)c2cc1OC)N1CCCN(C)CC1	BIX-01294
+CC(=O)Nc1ccc(cc1)C(=O)Nc1ccccc1N	tacedinaline
+Cc1[nH]c2ccccc2c1CCNCc1ccc(\C=C\C(=O)NO)cc1	LBH-589
+Cc1ccccc1-n1c(Cn2cnc3c(N)ncnc23)nc2cccc(C)c2c1=O	IC-87114
+CCC1NC(=O)C([C@H](O)[C@H](C)C\C=C\C)N(C)C(=O)C(C(C)C)N(C)C(=O)C(CC(C)C)N(C)C(=O)C(CC(C)C)N(C)C(=O)[C@@H](C)NC(=O)C(C)NC(=O)C(CC(C)C)N(C)C(=O)C(NC(=O)C(CC(C)C)N(C)C(=O)CN(C)C1=O)C(C)C	ciclosporin
+ONC(=O)CCCCCCC(=O)Nc1ccccc1	vorinostat
+CO[C@@H]1C[C@H](C[C@@H](C)[C@@H]2CC(=O)[C@H](C)\C=C(C)\[C@@H](O)[C@@H](OC)C(=O)[C@H](C)C[C@H](C)\C=C\C=C\C=C(C)\[C@H](C[C@@H]3CC[C@@H](C)[C@@](O)(O3)C(=O)C(=O)N3CCCC[C@H]3C(=O)O2)OC)CC[C@H]1O	sirolimus
+O=c1cc(oc(c1)-c1cccc2Sc3ccccc3Sc12)N1CCOCC1	KU-55933
+N[C@@H](CC(=O)N1CCn2c(C1)nnc2C(F)(F)F)Cc1cc(F)c(F)cc1F	sitagliptin
+CC1(C)CCC(C)(C)c2cc(ccc12)C(=O)Nc1ccc(cc1)C(O)=O	AM-580
+CCCCCCCCCC(=O)N[C@H](CN1CCOCC1)[C@H](O)c1ccccc1	PDMP
+COC(=O)C(CC#Cc1ccc2NC(=O)[C@@]3([C@H]([C@H]4N([C@H]3c3ccccc3OCCO)[C@@H]([C@@H](OC4=O)c3ccccc3)c3ccccc3)C(=O)N3CCN(CC3)c3ncccn3)c2c1)C(=O)OC	BRD-K71935468
+CC(C)C[C@H](NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CC(C)C)NC(=O)OCc1ccccc1)C=O	MG-132
+Nc1ccccc1NC(=O)c1ccc(CNC(=O)OCc2cccnc2)cc1	entinostat
+ONC(=O)\C=C\c1cccc(c1)S(=O)(=O)Nc1ccccc1	belinostat
+N[C@H](CSCCB(O)O)C(O)=O	BEC
+CC[C@@H](C)[C@@H]1NC(=O)[C@H](Cc2cn(OC)c3ccccc23)NC(=O)[C@H](CCCCCC(=O)CC)NC(=O)[C@H]2CCCCN2C1=O	apicidin
+CC(=O)Nc1ccc(cc1)C(=O)Nc1cc(ccc1N)-c1cccs1	Merck60
+CN1CCCCC1NC(=O)[C@H](CCCCCC(C)=O)C(=O)Nc1nc(cs1)-c1ccccc1	BRD-A94377914
+CCCCCCN(CCCCCC)C(=O)Cc1c([nH]c2ccccc12)-c1ccc(F)cc1	FGIN-1-27
+CCN(CC)c1ccc(cc1[N+]([O-])=O)C1=NNC(=O)CC1C	compound 1B
+CC[C@]1(O)C[C@@H]2CN(C1)CCc1c([nH]c3ccccc13)[C@@](C2)(C(=O)OC)c1cc2c(cc1OC)N(C=O)[C@@H]1[C@]22CCN3CC=C[C@](CC)([C@@H]23)[C@@H](OC(C)=O)[C@]1(O)C(=O)OC	vincristine
+Nc1ccn([C@@H]2O[C@H](CO)[C@@H](O)[C@@H]2O)c(=O)n1	cytarabine hydrochloride
+CCC(C)n1ncn(-c2ccc(cc2)N2CCN(CC2)c2ccc(OCC3COC(Cn4cncn4)(O3)c3ccc(Cl)cc3Cl)cc2)c1=O	itraconazole
+CCOc1ccccc1-n1c(=O)c2ccccc2nc1C(C)N1CCN(CC1)C(=O)COc1ccc(Cl)cc1	erastin
+Cc1cc(C(=O)CN2C(=O)CCC2=O)c(C)n1Cc1ccccc1	ML031
+ON=C1c2cc(ccc2-c2ccc(cc12)S(=O)(=O)N1CCCCC1)S(=O)(=O)N1CCCCC1	CIL56
+CCOc1ccccc1C1CC(=O)Nc2cc3OCOc3cc12	FQI-1
+COc1ccc(cc1[N+]([O-])=O)S(=O)(=O)N(C(C)=O)c1ccc(OC(C)=O)c2ccccc12	BRD-K92856060
+O=c1n(Cc2ccccc2)c(\C=C\c2cccnc2)nc2ccccc12	B02
+ClC1=C(NCC=C)C(=O)c2ccccc2C1=O	BRD-K45681478
+Brc1cc2OCOc2cc1C1Nc2ccccc2C2C=CCC12	ML050
+COc1ccc(cc1Cl)N(C(C(=O)NCCc1ccccc1)c1cccs1)C(=O)CCl	ML162
+N=C(NOC(=O)C12CC3CC(CC(C3)C1)C2)c1ccccc1	CIL41
+OC(=O)c1cc2cc(OCc3ccccc3)ccc2[nH]1	NSC30930
+Clc1ccc(CC(=N)NOC(=O)c2cccc3ccccc23)cc1	CIL70
+CC1(C)CN=C(S1)N1CCN(CC1)c1ncnc2sc3CCCCc3c12	MI-1
+C(Nc1nc(NCc2ccccc2)c2ccccc2n1)c1ccccc1	DBeQ
+COc1cc(c(Cl)cc1Cl)-n1c(=S)[nH]c2ccccc2c1=O	Mdivi-1
+COc1ccc(cc1)S(=O)(=O)N1CCN(CC1)S(=O)(=O)c1ccc2OCCOc2c1	ML083
+CN(C1CCS(=O)(=O)C1)C(=O)COC(=O)\C=C\c1cccc(c1)[N+]([O-])=O	CID-5951923
+Cc1cc(C(=O)CN2CCCC2)c(C)n1-c1ccc(F)cc1	IU1
+CC1CC2C3CCC4=CC(=O)C=CC4(C)C3(F)C(O)CC2(C)C1(O)C(=O)CO	dexamethasone
+CCN1CCN(CC1)C(c1ccc(cc1)C(F)(F)F)c1ccc2cccnc2c1O	ML311
+CN1CCN(CC1)c1cc(Nc2cc(C)[nH]n2)nc(Sc2ccc(NC(=O)C3CC3)cc2)n1	VX-680
+CN1CCN(Cc2ccc(cc2)C(=O)Nc2ccc(C)c(Nc3nccc(n3)-c3cccnc3)c2)CC1	imatinib
+Nc1nc(OCc2ccccc2)c2[nH]cnc2n1	O-6-benzylguanine
+Nc1ncn([C@H]2C[C@H](O)[C@@H](CO)O2)c(=O)n1	decitabine
+Cc1c[nH]c(n1)-c1cnc(NCCNc2ccc(cn2)C#N)nc1-c1ccc(Cl)cc1Cl	CHIR-99021
+CC[C@H]1N(C2CCCC2)c2nc(Nc3ccc(cc3OC)C(=O)NC3CCN(C)CC3)ncc2N(C)C1=O	BI-2536
+Nc1ccc(cc1NC(=O)c1ccc(cc1)C(=O)NCCc1ccncc1)-c1cccs1	BRD-K61166597
+CNC(=O)c1ccccc1Sc1ccc2c(\C=C\c3ccccn3)n[nH]c2c1	axitinib
+Cn1cnc2c(F)c(Nc3ccc(Br)cc3Cl)c(cc12)C(=O)NOCCO	selumetinib
+Cn1c2cnc3ccc(cc3c2n(-c2ccc(cc2)C(C)(C)C#N)c1=O)-c1cnc2ccccc2c1	NVP-BEZ235
+COc1cc2ncn(-c3cc(OCc4ccccc4C(F)(F)F)c(s3)C(N)=O)c2cc1OC	GW-843682X
+COc1cc2c(Nc3ccc(Br)cc3F)ncnc2cc1OCC1CCN(C)CC1	vandetanib
+CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3ccc(Cl)c(c3)C(F)(F)F)cc2)ccn1	sorafenib
+Cc1cc2nc(NCCCO)n(CC(=O)c3cc(c(O)c(c3)C(C)(C)C)C(C)(C)C)c2cc1C	ML029
+CN1N=Nc2c(ncn2C1=O)C(=O)N	temozolomide
+COC(=O)c1ccc2n(CCCc3ccccc3)c(NC(=O)c3ccccc3)nc2c1	QW-BI-011
+CC(=O)N[C@@H]1C\C=C\CCC(=O)N[C@@H](COC1=O)c1ccccc1	BRD-K90370028
+CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	navitoclax
+Cc1cc2c(cc1C(=C)c1ccc(cc1)C(O)=O)C(C)(C)CCC2(C)C	bexarotene
+Cc1cn(cn1)-c1cc(NC(=O)c2ccc(C)c(Nc3nccc(n3)-c3cccnc3)c2)cc(c1)C(F)(F)F	nilotinib
+CCN(CC)CCNC(=O)c1c(C)[nH]c(\C=C2/C(=O)Nc3ccc(F)cc23)c1C	sunitinib
+Cn1c(CCCC(O)=O)nc2cc(ccc12)N(CCCl)CCCl	bendamustine
+COC(=O)C[C@](O)(CCCC(C)(C)O)C(=O)O[C@H]1[C@H]2c3cc4OCOc4cc3CCN3CCC[C@]23C=C1OC	omacetaxine mepesuccinate
+OC(=O)c1ccc2cc(ccc2c1)-c1ccc(O)c(c1)C12CC3CC(CC(C3)C1)C2	CD-437
+CC(C)c1ccc(Cn2ccc3c2ccc2nc(NC4CC4)nc(N)c32)cc1	SCH-79797
+CN1c2cc3c(cc2N=C(c2ccc(cc2)C(O)=O)c2ccccc12)C(C)(C)CCC3(C)C	LE-135
+Oc1ccc(Nc2nc(cs2)-c2ccc(Cl)cc2)cc1	SKI-II
+CCCCCCCCCCC(C)(C)C(=O)Nc1c(OC)cc(OC)cc1OC	CI-976
+N[Pt](N)(Cl)Cl	Platin
+CN1C(=S)NC(Cc2c[nH]c3ccccc23)C1=O	necrostatin-1
+COc1ccc2n(C(=O)c3cccc(Cl)c3Cl)c(C)c(CCN3CCOCC3)c2c1	GW-405833
+CCCCCCCCc1ccc(cc1)-c1ccc(cc1)C(O)=O	AC55649
+OCc1ccc(s1)-c1ccc(o1)-c1ccc(CO)s1	RITA
+CN(C)C(=O)n1nnnc1Cc1ccc(cc1)-c1ccccc1	LY-2183240
+COc1cc2nccc(Oc3ccc(NC(=O)Nc4ccc(F)cc4F)c(F)c3)c2cc1OC	Ki8751
+OC(=O)c1ccc(cc1)-c1ccc2cc(c(O)cc2c1)C12CC3CC(CC(C3)C1)C2	CD-1530
+NC(=O)Nc1sc(cc1C(N)=O)-c1ccc(F)cc1	TPCA-1
+O=C1O[Pt]2(NC3CCCCC3N2)OC1=O	oxaliplatin
+Cc1ccc(C=C2CNCC(=Cc3ccc(C)cc3)C2=O)cc1	NSC632839
+NS(=O)(=O)C#Cc1ccccc1	pifithrin-mu
+CCc1c2Cn3c(cc4c(COC(=O)C4(O)CC)c3=O)-c2nc2ccc(O)cc12	SN-38
+CC(=O)N1CCC(CC1)C(=O)Nc1cc(ccc1N)-c1cccs1	BRD-K80183349
+Nc1ccc(cc1NC(=O)C1=CCCC1)-c1cccs1	BRD-K66532283
+NC1(CCC1)c1ccc(cc1)-c1nc2ccn3c(n[nH]c3=O)c2cc1-c1ccccc1	MK-2206
+COc1ccc(OC)c(c1)-c1nnc2SCC(=Nn12)c1ccc(OC)c(OC)c1	triazolothiadiazine
+C[C@@H](CO)N1C[C@H](C)[C@H](CN(C)S(=O)(=O)c2ccc(Cl)cc2)Oc2ccc(NC(=O)CCC(F)(F)F)cc2CC1=O	BRD-K66453893
+CC(=O)NC1CCN(CC1)C(=O)Nc1cc(ccc1N)-c1cccs1	BRD-K11533227
+C[C@@H](CO)N1C[C@H](C)[C@@H](CN(C)C(=O)C2CCOCC2)Oc2ncc(cc2C1=O)C#CC1(O)CCCC1	BRD-K27224038
+C[C@H](CO)N1C[C@@H](C)[C@H](CN(C)C(=O)Nc2ccc3OCOc3c2)Oc2cc(ccc2S1(=O)=O)C#Cc1ccncc1	BRD-K33514849
+CC(C)CC#Cc1ccc2c(O[C@@H](CN(C)C(=O)c3cnccn3)[C@H](C)CN([C@H](C)CO)S2(=O)=O)c1	BRD-K14844214
+C[C@@H](CO)N1C[C@H](C)[C@@H](CN(C)Cc2ccc(cc2)C(O)=O)Oc2cc(ccc2S1(=O)=O)C#CCC1CCCC1	BRD1835
+C[C@H](CO)N1C[C@H](C)[C@H](CN(C)C(=O)Nc2cc(F)ccc2F)Oc2cc(ccc2S1(=O)=O)C#CC1CCCC1	BRD-K41597374
+C[C@@H](CO)N1C[C@H](C)[C@@H](CN(C)C(=O)Nc2ccc3OCOc3c2)Oc2cc(ccc2S1(=O)=O)C#Cc1ccncc1	BRD-K63431240
+C[C@@H](CO)N1C[C@H](C)[C@H](CN(C)C(=O)Cc2ccncc2)Oc2cc(ccc2S1(=O)=O)C#Cc1ccccc1F	BRD-K13999467
+C\C=C\c1ccc2c(O[C@@H](CN(C)C(=O)c3ccccc3)[C@@H](C)CN([C@@H](C)CO)S2(=O)=O)c1	BRD-K96970199
+CC1CCC\C=C/C2CC(O)CC2C(O)\C=C/C(=O)O1	brefeldin A
+Clc1ccc(Cl)c(c1)-c1ccc(\C=C(/C#N)C(=O)Nc2cccc3ncccc23)o1	AGK-2
+CC(C)C[C@H](NC(=O)[C@@H](C[C@@H](O)[C@H](Cc1ccccc1)NC(=O)OC(C)(C)C)Cc1ccccc1)C(=O)N[C@@H](Cc1ccccc1)C(N)=O	L-685458
+O=C(Nc1ccccc1)N1CCC(Cc2cnc3ccccc3c2)CC1	PF-750
+CC(C)[C@]12O[C@H]1[C@@H]1O[C@]11[C@]3(O[C@H]3CC3C4=C(CC[C@]13C)C(=O)OC4)[C@@H]2O	triptolide
+COc1ccc(C2=NC(C(N2C(=O)N2CCNC(=O)C2)c2ccc(Cl)cc2)c2ccc(Cl)cc2)c(OC(C)C)c1	nutlin-3
+CCCCC\C=C/C\C=C/C\C=C/C\C=C/CCCC(=O)C(F)(F)F	AA-COCF3
+C[C@]12CC[C@H]3[C@@H](CC[C@H]4C[C@H](O)CC[C@]34C)[C@@H]1C[C@H](Br)C2=O	16-beta-bromoandrosterone
+Brc1ccc(OCc2ccccc2Br)c(\C=C2\SC(=S)NC2=O)c1	PRL-3 inhibitor I
+CCc1ccccc1NC(=O)CSC(=O)NNC(=O)[C@@H](Cc1c[nH]c2ccccc12)NC(=O)OC(C)(C)C	SID 26681509
+O=C(NC1CC1)c1cc(on1)-c1cccs1	neuronal differentiation inducer III
+Cc1ccc(cc1)S(=O)(=O)OCC(=O)Nc1ccc(C(O)=O)c(O)c1	NSC 74859
+CC(C)C[C@H](NC(=O)[C@H](Cc1ccccc1)NC(=O)c1cnccn1)B(O)O	bortezomib
+CN(C)CC[C@H](CSc1ccccc1)Nc1ccc(cc1[N+]([O-])=O)S(=O)(=O)NC(=O)c1ccc(cc1)N1CCN(Cc2ccccc2-c2ccc(Cl)cc2)CC1	ABT-737
+OC[C@H]1O[C@H](C(O)[C@H]1O)n1cccnc1=O	zebularine
+CN1CCc2c(C1)c1ccccc1n2Cc1ccc(cc1)C(=O)NO	tubastatin A
+CON(C)C(=O)[C@H]1[C@@H](O)[C@@]2(O)c3c(O[C@]2([C@@H]1c1ccccc1)c1ccc(OC)cc1)cc(OC)cc3OC	SR-II-138A
+CCC[C@H]1C[C@H](C[C@H](C)C[C@@H]2C[C@H](C[C@H](CC(=O)O1)O2)OC(=O)\C=C/CCc1coc(\C=C/CNC(=O)OC)n1)OC	neopeltolide
+C\C1=C\CC[C@@]2(C)O[C@@H]2[C@H]2OC(=O)C(=C)[C@@H]2CC1	parthenolide
+CCOC(=O)\C=C/n1nnc(n1)-c1cccc(Cl)c1	Compound 7d-cis
+Cc1cnc(Nc2ccc(OCCN3CCCC3)cc2)nc1Nc1cccc(c1)S(=O)(=O)NC(C)(C)C	TG-101348
+NS(=O)(=O)OC[C@@H]1C[C@H](C[C@@H]1O)n1ccc2c(N[C@H]3CCc4ccccc34)ncnc12	pevonedistat
+CN(C)C(=O)c1ccc(cc1)S(=O)(=O)c1ccc(NC(=O)[C@@](C)(O)C(F)(F)F)c(Cl)c1	AZD7545
+Nc1ncnc2n([C@@H]3O[C@H](COCc4ccc(cc4)C#N)[C@@H](O)[C@H]3O)c(NCc3ccc(Cl)c(Cl)c3)nc12	VER-155008
+Nc1cccc(c1)S(=O)(=O)N1CCCN(CC1)S(=O)(=O)c1ccc2OCCOc2c1	ML203
+O=C(Nc1cc(CN2CCNCC2)cc(c1)-c1nc2ccccc2[nH]1)c1cnc2ccccc2n1	SRT-1720
+O=C(NCCN1CCC2(CC1)N(CNC2=O)c1ccccc1)c1ccc2ccccc2c1	CAY10594
+Oc1cccc2cc(C(=O)Nc3cccc(c3)-c3cn4ccccc4n3)c(=O)oc12	Compound 1541A
+OC(=O)[C@H](Cc1c[nH]c2ccccc12)N1C(=O)c2ccccc2C1=O	RG-108
+Oc1c(CC=C)cccc1\C=N\NC(=O)CN1CCN(Cc2ccccc2)CC1	PAC-1
+CN1C(=O)N(Cc2cnc(Nc3cc(C)nn3C)nc12)c1cc(NC(=O)c2cccc(c2)C(F)(F)F)ccc1C	pluripotin
+Clc1ccc(OCCCCCC\N=C(\NC#N)Nc2ccncc2)cc1	GMX-1778
+CC1(C)Oc2ccc3C4=C[C@@]56NC(=O)[C@]7(CCCN7C5=O)C[C@H]6C(C)(C)C4=[N+]([O-])c3c2C=C1	avrainvillamide
+Cc1cc(cc2[nH]c(nc12)-c1c(NC[C@@H](O)c2cccc(Cl)c2)cc[nH]c1=O)N1CCOCC1	BMS-536924
+Nc1ccn([C@@H]2O[C@H](CO)[C@@H](O)C2(F)F)c(=O)n1	gemcitabine
+Oc1cccc(C(=O)Nc2cccc(NC(=O)c3cccc(O)c3O)c2)c1O	MST-312
+Fc1ccc(Cc2n[nH]c(=O)c3ccccc23)cc1C(=O)N1CCN(CC1)C(=O)C1CC1	olaparib
+CCC1CCC2OC3(CC[C@@H](C)C(C[C@H](C)O)O3)[C@H](C)C(OC(=O)\C=C\[C@@H](C)[C@H](O)[C@@H](C)C(=O)[C@H](C)[C@@H](O)[C@H](C)C(=O)[C@@](C)(O)[C@H](O)[C@@H](C)C\C=C\C=C\1)[C@H]2C	oligomycin A
+NS(=O)(=O)c1ccc(cc1)S(=O)(=O)Nc1cccc2c(Cl)c[nH]c12	indisulam
+OC[C@@H]1O[C@@H](CC(=O)NCc2ccncn2)CC[C@H]1NC(=O)c1ccc(F)cc1	BRD-K49290616
+CN1CCN(CC1)C(=O)C[C@@H]1O[C@H](CO)[C@@H](NS(=O)(=O)c2cccc(F)c2)C=C1	BRD-K02492147
+CC(C)(O)CCc1ccc(O)c2c1oc1cc3O[C@H]4OC=C[C@@]4(O)c3c(O)c1c2=O	austocystin D
+CCOc1cc(cc(Cl)c1OCC(=O)OC)\C=C1C(=O)N(N=C/1C)c1ccccc1	SJ-172550
+C[C@@H](NC(=O)C[C@@H]1CC[C@@H](NC(=O)CN2CCOCC2)[C@H](CO)O1)c1ccccc1	BRD-K09587429
+ONC(=O)\C=C\c1ccc(cc1)C(=O)N\N=C\c1ccc(O)c(O)c1O	pandacostat
+CN1CCN(CC1)C(=O)C[C@H]1CC[C@H](NC(=O)c2ccc3OCOc3c2)[C@@H](CO)O1	BRD-K96431673
+Fc1ccc(Nc2c(cnc3c(Cl)cc(NCc4cnc[nH]4)cc23)C#N)cc1Cl	cyanoquinoline 11
+Cn1cncc1[C@@](N)(c1ccc(Cl)cc1)c1ccc2n(C)c(=O)cc(-c3cccc(Cl)c3)c2c1	tipifarnib-P2
+Cn1cncc1[C@](N)(c1ccc(Cl)cc1)c1ccc2n(C)c(=O)cc(-c3cccc(Cl)c3)c2c1	tipifarnib-P1
+CN(C)[C@H]1CC[C@H]2[C@@H](CC[C@H]3[C@@H]4CC=C(c5ccc6cnccc6c5)[C@@]4(C)CC[C@H]23)C1	Compound 23 citrate
+C[C@H]1C[C@@H](OC1=O)[C@@H](O)[C@@H](C(Cl)Cl)c1ccc2[C@@H]3C[C@@H](Br)[C@]45O[C@H](C[C@]4(C)[C@H]3C(=O)c2c1C)CO[C@H]5O	nakiterpiosin
+Cc1[nH]c2ccccc2c1C(Nc1ccccn1)c1ccc(Cl)cc1	CCT036477
+COc1cc(Nc2ncc(F)c(Nc3ccc4OC(C)(C)C(=O)Nc4n3)n2)cc(OC)c1OC	tamatinib
+CCCCCCC(=O)CCCCCC\C=C\C[C@H](O)[C@@H](O)C(N)(CO)C(O)=O	myriocin
+COCCn1c2c(C(=O)c3ccccc3C2=O)[n+](Cc2cnccn2)c1C	YM-155
+C[C@]1(CCCN1c1nc(Nc2cc(n[nH]2)C2CC2)c2cccn2n1)C(=O)Nc1ccc(F)nc1	BMS-754807
+C\C(=C/C(=O)Nc1ccccc1C(O)=O)c1ccc2ccccc2c1	BIBR-1532
+CC(C)C[C@H]([C@H](O)C(=O)NO)C(=O)N[C@H](C(=O)OC1CCCC1)c1ccccc1	tosedostat
+CCOc1cc2ncc(C#N)c(Nc3ccc(OCc4ccccn4)c(Cl)c3)c2cc1NC(=O)\C=C\CN(C)C	neratinib
+Oc1ccc(C[C@@H]2N3[C@H](CN(Cc4cccc5ccccc45)C2=O)N(CCC3=O)C(=O)NCc2ccccc2)cc1	BRD1812
+CC1=NN(C(=O)C\1=C\c1ccc(o1)-c1cc(C)c(C)cc1[N+]([O-])=O)c1ccc(cc1)C(O)=O	BRD8958
+C(Cc1c[nH]c2ccccc12)Nc1cccc(Nc2ccncc2)c1	serdemetan
+O=C(NCCCCC1CCN(CC1)C(=O)c1ccccc1)\C=C\c1cccnc1	daporinad
+CN1CCN(CC1)c1ccc(Nc2ncc3c(n2)n(-c2cccc(n2)C(C)(C)O)n(CC=C)c3=O)cc1	MK-1775
+COc1cc2nccc(Oc3ccc(NC(=O)Nc4cc(C)on4)c(Cl)c3)c2cc1OC	tivozanib
+COc1ccc2c3C[C@@H]4N([C@@H](CC(C)C)c3[nH]c2c1)C(=O)[C@H](CCC(=O)OC(C)(C)C)NC4=O	Ko-143
+CONC(=O)[C@H]1[C@@H](O)[C@@]2(O)c3c(O[C@]2([C@@H]1c1ccccc1)c1ccc(OC)cc1)cc(OC)cc3OC	CR-1-31B
+OC(=O)c1ccc(NCc2nc3cc4ccccc4cc3[nH]2)cc1	BRD-K71781559
+CO[C@@H]1CC[C@H]2CCN(C)C(=O)[C@@H](C)[C@H](CN(C)C(=O)c3cccc(C#N)c3OC[C@H]1O2)OC	BRD-K86535717
+C[C@H](CO)N1C[C@H](C)[C@@H](CN(C)C(=O)NC2CCCCC2)Oc2ccc(NC(=O)Cc3cn(C)c4ccccc34)cc2C1=O	BRD-K48334597
+CC(C)NC(=O)Nc1ccc2O[C@@H](CN(C)S(=O)(=O)c3ccc(Cl)cc3)[C@H](C)CN([C@H](C)CO)C(=O)c2c1	ML312
+C[C@@H](CO)N1C[C@@H](C)[C@@H](CN(C)CC2CCCCC2)Oc2ccc(NC(=O)Nc3c(C)noc3C)cc2C1=O	BRD-K04800985
+C[C@H](CO)N1C[C@H](C)[C@H](CN(C)CC2CC2)Oc2ccc(NS(=O)(=O)c3cn(C)cn3)cc2C1=O	BRD-K78574327
+C[C@H](CO)N1C[C@H](C)[C@H](CN(C)Cc2ccc(Cl)c(Cl)c2)Oc2ccc(cc2C1=O)N(C)C	BRD-K19103580
+CC(C)NC(=O)N(C)C[C@H]1Oc2ccc(cc2C(=O)N(C[C@H]1C)[C@H](C)CO)N(C)C	BRD-K30019337
+C[C@H](CO)N1C[C@H](C)[C@@H](CN(C)C)Oc2c(NC(=O)c3cc(C)nn3C)cccc2C1=O	BRD-K84807411
+COc1ccc(NC(=O)Nc2ccc3O[C@@H](CN(C)Cc4ccc5OCOc5c4)[C@@H](C)CN([C@@H](C)CO)C(=O)c3c2)cc1	BRD-K01737880
+CNC[C@@H]1Oc2ccc(NC(=O)C3CCCCC3)cc2C(=O)N(C[C@@H]1C)[C@@H](C)CO	BRD-K44224150
+C[C@@H](CO)N1C[C@@H](C)[C@H](CN(C)C(=O)Nc2cccc3ccccc23)Oc2c(NC(=O)c3ccncc3)cccc2C1=O	BRD-K75293299
+COc1ccc(cc1)S(=O)(=O)N(C)C[C@@H]1Oc2c(NC(=O)Nc3cccc4ccccc34)cccc2C(=O)N(C[C@H]1C)[C@@H](C)CO	BRD-K64610608
+C[C@H](CO)N1C[C@@H](C)[C@H](CN(C)Cc2ccc3OCOc3c2)Oc2c(NC(=O)c3ccncc3)cccc2C1=O	BRD-K09344309
+C[C@H](CO)N1C[C@H](C)[C@H](CN(C)C(=O)NC2CCCCC2)Oc2c(NS(=O)(=O)c3ccc(F)cc3)cccc2C1=O	BRD-K02251932
+C[C@@H](CO)N1C[C@@H](C)[C@@H](CN(C)Cc2ccc(cc2)C(=O)Nc2ccccc2N)Oc2c(NC(=O)Nc3ccccc3)cccc2C1=O	BRD-K55116708
+CNC[C@@H]1Oc2ccc(NS(C)(=O)=O)cc2CC(=O)N(C[C@@H]1C)[C@H](C)CO	BRD-K41334119
+CNC[C@@H]1Oc2ccc(NC(=O)CCN3CCOCC3)cc2CC(=O)N(C[C@@H]1C)[C@H](C)CO	BRD-K34485477
+CC(C)NC(=O)Nc1ccc2O[C@@H](CN(C)S(C)(=O)=O)[C@@H](C)CN([C@H](C)CO)C(=O)Cc2c1	BRD-K16147474
+C[C@H](CO)N1C[C@@H](C)[C@@H](CN(C)Cc2ccc(cc2)C(O)=O)Oc2ccc(NC(=O)Nc3ccc(F)cc3)cc2CC1=O	BRD-K29086754
+CNC[C@@H]1Oc2ccc(cc2CC(=O)N(C[C@@H]1C)[C@@H](C)CO)N(C)C	BRD-K33199242
+C[C@@H](CO)N1C[C@H](C)[C@H](CN(C)C(=O)Nc2cccc3ccccc23)Oc2ccc(NC(=O)NC3CCCCC3)cc2CC1=O	BRD-K52037352
+C[C@H](CO)N1C[C@H](C)[C@H](CN(C)Cc2ccc3OCCOc3c2)OCc2cn(CCCC1=O)nn2	BRD-K27986637
+C[C@H](CO)N1C[C@H](C)[C@@H](CN(C)C(=O)Nc2cccc3ccccc23)Oc2ccc(NC(=O)c3ccncc3)cc2CC1=O	BRD-K37390332
+COc1cc2c(ncnc2cc1OCCCN1CCCCC1)N1CCN(CC1)C(=O)Nc1ccc(OC(C)C)cc1	tandutinib
+C[C@]12CC[C@H]3[C@H]([C@@H]1CC[C@@H]2O)[C@H](CCCCCCCCCS(=O)CCCC(F)(F)C(F)(F)F)Cc1cc(O)ccc31	fulvestrant
+CO[C@H]1\C=C\C=C(C)\C[C@@H](C)[C@H](O)[C@H](C)\C=C(C)\C=C(OC)\C(=O)O[C@@H]1[C@@H](C)[C@@H](O)[C@H](C)[C@H]1C[C@@H](O)[C@H](C)[C@H](O1)C(C)C	bafilomycin A1
+ONC(=O)c1ccncc1	isonicotinohydroxamic acid
+CN(C)CCCNc1c2ccccc2n(C)c2nc(=O)n(C)c(=O)c12	HLI 373
+CCC(=O)OCN1C(=O)C=CC1=O	NSC19630
+O[As](O)(=O)c1ccc(Cc2ccc(cc2)[As](O)(O)=O)cc1	NSC48300
+COC[C@]1(CO)[N@@]2CC[C@@H](CC2)C1=O	PRIMA-1-Met
+CN1C2N(CCc3c2[nH]c2ccccc32)C(=O)c2ccccc12	isoevodiamine
+COc1cc2c(NC3CCN(CC3)C(C)C)nc(nc2cc1OCCCN1CCCC1)C1CCCCC1	UNC0638
+CC(C)(O)\C=C\C(=O)[C@](C)(O)C1[C@H](O)C[C@@]2(C)C3CC=C4C(CC(=O)C(=O)C4(C)C)[C@]3(C)C(=O)C[C@]12C	cucurbitacin I
+COc1ccccc1-c1cccc(c1)-c1nc(cc2CN([C@@H](CCO)c12)[S@@](=O)C(C)(C)C)C(=O)NCc1ccncc1	BRD-K50799972
+CN(C)CC(=O)N[C@@H]1CC[C@@H](CCNC(=O)Nc2ccc(F)cc2)O[C@H]1CO	BRD-K17060750
+CCN(CCO)CCCOc1ccc2c(Nc3cc(CC(=O)Nc4cccc(F)c4)[nH]n3)ncnc2c1	barasertib
+Cc1ccc(F)c(NC(=O)Nc2ccc(cc2)-c2cccc3[nH]nc(N)c23)c1	linifanib
+C[C@@]1(CCCN1)c1nc2c(cccc2[nH]1)C(N)=O	veliparib
+CN1CCN(CCOc2cc(OC3CCOCC3)c3c(Nc4c5OCOc5ccc4Cl)ncnc3c2)CC1	saracatinib
+CN(C)C\C=C\C(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1O[C@H]1CCOC1	afatinib
+COc1cc2c(Oc3ccc4[nH]c(C)cc4c3F)ncnc2cc1OCCCN1CCCC1	cediranib
+Fc1ccc(Nc2ncnc3cc(OCCCN4CCOCC4)c(NC(=O)C=C)cc23)cc1Cl	canertinib
+COC1=CC(=N\C\1=C/c1[nH]c(C)cc1C)c1cc2ccccc2[nH]1	obatoclax
+CN1CCN(Cc2ccc(cc2)C(=O)Nc2ccc(C)c(Nc3nc(cs3)-c3cccnc3)c2)CC1	masitinib
+FC(F)c1nc2ccccc2n1-c1nc(nc(n1)N1CCOCC1)N1CCOCC1	ZSTK474
+C[C@@H](O)COc1cn2ncnc(Oc3ccc4[nH]c(C)cc4c3F)c2c1C	brivanib
+OCCn1cc(c(n1)-c1ccncc1)-c1ccc2c(CC\C2=N/O)c1	GDC-0879
+COc1cc(ccc1Nc1ncc(Cl)c(Nc2ccccc2S(=O)(=O)C(C)C)n1)N1CCC(CC1)N1CCN(C)CC1	NVP-TAE684
+CC(C)(C)c1cnc(CSc2cnc(NC(=O)C3CCNCC3)s2)o1	SNS-032
+CCCS(=O)(=O)Nc1ccc(F)c(C(=O)c2c[nH]c3ncc(Cl)cc23)c1F	PLX-4720
+CC(Nc1ccccc1)c1cc(C)cn2c1nc(cc2=O)N1CCOCC1	TGX-221
+COc1ccc(cc1CO)-c1ccc2c(nc(nc2n1)N1C[C@H](C)O[C@H](C)C1)N1CCOCC1	KU-0063794
+Nc1nc(N)c2nc(-c3cccc(O)c3)c(nc2n1)-c1cccc(O)c1	TG-100-115
+O=C1NC(=O)\C(S1)=C\c1ccc2nccc(-c3ccncc3)c2c1	GSK1059615
+CN(c1cccc(Cl)c1)S(=O)(=O)c1ccc2NC(=O)\C(=C/c3[nH]c(C)c(C(=O)N4CCN(C)CC4)c3C)c2c1	SU11274
+COc1ccc(Cn2ccc3ccc(cc23)C(=O)NO)cc1	BRD-K88742110
+COc1cc(ccc1Nc1ncc2N(C)C(=O)c3ccccc3N(C)c2n1)C(=O)N1CCC(CC1)N1CCN(C)CC1	LRRK2-IN-1
+CC(=O)NC[C@@H]1C[C@H](CN1)NS(=O)(=O)c1cccc2cncc(C)c12	BRD8899
+NC(=O)[C@H]1CCCc2c1[nH]c1ccc(Cl)cc21	EX-527
+O=S(=O)(N1CCCc2ccccc12)c1ccc(cc1)-c1cnc(o1)C1CC1	ELCPK
+CCOC(=O)c1c(NC(=O)c2ccc(s2)[N+]([O-])=O)sc2c1CC(C)(C)NC2(C)C	NPC-26
+COC(=O)[C@H]1Cc2c([nH]c3ccccc23)[C@@H](N1C(=O)CCl)c1ccc(cc1)C(=O)OC	1S-3R-RSL-3
+CN(C)CCNC(=O)c1cc2CSc3ccc(Cl)cc3-c2s1	CIL55A
+CN(C)CCCNc1nc(CN2CCN(CC2)C(c2ccc(Cl)cc2)c2ccc(Cl)cc2)nc2ccccc12	SCH-529074
+CC(C)n1cnc2c(NCCc3ccc(O)cc3)nc(nc12)-c1csc2ccccc12	StemRegenin 1
+CCOc1ccccc1-c1cc(=O)[nH]c2cc3OCOc3cc12	FQI-2
+Cc1onc(C(=O)N2CCN(CC2)C(c2ccc(Cl)cc2)c2ccc(Cl)cc2)c1[N+]([O-])=O	ML210
+C[As](C)SC[C@H](NC(=O)CC[C@H](N)C(O)=O)C(=O)NCC(O)=O	darinaparsin
+CCC(C)SSc1ncc[nH]1	PX-12
+CN(C)c1ccccc1CN1CCCN(Cc2ccccc2N(C)C)C1c1ccncc1	GANT-61
+COc1cc(\C=C\C(=O)N2CCC=CC2=O)cc(OC)c1OCCN(C)CCOc1c(OC)cc(\C=C\C(=O)N2CCC=CC2=O)cc1OC	PL-DI
+CC(C)c1ccccc1Cc1cc(C(=O)Nc2ccc(cc2)S(=O)(=O)c2ccccc2C(C)(C)C)c(O)c(O)c1O	TW-37
+COc1ccc(cc1CO)-c1ccc2c(nc(nc2n1)N1CCOC[C@@H]1C)N1CCOC[C@@H]1C	AZD8055
+Fc1ccccc1-c1cc(=O)c2cc3OCOc3cc2[nH]1	CHM-1
+OC[C@H](Cc1ccccc1)Nc1nc(Oc2ccc3CCCc3c2)nc2n(Cc3ccc(cc3)-c3ccccc3)cnc12	QS-11
+Clc1cc(Cl)c(OCC(=O)N\N=C\c2ccc[nH]2)c(Cl)c1	ML239
+CC(C(=O)Nc1cccc(c1)\N=C\c1c(O)ccc2ccccc12)c1ccccc1	salermide
+CCCC[C@@H](C)[C@@H](OC(=O)C[C@@H](CC(O)=O)C(O)=O)[C@H](CC(C)C[C@H](O)CCCC[C@@H](O)C[C@H](O)[C@H](C)N)OC(=O)C[C@@H](CC(O)=O)C(O)=O	fumonisin B1
+Cc1sc-2c(c1C)C(=N[C@@H](CC(=O)OC(C)(C)C)c1nnc(C)n-21)c1ccc(Cl)cc1	JQ-1
+ONC(=O)c1cccc(c1)C(=O)Nc1ccccc1	BRD-K51490254
+CC(=O)N[C@H]1C[C@H](C1)C(=O)Nc1cc(ccc1N)-c1ccc(F)cc1	BRD-K85133207
+Cc1cnc2c(NCCN)nc3ccc(C)cc3n12	BMS-345541
+COc1cc2ncn(-c3cc(OCc4ccccc4S(C)(=O)=O)c(s3)C#N)c2cc1OC	CAY10576
+Cc1ccc(cc1)C(=O)NCCCCCC(=O)Nc1ccc(F)cc1N	Repligen 136
+COC(=O)c1ccc2c(NC(=O)\C2=C(/Nc2ccc(cc2)N(C)C(=O)CN2CCN(C)CC2)c2ccccc2)c1	nintedanib
+C[C@@H](Oc1cc(cnc1N)-c1cnn(c1)C1CCNCC1)c1c(Cl)ccc(F)c1Cl	crizotinib
+COc1cc2c(Oc3ccc(NC(=O)C4(CC4)C(=O)Nc4ccc(F)cc4)cc3F)ccnc2cc1OCCCN1CCOCC1	foretinib
+CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3ccc(Cl)c(c3)C(F)(F)F)c(F)c2)ccn1	regorafenib
+CN1CCN(CC1)c1ccc(Nc2ncc(Cl)c(Sc3cccc(NC(=O)C=C)c3)n2)cc1	WZ8040
+FC(F)(F)Oc1ccc(NC(=O)c2sccc2NCc2ccnc3ccccc23)cc1	OSI-930
+Cn1cnc(c1)-c1cc2nccc(Oc3ccc(NC(=S)NC(=O)Cc4ccccc4)cc3F)c2s1	MGCD-265
+COc1cc2nccc(Oc3ccc(NC(=O)NC4CC4)c(Cl)c3)c2cc1C(N)=O	lenvatinib
+COc1ccc(cc1)C(=O)CC1(O)C(=O)Nc2c1c(Cl)ccc2Cl	YK 4-279
+O=C(CCCCCCCn1cc(nn1)-c1cccnc1)Nc1ccccc1-c1ccccc1	CAY10618
+CCN1CCN(CC(=O)Nc2ccc(-c3cccc4c3oc(cc4=O)N3CCOCC3)c3sc4ccccc4c23)CC1	KU 0060648
+O[C@H]1C=C2[C@@H](NC(=O)c3c(O)c4OCOc4cc23)[C@H](O)[C@@H]1O	narciclasine
+CC(C)C[C@H](NC(=O)CNC(=O)c1cc(Cl)ccc1Cl)B(O)O	MLN2238
+CC(C)(C)OC(=O)Nc1ccc(cc1)-c1cc(no1)C(=O)NCCCCCCC(=O)NO	ISOX
+CS(=O)(=O)CCNCc1ccc(o1)-c1ccc2ncnc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)c2c1	lapatinib
+CC(=O)Nc1ccc(cc1)C(=O)Nc1ccc(F)cc1N	BRD-K29313308
+COc1cc2c(NC3CCN(C)CC3)nc(nc2cc1OCCOCCN(C)C)N1CCCN(C)CC1	UNC0321
+Cn1cc(cn1)-c1ccc2nnc(Sc3ccc4ncccc4c3)n2n1	SGX-523
+C[C@H]1CN(C[C@@H](C)O1)c1ccc(NC(=O)c2cccc(-c3ccc(OC(F)(F)F)cc3)c2C)cn1	erismodegib
+COc1cc(Nc2ncc3CN=C(c4cc(Cl)ccc4-c3n2)c2c(F)cccc2OC)ccc1C(O)=O	alisertib
+C[C@@H](Nc1ccccc1C(O)=O)c1cc(C)cn2c1nc(cc2=O)N1CCOCC1	AZD6482
+N#CC[C@H](C1CCCC1)n1cc(cn1)-c1ncnc2[nH]ccc12	ruxolitinib
+C[C@@H](O)[C@@H](NC(=O)[C@H](C)[C@@H](O)[C@H](C)NC(=O)[C@@H](NC(=O)c1nc(nc(N)c1C)[C@H](CC(N)=O)NC[C@@H](N)C(N)=O)C(O[C@H]1O[C@H](CO)[C@H](O)[C@@H](O)[C@H]1O[C@H]1O[C@H](CO)[C@@H](O)[C@H](OC(N)=O)[C@@H]1O)c1c[nH]cn1)C(=O)NCCc1nc(cs1)-c1nc(cs1)C(=O)NCCC[S+](C)C	bleomycin A2
+CS(=O)(=O)N1CCN(Cc2cc3nc(nc(N4CCOCC4)c3s2)-c2cccc3[nH]ncc23)CC1	GDC-0941
+Cc1cccc(n1)-c1[nH]c(nc1-c1ccc2nccnc2c1)C(C)(C)C	SB-525334
+CC(C)CC(=O)Nc1n[nH]c2c1CN(C(=O)C1CCN(C)CC1)C2(C)C	PHA-793887
+CC(C)(C)c1cc(NC(=O)Nc2ccc(cc2)-c2cn3c(n2)sc2cc(OCCN4CCOCC4)ccc32)no1	quizartinib
+CCCCCCCCc1ccc(CCC(N)(CO)CO)cc1	fingolimod
+CN(c1ccc2c(C)n(C)nc2c1)c1ccnc(Nc2ccc(C)c(c2)S(N)(=O)=O)n1	pazopanib
+COc1cc(ccc1Nc1ncc(Cl)c(Oc2cccc(NC(=O)C=C)c2)n1)N1CCN(C)CC1	WZ4002
+CN(C)CC1CN(C1)C(=O)Nc1cc(ccc1N)-c1ccc(F)cc1	BRD-K24690302
+COc1ccc(cc1)S(=O)(=O)N(C(=O)C)c2ccccc2C=Cc3cc[n+]([O-])cc3	BRD-K70511574
+CCCS(=O)(=O)Nc1ccc(F)c(C(=O)c2c[nH]c3ncc(cc23)-c2ccc(Cl)cc2)c1F	PLX-4032
+Cc1n[nH]c2NC3=C([C@@H](c12)c1ccccc1)C(=O)CC(C)(C)C3	BRD-K48477130
+C[C@@H](Oc1cc(sc1C(N)=O)-n1cnc2ccc(CN3CCN(C)CC3)cc12)c1ccccc1C(F)(F)F	GSK461364
+CC[C@H](C)[C@H](NC(=O)[C@H](CCCNC(N)=N)NC(=O)[C@H](CCCNC(N)=N)NC(=O)CCNC(C)=O)C(=O)N[C@]1(C)CCC\C=C/CCC[C@@](C)(NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCSC)NC1=O)C(=O)N[C@@H](C)C(=O)N[C@@H](C)C(=O)N[C@@H](CC(N)=O)C(=O)N[C@@H](CCCNC(N)=N)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCC(O)=O)C(=O)N[C@@H](CCCNC(N)=N)C(O)=O	YL54
+CC[C@H](C)[C@H](NC(=O)[C@H](CCCNC(N)=N)NC(=O)[C@H](CCCNC(N)=N)NC(=O)CCNC(C)=O)C(=O)N[C@@H](CCC(N)=O)C(=O)N[C@@H](CCSC)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCC(O)=O)C(=O)N[C@@H](C)C(=O)N[C@@H](C)C(=O)N[C@@H](CC(N)=O)C(=O)N[C@@H](CCCNC(N)=N)C(=O)N[C@]1(C)CCC\C=C/CCC[C@@](C)(NC(=O)[C@H](CCCNC(N)=N)NC(=O)[C@H](CCCNC(N)=N)NC(=O)[C@H](CCC(O)=O)NC1=O)C(=O)N[C@@H](CCCNC(N)=N)C(N)=O	BRD-K20514654
+CCC(C)C(NC(=O)C(CCCNC(=N)N)NC(=O)C(CCCNC(=N)N)NC(=O)C(CCCNC(=N)N)NC(=O)C(CC(C)C)NC(=O)C(CCCNC(=N)N)NC(=O)C(CCC(=O)O)NC(=O)CCNC(=O)C)C(=O)NC1(C)CCCC=CCCCC(C)(NC(=O)C(CCCNC(=N)N)NC(=O)C(CS)NC(=O)C(CC(C)C)NC1=O)C(=O)NC(Cc2c[nH]cn2)C(=O)NC(Cc3c[nH]cn3)C(=O)NC(CO)C(=O)NC(C(C)O)C(=O)N	BRD-K55473186
+Cc1c(oc2ccc3ccccc3c12)[N+]([O-])=O	BRD-K28456706
+CC(C)(C)c1ccc(cc1)S(=O)(=O)NCc1ccc(cc1)C(=O)Nc1cccnc1	STF-31
+OC(=O)[C@@H]1CCCC[C@@H]1C(=O)N1CCc2ccccc2[C@H]1CN1C(=O)c2ccccc2C1=O	ML334 diastereomer
+Fc1ccc(CNc2ncnc3ccc(F)cc23)cc1	spautin-1
+FC(F)(F)c1ccc(Nc2nccc(n2)-c2cccc(Cl)c2)cc1	VAF-347
+CC(C)N(CCCNC(=O)Nc1ccc(cc1)C(C)(C)C)C[C@H]1O[C@H](C(O)[C@H]1O)n1cnc2c(N)ncnc12	BRD-A02303741
+COc1ccccc1[C@H]1c2c(NC3=C1C(=O)CC(C)(C)C3)n[nH]c2C(F)(F)F	ML320
+CN(C)[C@H]1[C@@H]2C[C@@H]3Cc4c(cc(NC(=O)CNC(C)(C)C)c(O)c4C(=O)C3C(=O)[C@]2(O)C(=O)C(C(N)=O)C1=O)N(C)C	tigecycline
+CC(C)N1C[C@@H](C)[C@H](CN(C)Cc2ccc(Oc3ccccc3)cc2)Oc2c(NC(=O)c3ccncc3)cccc2C1=O	BRD-K34099515
+Cc1cc(CS(=O)(=O)c2ccccc2)cc(OCc2ccc(CN3CCC[C@@H]3CO)cc2)c1	PF-543
+CS(=O)(=O)c1cccc(CNc2nc(Nc3ccc4NC(=O)CCc4c3)ncc2C(F)(F)F)c1	PF-573228
+COc1ccc(\C=C\C(=O)c2c(-c3ccccc3)c3ccccc3[nH]c2=O)cc1	ceranib-2
+CCOC(=O)NC(=O)C(=C\c1ccc(Cl)c(Cl)c1)\C#N	FSC231
+CN(C)c1ccc(cc1Br)C1Nc2ccc3ccccc3c2C2=C1C(=O)CC(C)(C)C2	968
+CC(C)(C)OC(=O)CN(Cc1ccc(s1)[N+]([O-])=O)Cc1ccc(Cl)cc1	GSK4112
+OC(=O)[C@@]1(CCCCCCOc2ccc(Cl)cc2)CO1	etomoxir
+Cc1c(cc(-c2ccccc2)n1CCCN1CCOCC1)C(=O)Nc1cccc(c1)C(F)(F)F	HC-067047
+CC1CC(C)CN(C1)c1cc(Nc2ccccc2C(O)=O)c2C(=O)c3ccccc3-c3onc1c23	IPR-456
+CCOC(=O)c1c(C(=CN)C#N)c2ccc(Cl)c(Cl)c2n1C	KH-CB19
+CCC(\C=C\[C@@H]1OC(=O)C=C[C@@H]1C)=C\[C@H](C)C\C=C\C(C)=C\[C@@H](C)C(=O)[C@@H](C)[C@H](O)[C@@H](C)C\C(C)=C\C(O)=O	leptomycin B
+COc1cc(OC2CCN(C)CC2)ccc1Nc1ncc2n(C)c(=O)n(C3CCCC3)c2n1	AZ-3146
+O=C(NCCN1CCC(CC1)n1c2ccccc2[nH]c1=O)c1ccc2ccccc2c1	VU0155056
+Cc1sc-2c(c1C)C(=N[C@@H](CC(=O)OC(C)(C)C)c1nnc(C)n-21)c1ccc(Cl)cc1.COc1cc2c(NC3CCN(CC3)C(C)C)nc(nc2cc1OCCCN1CCCC1)C1CCCCC1	JQ-1:UNC0638 (2:1 mol/mol)
+O=C1O[Pt]OC(=O)C11CCC1.COc1cc2c(NC3CCN(CC3)C(C)C)nc(nc2cc1OCCCN1CCCC1)C1CCCCC1	carboplatin:UNC0638 (2:1 mol/mol)
+O=C1O[Pt]OC(=O)C11CCC1.ONC(=O)CCCCCCC(=O)Nc1ccccc1	vorinostat:carboplatin (1:1 mol/mol)
+C(Cc1c[nH]c2ccccc12)Nc1ccc(Nc2ccncc2)cc1.CN(C)CCCNc1nc(CN2CCN(CC2)C(c2ccc(Cl)cc2)c2ccc(Cl)cc2)nc2ccccc12	serdemetan:SCH-529074 (1:1 mol/mol)
+Cn1cnc2c(F)c(Nc3ccc(Br)cc3Cl)c(cc12)C(=O)NOCCO.CCCS(=O)(=O)Nc1ccc(F)c(C(=O)c2c[nH]c3ncc(cc23)-c2ccc(Cl)cc2)c1F	selumetinib:PLX-4032 (8:1 mol/mol)
+CC(C)C[C@H](NC(=O)[C@H](Cc1ccccc1)NC(=O)c1cnccn1)B(O)O.CO[C@@H]1C[C@H](C[C@@H](C)[C@@H]2CC(=O)[C@H](C)\C=C(C)\[C@@H](O)[C@@H](OC)C(=O)[C@H](C)C[C@H](C)\C=C\C=C\C=C(C)\[C@H](C[C@@H]3CC[C@@H](C)[C@@](O)(O3)C(=O)C(=O)N3CCCC[C@H]3C(=O)O2)OC)CC[C@H]1O	sirolimus:bortezomib (250:1 mol/mol)
+CN(CCc1cc(Br)c(OCCCNc2ncnc3n(C)cnc23)c(Br)c1)C(=O)c1ccc(C)cc1	BRD-K97651142
+CCOC(=O)N[C@@H]1CC[C@@H]2[C@H](C[C@@H]3[C@@H]([C@@H](C)OC3=O)[C@H]2\C=C\c2ccc(cn2)-c2cccc(F)c2)C1	vorapaxar
+CC(C)(C)c1cc(cc(c1)C(C)(C)C)C(=O)\C=C\c1ccc(cc1)C(O)=O	Ch-55
+CC(C)C[C@@H]1NC(=O)[C@H](CCCNC(N)=N)NC(=O)[C@H](Cc2c[nH]c3ccccc23)NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CC(N)=O)NC(=O)[C@@](C)(CCCCCC\C=C/CCC[C@](C)(NC(=O)[C@H](CC(C)C)NC1=O)C(=O)N[C@@H](CCC(N)=O)C(=O)N[C@@H](CC(N)=O)C(N)=O)NC(=O)[C@H](Cc1ccccc1)NC(=O)[C@@H](NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CO)NC(=O)[C@H](CCC(N)=O)NC(C)=O)[C@@H](C)O	BRD-K79669418
+CC[C@H](C)[C@H](NC(C)=O)C(=O)N[C@@H](Cc1c[nH]c2ccccc12)C(=O)N[C@@H]([C@@H](C)CC)C(=O)N[C@@H](C)C(=O)N[C@@H](CCC(N)=O)C(=O)N[C@@H](CCC(O)=O)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCNC(N)=N)C(=O)N[C@@]1(C)CCC\C=C/CCC[C@](C)(NC(=O)[C@H](CC(O)=O)NC(=O)CNC(=O)[C@@H](NC1=O)[C@@H](C)CC)C(=O)N[C@@H](Cc1ccccc1)C(=O)N[C@@H](CC(N)=O)C(=O)N[C@@H](C)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](C)C(=O)N[C@@H](CCCNC(N)=N)C(=O)N[C@@H](CCCNC(N)=N)C(N)=O	BRD-K99584050
+Fc1cccc(c1)N(C(C(=O)NC1CCCCC1)c1ccccc1Cl)C(=O)Cc1cccs1	BRD-A71883111
+CC[C@H](NC(=O)[C@H](C)NC)C(=O)N1C[C@@H](O)C[C@H]1Cc1c([nH]c2cc(F)ccc12)-c1cc2c(C[C@@H]3C[C@H](O)CN3C(=O)[C@H](CC)NC(=O)[C@H](C)NC)cc(F)cc2[nH]1.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	navitoclax:birinapant (1:1 mol/mol)
+CC(C)C[C@H](NC(=O)[C@H](Cc1ccccc1)NC(=O)c1cnccn1)B(O)O.CC(C)(C)OC(=O)Nc1ccc(cc1)-c1cc(no1)C(=O)NCCCCCCC(=O)NO	ISOX:bortezomib (250:1 mol/mol)
+Cn1cnc2c(F)c(Nc3ccc(Br)cc3Cl)c(cc12)C(=O)NOCCO.CS(=O)(=O)N1CCN(Cc2cc3nc(nc(N4CCOCC4)c3s2)-c2cccc3[nH]ncc23)CC1	selumetinib:GDC-0941 (4:1 mol/mol)
+CC(=C/CO)\C=C\C=C(C)\C=C\C1=C(C)CCCC1(C)C.Cn1cnc2c(F)c(Nc3ccc(Br)cc3Cl)c(cc12)C(=O)NOCCO	selumetinib:tretinoin (2:1 mol/mol)
+ONC(=O)CCCCCCC(=O)Nc1ccccc1.Cn1cnc2c(F)c(Nc3ccc(Br)cc3Cl)c(cc12)C(=O)NOCCO	selumetinib:vorinostat (8:1 mol/mol)
+Cn1cnc2c(F)c(Nc3ccc(Br)cc3Cl)c(cc12)C(=O)NOCCO.Cc1sc-2c(c1C)C(=N[C@@H](CC(=O)OC(C)(C)C)c1nnc(C)n-21)c1ccc(Cl)cc1	selumetinib:JQ-1 (4:1 mol/mol)
+Cn1cnc2c(F)c(Nc3ccc(Br)cc3Cl)c(cc12)C(=O)NOCCO.CC(C)N(CCCNC(=O)Nc1ccc(cc1)C(C)(C)C)C[C@H]1O[C@H]([C@H](O)[C@@H]1O)n1ccc2c(N)ncnc12	selumetinib:BRD-A02303741 (4:1 mol/mol)
+CC(=C/CO)\C=C\C=C(C)\C=C\C1=C(C)CCCC1(C)C.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	tretinoin:navitoclax (4:1 mol/mol)
+Nc1ncn([C@H]2C[C@H](O)[C@@H](CO)O2)c(=O)n1.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	decitabine:navitoclax (2:1 mol/mol)
+O=C1O[Pt]OC(=O)C11CCC1.CC(\C=C\C=C(C)\C=C\C1=C(C)CCCC1(C)C)=C/CO	tretinoin:carboplatin (2:1 mol/mol)
+Fc1ccc(cc1)-c1n[nH]cc1C=C1SC(=N)N(C1=O)c1nccs1	necrostatin-7
+CCOC(=O)c1ccc(cc1)N1NC(=O)C(=Cc2ccc(o2)[N+]([O-])=O)C1=O	PYR-41
+COc1cc2c3n([C@H](C)c4ccccn4)c(=O)[nH]c3cnc2cc1-c1c(C)noc1C	I-BET151
+Nc1nc(OCc2cc(Br)cs2)c2[nH]cnc2n1	lomeguatrib
+C[C@@]1(CO)CN(C[C@]1(C)CO)c1cc(C(=O)Nc2ccc3CCc4c(nn(c4-c3c2)-c2ccc(F)cc2)C(N)=O)c(Cl)cn1	PF-184
+Nc1ccn([C@@H]2O[C@H](CO)[C@@H](O)C2(F)F)c(=O)n1.CO[C@H]1C[C@H](C)CC2=C(NCC=C)C(=O)C=C(NC(=O)\C(C)=C\C=C/[C@H](OC)[C@@H](OC(N)=O)\C(C)=C\[C@H](C)[C@H]1O)C2=O	tanespimycin:gemcitabine (1:1 mol/mol)
+CO[C@H]1C[C@H](C)CC2=C(NCC=C)C(=O)C=C(NC(=O)\C(C)=C\C=C/[C@H](OC)[C@@H](OC(N)=O)\C(C)=C\[C@H](C)[C@H]1O)C2=O.CC(=O)O[C@@]12CO[C@@H]1C[C@H](O)[C@]1(C)C2[C@H](OC(=O)c2ccccc2)[C@]2(O)C[C@H](OC(=O)[C@H](O)[C@@H](NC(=O)OC(C)(C)C)c3ccccc3)C(C)=C([C@@H](O)C1=O)C2(C)C	docetaxel:tanespimycin (2:1 mol/mol)
+Cn1cnc2c(F)c(Nc3ccc(Br)cc3Cl)c(cc12)C(=O)NOCCO.NC1(CCC1)c1ccc(cc1)-c1nc2ccn3c(n[nH]c3=O)c2cc1-c1ccccc1	selumetinib:MK-2206 (8:1 mol/mol)
+CCCS(=O)(=O)Nc1ccc(F)c(C(=O)c2c[nH]c3ncc(cc23)-c2ccc(Cl)cc2)c1F.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	navitoclax:PLX-4032 (1:1 mol/mol)
+COc1cc(\C=C\C(=O)N2CCC=CC2=O)cc(OC)c1OC.Cn1cnc2c(F)c(Nc3ccc(Br)cc3Cl)c(cc12)C(=O)NOCCO	selumetinib:piperlongumine (8:1 mol/mol)
+CC(C)C[C@H](NC(=O)[C@H](Cc1ccccc1)NC(=O)c1cnccn1)B(O)O.CO[C@H]1C[C@H](C)CC2=C(NCC=C)C(=O)C=C(NC(=O)\C(C)=C\C=C/[C@H](OC)[C@@H](OC(N)=O)\C(C)=C\[C@H](C)[C@H]1O)C2=O	tanespimycin:bortezomib (250:1 mol/mol)
+Oc1cccc(C(=O)Nc2cccc(NC(=O)c3cccc(O)c3O)c2)c1O.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	navitoclax:MST-312 (1:1 mol/mol)
+O=C1O[Pt]OC(=O)C11CCC1.COc1cc(cc(OC)c1O)[C@H]1[C@@H]2[C@H](COC2=O)[C@H](O[C@@H]2O[C@@H]3CO[C@@H](C)O[C@H]3[C@H](O)[C@H]2O)c2cc3OCOc3cc12	carboplatin:etoposide (40:17 mol/mol)
+COc1cc(\C=C\C(=O)N2CCC=CC2=O)cc(OC)c1OC.Oc1cccc(C(=O)Nc2cccc(NC(=O)c3cccc(O)c3O)c2)c1O	piperlongumine:MST-312 (1:1 mol/mol)
+Nc1ccn([C@@H]2O[C@H](CO)[C@@H](O)C2(F)F)c(=O)n1.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	navitoclax:gemcitabine (1:1 mol/mol)
+CC(C)c1ccccc1OC(=O)NCCc1ccc2ccccc2c1	JW-480
+CC1(C)CC=C(c2cnc3ccccc3c2)c2cc(ccc12)C(=O)Nc1ccc(cc1)C(O)=O	BMS-195614
+CCOc1ccccc1N\N=C1C(=O)N(N=C\1C)c1nc(cs1)-c1ccccc1	BRD-K07442505
+Cc1cs\c(=N/C2CCCCC2)n1\N=C\c1ccc(O)c(O)c1O	BRD-K35604418
+CC(C)[C@H](N(CCCN)C(=O)c1ccc(C)cc1)c1oc2cc(Cl)ccc2c(=O)c1Cc1ccccc1	SB-743921
+CCNC(=O)C[C@@H]1N=C(c2ccc(Cl)cc2)c2cc(OC)ccc2-n2c(C)nnc12	GSK525762A
+CN1C(=O)N(Cc2cnc(Nc3cc(C)nn3C)nc12)c1cc(NC(=O)c2cccc(c2)C(F)(F)F)ccc1C.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	navitoclax:pluripotin (1:1 mol/mol)
+O=C1O[Pt]OC(=O)C11CCC1.Cc1sc-2c(c1C)C(=N[C@@H](CC(=O)OC(C)(C)C)c1nnc(C)n-21)c1ccc(Cl)cc1	JQ-1:carboplatin (1:1 mol/mol)
+Cn1cnc2c(F)c(Nc3ccc(Br)cc3Cl)c(cc12)C(=O)NOCCO.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	selumetinib:navitoclax (8:1 mol/mol)
+Nc1ncn([C@H]2C[C@H](O)[C@@H](CO)O2)c(=O)n1.Cn1cnc2c(F)c(Nc3ccc(Br)cc3Cl)c(cc12)C(=O)NOCCO	selumetinib:decitabine (4:1 mol/mol)
+O=C1O[Pt]OC(=O)C11CCC1.Nc1ncn([C@H]2C[C@H](O)[C@@H](CO)O2)c(=O)n1	decitabine:carboplatin (1:1 mol/mol)
+CC(C)C[C@H](NC(=O)[C@H](Cc1ccccc1)NC(=O)c1cnccn1)B(O)O.CC1(C)Cc2c(c(nn2-c2ccc(C(N)=O)c(N[C@H]3CC[C@H](O)CC3)c2)C(F)(F)F)C(=O)C1	SNX-2112:bortezomib (250:1 mol/mol)
+Cc1sc-2c(c1C)C(=N[C@@H](CC(=O)OC(C)(C)C)c1nnc(C)n-21)c1ccc(Cl)cc1.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	JQ-1:navitoclax (2:1 mol/mol)
+OC(=O)CC[C@H]1CC[C@@](CC1)(c1cc(F)ccc1F)S(=O)(=O)c1ccc(Cl)cc1.Cc1sc-2c(c1C)C(=N[C@@H](CC(=O)OC(C)(C)C)c1nnc(C)n-21)c1ccc(Cl)cc1	JQ-1:MK-0752 (1:1 mol/mol)
+CC(C)N(CCCNC(=O)Nc1ccc(cc1)C(C)(C)C)C[C@H]1O[C@H]([C@H](O)[C@@H]1O)n1ccc2c(N)ncnc12.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	BRD-A02303741:navitoclax (2:1 mol/mol)
+CC(C(=O)Nc1cccc(c1)\N=C\c1c(O)ccc2ccccc12)c1ccccc1.CCCS(=O)(=O)Nc1ccc(F)c(C(=O)c2c[nH]c3ncc(cc23)-c2ccc(Cl)cc2)c1F	salermide:PLX-4032 (12:1 mol/mol)
+COc1cc2c(NC3CCN(CC3)C(C)C)nc(nc2cc1OCCCN1CCCC1)C1CCCCC1.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	UNC0638:navitoclax (1:1 mol/mol)
+O=C1O[Pt]OC(=O)C11CCC1.CC(C)N(CCCNC(=O)Nc1ccc(cc1)C(C)(C)C)C[C@H]1O[C@H]([C@H](O)[C@@H]1O)n1ccc2c(N)ncnc12	BRD-A02303741:carboplatin (1:1 mol/mol)
+COc1cccc2C(=O)c3c(O)c4C[C@](O)(C[C@H](O[C@H]5C[C@H](N)[C@H](O)[C@H](C)O5)c4c(O)c3C(=O)c12)C(=O)CO.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	doxorubicin:navitoclax (2:1 mol/mol)
+Cn1cnc2c(F)c(Nc3ccc(Br)cc3Cl)c(cc12)C(=O)NOCCO.COc1cc2c(NC3CCN(CC3)C(C)C)nc(nc2cc1OCCCN1CCCC1)C1CCCCC1	selumetinib:UNC0638 (4:1 mol/mol)
+COc1cc(Nc2ncc3CN=C(c4cc(Cl)ccc4-c3n2)c2c(F)cccc2OC)ccc1C(O)=O.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	alisertib:navitoclax (2:1 mol/mol)
+CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3ccc(Cl)c(c3)C(F)(F)F)cc2)ccn1.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	navitoclax:sorafenib (1:1 mol/mol)
+COc1cc(\C=C\C(=O)N2CCC=CC2=O)cc(OC)c1OC.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	navitoclax:piperlongumine (1:1 mol/mol)
+O=C1c2ccccc2-c2nc3nonc3nc12	SMER-3
+Nc1ncnc2n(cc(-c3cccc(OCc4ccccc4)c3)c12)[C@H]1C[C@H](CN2CCCC2)C1	NVP-ADW742
+Nc1nc(Cl)nc2n(cnc12)[C@@H]1O[C@H](CO)[C@@H](O)[C@@H]1F	clofarabine
+ONC(=O)CCCCCCC(=O)Nc1ccccc1.CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1	vorinostat:navitoclax (4:1 mol/mol)
+COc1cc(Nc2nc3ccccc3nc2NS(=O)(=O)c2ccc(NC(=O)c3ccc(C)c(OC)c3)cc2)cc(OC)c1	XL765
+C[C@H](Nc1ncc(Cl)c(Nc2cc(C)[nH]n2)n1)c1ncc(F)cn1	AZD1480
+COc1ccc(CN2c3nnnn3C3C(C2=O)C2(CCCC2)Cc2ccccc32)cc1	ML258
+CC(=O)Nc1nc(C)c(s1)S(=O)(=O)Nc1ccc(cc1)C(O)(C(F)(F)F)C(F)(F)F	SR1001
+COC(=O)[C@@]12CCC(C)(C)C[C@@H]1[C@@H]1C(=O)C=C3[C@]4(C)C=C(C#N)C(=O)C(C)(C)[C@H]4CC[C@]3(C)[C@@]1(C)CC2	bardoxolone methyl
+CCC(O)(CC)\C=C\CC(C)C1=CC[C@@H]2[C@]1(C)CCC\C2=C/C=C1/C[C@@H](O)C[C@H](F)C1=C	elocalcitol
+CC1(C)CCC(C)(C)c2cc(ccc12)[C@@H](O)C(=O)Nc1ccc(cc1F)C(O)=O	BMS-270394
+CC(C)N1C(\C=C\C(O)CC(O)CC(O)=O)C(c2ccccc12)c1ccc(F)cc1	fluvastatin
+COc1cc(CCc2cc(NC(=O)c3ccc(cc3)N3C[C@H](C)N[C@H](C)C3)n[nH]2)cc(OC)c1	AZD4547
+CC(C)C(=O)[C@@]12C(=O)C(CC=C(C)C)C(=O)C(CC=C(C)C)(C[C@H](CC=C(C)C)[C@@]1(C)CCC=C(C)C)C2=O	hyperforin
+O=C(Nc1nc2ccc(NC(=O)C34C[C@H]5C[C@H](C[C@H](C5)C3)C4)cc2s1)c1ccccc1	NVP-231
+OC(=O)CC[C@H]1CC[C@@](CC1)(c1cc(F)ccc1F)S(=O)(=O)c1ccc(Cl)cc1	MK-0752
+CC(C)[C@H](O)C(=O)N[C@@H](C)C(=O)N[C@H]1c2ccccc2CCN(C)C1=O	semagacestat
+Cc1ccccc1C(N(C(=O)Cc1ccncc1)c1cccc(F)c1)C(=O)NC1CCCCC1	BRD-A05715709
+COc1cc(Nc2cc(nc3cc(OCCCN4CCN(C)CC4)c(OC)cc23)C#N)c(Cl)cc1Cl	bosutinib
+CO[C@@H]1C[C@H](C[C@@H](C)[C@@H]2CC(=O)[C@H](C)\C=C(C)\[C@@H](O)[C@@H](OC)C(=O)[C@H](C)C[C@H](C)\C=C\C=C\C=C(C)\[C@H](C[C@@H]3CC[C@@H](C)[C@@](O)(O3)C(=O)C(=O)N3CCCC[C@H]3C(=O)O2)OC)CC[C@H]1OC(=O)C(C)(CO)CO	temsirolimus
+C[C@]12CC[C@H]3[C@@H](CC=C4C[C@@H](O)CC[C@]34C)[C@@H]1CC=C2c1cccnc1	abiraterone
+CC(=O)O[C@@]12CO[C@@H]1C[C@H](O)[C@]1(C)C2[C@H](OC(=O)c2ccccc2)[C@]2(O)C[C@H](OC(=O)[C@H](O)[C@@H](NC(=O)OC(C)(C)C)c3ccccc3)C(C)=C([C@@H](O)C1=O)C2(C)C	docetaxel
+COc1nc(N)nc2n(cnc12)[C@@H]1O[C@H](CO)[C@@H](O)[C@@H]1O	nelarabine
+COc1cc(OC)c(\C=C\S(=O)(=O)Cc2ccc(OC)c(NCC(O)=O)c2)c(OC)c1	rigosertib
+Clc1ccc(cc1)C1(CCNCC1)c1ccc(cc1)-c1cn[nH]c1	AT7867
+OCC(O)CONC(=O)c1cc(Br)c(F)c(F)c1Nc1ccc(I)cc1F	PD318088
+C[C@H]1CN(CC(=O)Nc2ccc3Sc4c(Cc3c2)cccc4-c2cc(=O)cc(o2)N2CCOCC2)C[C@@H](C)O1	KU-60019
+Cc1ccc(cc1)-n1nc(cc1NC(=O)Nc1ccc(OCCN2CCOCC2)c2ccccc12)C(C)(C)C	BIRB-796
+O=C(N1CCNCC1)c1ccc(cc1)\C=C\c1n[nH]c2ccccc12	KW-2449
+Cn1c(Nc2ccc(cc2)C(F)(F)F)nc2cc(Oc3ccnc(c3)-c3ncc([nH]3)C(F)(F)F)ccc12	RAF265
+OC(=O)c1ccc2c(c1)nc(Nc1cccc(Cl)c1)c1ccncc21	silmitasertib
+CCCC[C@H](NC(=O)[C@H](CCCNC(N)=N)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@@H](NC(=O)[C@]1(C)CCC\C=C/CCC[C@](C)(NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CO)NC(=O)[C@H](CCCNC(N)=N)NC(=O)[C@H](CCC(O)=O)NC(=O)[C@H](CCCNC(N)=N)NC(=O)[C@H](Cc2cnc[nH]2)NC(=O)[C@H](CCC(O)=O)NC(=O)[C@H](CC(C)C)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CCC(O)=O)NC(=O)[C@H](CCC(N)=O)NC(=O)[C@H](CO)NC(=O)[C@H](CC(C)C)NC(C)=O)C(=O)N[C@@H]([C@@H](C)O)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCNC(N)=N)C(=O)N1)[C@@H](C)CC)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](Cc1ccccc1)C(N)=O	BRD-K03911514
+CC[C@H](C)[C@H](NC(C)=O)C(=O)N[C@@H](Cc1c[nH]c2ccccc12)C(=O)N[C@@H]([C@@H](C)CC)C(=O)N[C@@H](C)C(=O)N[C@@H](CCC(N)=O)C(=O)N[C@@H](CCC(O)=O)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CC(O)=O)C(=O)N[C@@]1(C)CCC\C=C/CCC[C@](C)(NC(=O)[C@H](CC(O)=O)NC(=O)CNC(=O)[C@@H](NC1=O)[C@@H](C)CC)C(=O)N[C@@H](Cc1ccccc1)C(=O)N[C@@H](CC(N)=O)C(=O)N[C@@H](C)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](Cc1ccc(O)cc1)C(=O)N[C@@H](C)C(=O)N[C@@H](CCCNC(N)=N)C(=O)N[C@@H](CCCNC(N)=N)C(N)=O	BRD-K16130065
+O=C(NCC#N)c1ccc(cc1)-c1ccnc(Nc2ccc(cc2)N2CCOCC2)n1	momelotinib
+CC[C@H](Nc1ncnc2[nH]cnc12)c1nc2cccc(F)c2c(=O)n1-c1ccccc1	CAL-101
+Cc1cccc(n1)-c1nn2CCCc2c1-c1ccnc2ccc(cc12)C(N)=O	LY-2157299
+CCC[C@H](NC(=O)C(=C\c1cccc(Br)n1)\C#N)c1ccccc1	WP1130
+COc1cccc2cc([nH]c12)-c1nc([C@H]2CC[C@@H](CC2)C(O)=O)n2ncnc(N)c12	OSI-027
+Fc1cc(cc(F)c1CN1CCOCC1)-c1cccc2ncc(nc12)-c1cnn(c1)C1CCNCC1	NVP-BSK805
+COCCOc1cc2ncnc(Nc3cccc(c3)C#C)c2cc1OCCOC.CCCS(=O)(=O)Nc1ccc(F)c(C(=O)c2c[nH]c3ncc(cc23)-c2ccc(Cl)cc2)c1F	erlotinib:PLX-4032 (2:1 mol/mol)
+CC(=O)Nc1nc(C)c(s1)-c1ccc(Cl)c(c1)S(=O)(=O)NCCO	PIK-93
+NC(=O)Nc1cc(sc1C(=O)N[C@H]1CCCNC1)-c1cccc(F)c1	AZD7762
+CC[C@H](NC(=O)[C@H](C)NC)C(=O)N1C[C@@H](O)C[C@H]1Cc1c([nH]c2cc(F)ccc12)-c1cc2c(C[C@@H]3C[C@H](O)CN3C(=O)[C@H](CC)NC(=O)[C@H](C)NC)cc(F)cc2[nH]1	birinapant
+O=C(Cc1ccc(cn1)-c1ccc(OCCN2CCOCC2)cc1)NCc1ccccc1	KX2-391
+OC(=O)\C=C\c1ccc(c(Cl)c1)-c1ccc(O)c(c1)C12C[C@H]3C[C@H](C[C@H](C3)C1)C2	3-Cl-AHPC
+CC(C)C[C@H](NC(=O)[C@H](C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCCNC(N)=N)NC(C)=O)C(=O)N[C@@H](CCC(O)=O)C(=O)N[C@@H]([C@@H](C)O)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCNC(N)=N)C(=O)N[C@@H](CCCNC(N)=N)C(=O)N[C@@H](C(C)C)C(=O)NCC(=O)N[C@@H](CC(O)=O)C(=O)N[C@@H](CCC(O)=O)C(=O)N[C@@H](C(C)C)C(=O)N[C@@]1(C)CCC\C=C/CCC[C@](C)(NC(=O)[C@H](Cc2cnc[nH]2)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CCCNC(N)=N)NC1=O)C(=O)N[C@@H]([C@@H](C)O)C(=O)N[C@@H](C)C(=O)N[C@@H](Cc1ccccc1)C(N)=O	BRD-K58730230
+CC(C)C[C@H](NC(=O)[C@H](C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCCNC(N)=N)NC(C)=O)C(=O)N[C@@H](CCC(O)=O)C(=O)N[C@@H]([C@@H](C)O)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCNC(N)=N)C(=O)N[C@@H](CCCNC(N)=N)C(=O)N[C@@H](C(C)C)C(=O)NCC(=O)N[C@@H](CC(O)=O)C(=O)NCC(=O)N[C@@H](C(C)C)C(=O)N[C@@]1(C)CCC\C=C/CCC[C@](C)(NC(=O)[C@H](Cc2cnc[nH]2)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CCCNC(N)=N)NC1=O)C(=O)N[C@@H]([C@@H](C)O)C(=O)N[C@@H](C)C(=O)N[C@@H](Cc1ccccc1)C(N)=O	BRD-K27188169
+CC(C)CNc1ccnc(NCc2csc(n2)-c2ccccc2)n1	KHS101
+CC(C)OC(=O)C1=CN(CC(C)(C)c2c1[nH]c1ccccc21)C(=O)c1ccc(F)c(F)c1	WAY-362450
+ONC(=O)CCCCCCC(=O)Nc1ccccc1.Cc1sc-2c(c1C)C(=N[C@@H](CC(=O)OC(C)(C)C)c1nnc(C)n-21)c1ccc(Cl)cc1	JQ-1:vorinostat (2:1 mol/mol)
+CC(C)C[C@H](NC(=O)[C@H](C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCCNC(N)=N)NC(C)=O)C(=O)N[C@@H](CCC(O)=O)C(=O)N[C@@H]([C@@H](C)O)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCNC(N)=N)C(=O)N[C@@H](CCCNC(N)=N)C(=O)N[C@@H](C(C)C)C(=O)N[C@@H](CCC(O)=O)C(=O)N[C@@H](CC(O)=O)C(=O)NCC(=O)N[C@@H](C(C)C)C(=O)N[C@@]1(C)CCC\C=C/CCC[C@](C)(NC(=O)[C@H](Cc2cnc[nH]2)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CCCNC(N)=N)NC1=O)C(=O)N[C@@H]([C@@H](C)O)C(=O)N[C@@H](C)C(=O)N[C@@H](Cc1ccccc1)C(N)=O	BRD-K13185470
+COc1cc2nccc(Oc3ccc(NC(=O)C4(CC4)C(=O)Nc4ccc(F)cc4)cc3)c2cc1OC	cabozantinib
+C[C@@H](Oc1cc(cnc1N)-c1cnn(c1)C1CCNCC1)c1c(Cl)ccc(F)c1Cl.CCCS(=O)(=O)Nc1ccc(F)c(C(=O)c2c[nH]c3ncc(cc23)-c2ccc(Cl)cc2)c1F	crizotinib:PLX-4032 (2:1 mol/mol)
+C[C@H](O)[C@@H]1[C@H](CO)ON(Cc2cccc(CN(CCN(C)C)[C@H](C3CCCCC3)c3ccccc3)c2)[C@@H]1C(=O)N[C@H]1C[C@H]2C[C@@H]([C@@H]1C)C2(C)C.C[C@H](O)[C@@H]1[C@H](CO)ON(Cc2cccc(CN(CCN(C)C)[C@@H](C3CCCCC3)c3ccccc3)c2)[C@@H]1C(=O)N[C@H]1C[C@H]2C[C@@H]([C@@H]1C)C2(C)C	BRD-M00053801
+COc1cc(cc(c1)C(F)(F)F)-c1ncn(\C=C/C(=O)OC(C)C)n1	KPT185
+Brc1ccc(cc1)\C=C1/SC(NS(=O)(=O)c2cccc3ccccc23)=NC1=O	pitstop2
+Nc1nc(Nc2ccc3CC[C@@H](CCc3c2)N2CCCC2)nn1-c1cc2CCCc3ccccc3-c2nn1	R428
+Nc1ncnc2n(nc(-c3ccc(Oc4ccccc4)cc3)c12)[C@@H]1CCCN(C1)C(=O)C=C	ibrutinib
+CN1CCN(CC1)c1nc(C2=C(C(=O)NC2=O)c2c[nH]c3ccccc23)c2ccccc2n1	sotrastaurin
+C[C@H](\N=C(\NC#N)Nc1cccc2ncccc12)c1ccccc1	A-804598
+CC1(C)CCC(=C(CN2CCN(CC2)c2ccc(cc2)C(=O)NS(=O)(=O)c2ccc(N[C@H](CCN3CCOCC3)CSc3ccccc3)c(c2)S(=O)(=O)C(F)(F)F)C1)c1ccc(Cl)cc1.CC(C)C[C@H](NC(=O)[C@H](C)NC(=O)[C@H](CCCCN)NC(=O)[C@H](CCCNC(N)=N)NC(C)=O)C(=O)N[C@@H](CCC(O)=O)C(=O)N[C@@H]([C@@H](C)O)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCCNC(N)=N)C(=O)N[C@@H](CCCNC(N)=N)C(=O)N[C@@H](C(C)C)C(=O)NCC(=O)N[C@@H](CC(O)=O)C(=O)NCC(=O)N[C@@H](C(C)C)C(=O)N[C@@]1(C)CCC\C=C/CCC[C@](C)(NC(=O)[C@H](Cc2cnc[nH]2)NC(=O)[C@H](CC(N)=O)NC(=O)[C@H](CCCNC(N)=N)NC1=O)C(=O)N[C@@H]([C@@H](C)O)C(=O)N[C@@H](C)C(=O)N[C@@H](Cc1ccccc1)C(N)=O	BRD-K27188169:navitoclax (2:1 mol/mol)
+NC(=O)C1C(=O)C[C@@H]2C[C@@H]3Cc4cccc(O)c4C(=O)C3C(=O)[C@]2(O)C1=O	COL-3
+CC1(C)CCC(CN2CCN(CC2)c2ccc(C(=O)NS(=O)(=O)c3ccc(NCC4CCOCC4)c(c3)[N+]([O-])=O)c(Oc3cnc4[nH]ccc4c3)c2)=C(C1)c1ccc(Cl)cc1	ABT-199
+CC(C)(C#N)c1ccc(cc1)N1C(=O)OCc2cnc3ccc(cc3c12)-c1cnc2ccccc2c1	ETP-46464
+Oc1ccccc1C(=O)c1[nH]c(Cl)c(Cl)c1-n1c(cc(Cl)c1Cl)C(=O)c1ccccc1O	marinopyrrole A
+COC(=O)\C=C\C(=O)N(O)CCCCNCc1ccc(COC(=O)Nc2cccc3ccccc23)cc1	methylstat
+Cc1nc(NC(=O)N2CCC[C@H]2C(N)=O)sc1-c1ccnc(c1)C(C)(C)C(F)(F)F	BYL-719
+Cc1nc2c(cc(cc2n1Cc1cccc(c1C)C(F)(F)F)N1CCOCC1)C(O)=O	GSK2636771
+CCOC(=O)C1Cc2ccccc2CN1C(=O)c1ccc(SC)s1	SR8278
+COc1ccc(cc1)-n1c(SCc2nc(no2)-c2ccc(C)cc2)nnc1-c1ccncc1	JW-74
+COc1nccnc1NS(=O)(=O)c1ccc(NC(=O)\C=C\c2ccc(s2)[N+]([O-])=O)cc1	necrosulfonamide
+Clc1ccc-2c(c1)C(=O)c1nc(C#N)c(nc-21)C#N	HBX-41108
+CCCCCCCCCC[C@H]1[C@H](CCc2ccc(OC)c(OC)c2)OC1=O	palmostatin B
+COc1ccc(cc1)C1(CNC(=O)c2ccc(NC(=O)c3ccco3)cc2)CCOCC1	JW-55
+CC1=NN(C(=O)C\1=N\Nc1ccccc1C(O)=O)c1nc(cs1)-c1ccccc1	BRD-K03536150
+CCN(CC)c1ccc(cc1)C1=NNC(=O)C[C@H]1C	BRD-K99006945
+O=C1NC(=O)[C@H]([C@@H]1c1c[nH]c2ccccc12)c1cn2CCCc3cccc1c23	tivantinib
+CC(=O)Nc1cccc(c1)-n1c2c(C)c(=O)n(C)c(Nc3ccc(I)cc3F)c2c(=O)n(C2CC2)c1=O	trametinib
+CC(C)(C(=O)NCC(F)(F)C(F)(F)F)C(=O)N[C@H]1c2ccccc2-c2ccccc2NC1=O	RO4929097
+CCc1cnn2c(NCc3ccc[n+]([O-])c3)cc(nc12)N1CCCC[C@H]1CCO	dinaciclib
+C[C@@H](NC(=O)c1ncnc(N)c1Cl)c1ncc(s1)C(=O)Nc1cc(c(Cl)cn1)C(F)(F)F	MLN2480
+CC(C)n1ncc2c(cc(Br)cc12)C(=O)NCc1c(C)cc(C)[nH]c1=O	BRD-K51831558
+CCn1c2nc(\C=C\c3ccc(OC)c(OC)c3)n(C)c2c(=O)n(CC)c1=O	istradefylline
+CCCc1cc2c(ncnc2s1)N1CCN(CC1)C1=NCC(C)(C)S1	MI-2
+CC(C)n1ncc2c(cc(cc12)-c1ccc(nc1)N1CCNCC1)C(=O)NCc1c(C)cc(C)[nH]c1=O	BRD-K42260513
+CN1CC[C@H]([C@H](O)C1)c1c(O)cc(O)c2c1oc(cc2=O)-c1ccccc1Cl	alvocidib
+COC(=O)c1cc(CN2CCN(CC2)C(N)=N)cc(c1)C(=O)N1CCN(CC1)C(=O)c1ccc(cc1)C(N)=N	CBB-1007
+CCOC(=O)CCNc1cc(nc(n1)-c1ccccn1)N1CCc2ccccc2CC1	GSK-J4
+Cc1ccc(cc1)C(NC(=O)c1ccccc1)c1ccc2cccnc2c1O	BRD-A86708339
+CN(C)C[C@@H](NC(=O)N1Cc2c(Nc3nc(C)nc4ccsc34)n[nH]c2C1(C)C)c1ccccc1	PF-3758309
+CC(C)(C)c1nc(c(s1)-c1ccnc(N)n1)-c1cccc(NS(=O)(=O)c2c(F)cccc2F)c1F	dabrafenib
+CC1(C)CCN(CC1)c1ccc(cc1)C(=O)NS(=O)(=O)c1ccc(NCCSc2ccccc2)c(c1)[N+]([O-])=O	SZ4TA2
+CC(C)c1cc(C(=O)N2Cc3ccc(CN4CCN(C)CC4)cc3C2)c(O)cc1O	AT13387
+COc1ccc(cc1)C1C(C(=O)Nc2ccccc2)=C(C)N=c2s\c(=C/c3cn(Cc4ccccc4)c4ccccc34)c(=O)n12	BCL-LZH-4
+OC[C@@H](O)COc1ccc2CCc3cc(Nc4ccc(F)cc4F)ccc3C(=O)c2c1	skepinone-L
+COc1ccc(cc1)C#CC1=CCCN(C(=O)\C=C\c2cc(OC)c(OC)c(OC)c2)C1=O	BRD-K34222889
+Nc1ncnc2n(nc(COc3cccc(Cl)c3)c12)C1CCOCC1	PF-4800567 hydrochloride
+CC1O[C@@H](OCC2O[C@@H](O[C@H]3CC[C@@]4(C)C(CC[C@]5(C)C4CC=C4C6CC(C)(C)[C@H](C[C@@]6([C@H](O)C[C@@]54C)C(=O)O[C@@H]4OC(CO)[C@@H](O)[C@@H](O)[C@@H]4O[C@@H]4OC(C)[C@H](O[C@@H]5O[C@@H](CO)[C@H](O)[C@@H]5O)[C@@H](O[C@@H]5OC(CO)[C@@H](O)[C@@H](O)[C@@H]5O)[C@@H]4O)OC(=O)C(\CO)=C\CC[C@](C)(O[C@@H]4OC(C)[C@@H](OC(=O)C(\CO)=C\CCC(C)(O)C=C)[C@@H](O)[C@@H]4O)C=C)C3(C)C)[C@@H](NC(C)=O)[C@H](O)[C@@H]2O)[C@@H](O[C@@H]2OC[C@@H](O)[C@@H](O)[C@@H]2O)[C@H](O)[C@H]1O	avicin D
+CC(C)(C)c1ccc2cc(C#N)c(cc2c1)C#N.CN1CCN(CC1)c1ccc(Nc2ncc3c(n2)n(-c2cccc(n2)C(C)(C)O)n(CC=C)c3=O)cc1	BRD9876:MK-1775 (4:1 mol/mol)
+Cc1c(sc(=O)n1C)-c1ccnc(Nc2ccc(cc2)N2CCNCC2)n1	BRD-K30748066
+CC1(O)CC(C1)c2nc(c3ccc4ccc(nc4c3)c5ccccc5)c6c(N)nccn26	linsitinib
+CNC(C)C(=O)NC1CN(CCC2CCC(N2C1=O)C(=O)NC(c3ccccc3)c4ccccc4)C(=O)CC(C)C	AT-406
+CCc1cnn2c(NCc3ccc[n+]([O-])c3)cc(N3CCCC[C@H]3CCO)nc12	Dinaciclib
+CC(=O)O[C@H]1C(=O)[C@]2(C)[C@@H](O)C[C@H]3OC[C@@]3(OC(C)=O)[C@H]2[C@H](OC(=O)c2ccccc2)[C@]2(O)C[C@H](OC(=O)[C@H](O)[C@@H](NC(=O)c3ccccc3)c3ccccc3)C(C)=C1C2(C)C	Paclitaxel
+C#Cc1cccc(Nc2ncnc3cc(OC)c(OCCCCCCC(=O)NO)cc23)c1	CUDC-101
+CC(C)N(CCCNC(=O)Nc1ccc(C(C)(C)C)cc1)CC1OC(n2cc(Br)c3c(N)ncnc32)C(O)C1O	SGC0946
+Cn1nnc2c(C(N)=O)ncn2c1=O	Temozolomide
+c1cn2cc(-c3ccc4cn[nH]c4c3)nc(Nc3ccc(N4CCOCC4)cc3)c2n1	Entospletinib
+CN1CCc2c(c3ccccc3n2Cc2ccc(C(=O)NO)cc2)C1	Tubastatin A
+COc1cc([C@@H]2c3cc4c(cc3[C@@H](O[C@@H]3O[C@@H]5CO[C@@H](c6cccs6)O[C@H]5[C@H](O)[C@H]3O)[C@H]3COC(=O)[C@H]23)OCO4)cc(OC)c1O	Teniposide
+CCCCC(C=O)NC(=O)[C@H](CC(C)C)NC(=O)[C@@H](CC(C)C)NC(=O)OCc1ccccc1	Z-LLNle-CHO
+CCNC(=O)Nc1ncc(-c2cc(-c3c(C)cc(OC)cc3C)nc(-c3cnccn3)n2)s1	LIMK1 inhibitor BMS4
+Nc1nc(F)nc2c1ncn2[C@@H]1O[C@H](COP(=O)(O)O)[C@@H](O)[C@@H]1O	Fludarabine
+CCn1c(-c2nonc2N)nc2c(C#CC(C)(C)O)ncc(OCC3CCCNC3)c21	GSK690693
+Cc1c(CN2CCN(C(=O)[C@H](C)O)CC2)sc2c(N3CCOCC3)nc(-c3cnc(N)nc3)nc12	Apitolisib
+Cc1oncc1C(=O)Nc1ccc(C(F)(F)F)cc1	Leflunomide
+Cc1cc([N+](=O)[O-])ccc1NS(=O)(=O)c1cc(Cl)ccc1Cl	FH535
+NCCOc1cc(C(=O)Nc2cc(OCCN)c3ccccc3n2)nc(C(=O)Nc2cc(OCCN)c3ccccc3n2)c1	Pyridostatin
+Cn1cnc2c(F)c(Nc3ccc(Br)cc3Cl)c(C(=O)NOCCO)cc21	Selumetinib
+COc1cc2c(cc1OC)[C@@H]1C(=O)c3ccc4c(c3O[C@@H]1CO2)C[C@H](C(C)C)O4	Dihydrorotenone
+Cc1cc(Nc2nc(N[C@@H](C)c3ccc(F)cc3)c(C#N)cc2F)n[nH]1	AZ960
+O=C(NOCC1CC1)c1ccc(F)c(F)c1Nc1ccc(I)cc1Cl	CI-1040
+CN1CCN(c2ccc([N+](=O)[O-])c3no[n+]([O-])c23)CC1	NSC-207895
+CNCc1ccc(-c2[nH]c3cc(F)cc4c3c2CCNC4=O)cc1	Rucaparib
+Br.C=C1N(CCCCCC(=O)O)c2ccccc2C1(C)C	Cetuximab
+N#CCCC1CCCCC1=NNc1ccc([N+](=O)[O-])cc1[N+](=O)[O-]	JW-7-24-1
+c1ccc(-c2nn3c(c2-c2ccnc4cc(OCCN5CCOCC5)ccc24)CCC3)nc1	LY2109761
+Nc1cccc(-c2cc3c(Oc4cccc(O)c4)ncnc3[nH]2)c1	TWS119
+Nc1nc2c(ncn2[C@@H]2O[C@H](CO)[C@@H](O)[C@@H]2O)c(=O)[nH]1	Ara-G
+CN(C)CC=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OC1CCOC1	Afatinib
+Cc1c2oc3c(C)ccc(C(=O)N[C@@H]4C(=O)N[C@H](C(C)C)C(=O)N5CCC[C@H]5C(=O)N(C)CC(=O)N(C)[C@@H](C(C)C)C(=O)O[C@@H]4C)c3nc-2c(C(=O)N[C@@H]2C(=O)N[C@H](C(C)C)C(=O)N3CCC[C@H]3C(=O)N(C)CC(=O)N(C)[C@@H](C(C)C)C(=O)O[C@@H]2C)c(N)c1=O	Dactinomycin
+Cl.Cl.c1cc(-c2cc(C3CCNCC3)[nH]n2)ccn1	ETP-45835
+COc1ncc(-c2ccc3nccc(-c4ccnnc4)c3c2)cc1NS(=O)(=O)c1ccc(F)cc1F	Omipalisib
+O=C(NC[C@H](O)CN1CCc2ccccc2C1)c1ccnc(NC2CCC2)c1	GSK591
+COc1ccc(Cl)c(Nc2nc3ccccc3nc2NS(=O)(=O)c2cccc(NC(=O)C(C)(C)N)c2)c1	Pilaralisib
+C/C(=C\c1csc(C)n1)[C@@H]1C[C@@H]2O[C@@]2(C)CCC[C@H](C)[C@@H](O)[C@H](C)C(=O)C(C)(C)[C@H](O)CC(=O)O1	Epothilone B
+C[C@]12O[C@H](C[C@]1(O)CO)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)CNC4=O	Lestaurtinib
+O=P(O)(O)C(O)(Cn1ccnc1)P(=O)(O)O	Zoledronate
+Cc1cnc(Nc2ccc(F)cc2Cl)nc1-c1c[nH]c(C(=O)NC(CO)c2cccc(Cl)c2)c1	VX-11e
+C/C=C(/C)C(=O)O[C@H]1C(C)=C2[C@@H]3OC(=O)[C@@](C)(O)[C@@]3(O)[C@@H](OC(=O)CCC)C[C@](C)(OC(C)=O)[C@H]2[C@@H]1OC(=O)CCCCCCC	Thapsigargin
+O=c1[nH]cc(F)c(=O)[nH]1	5-Fluorouracil
+CNC(=O)c1ccc(Nc2cc(Nc3ccccc3S(=O)(=O)C(C)C)c3cc[nH]c3n2)nc1	HG-5-113-01
+Cc1cc(Nc2nc(N[C@@H](C)c3ccc(F)cc3)c(C#N)cc2F)n[nH]1	Telomerase Inhibitor IX
+Nc1[nH]nc2nnc(-c3c(-c4ccccc4)nn4ccccc34)cc12	FR-180204
+Cc1cccc(Nc2nc(-c3ccncc3)cs2)c1	STF-62247
+O=C(C=Cc1cccnc1)NCCCCC1CCN(C(=O)c2ccccc2)CC1	Daporinad
+CCc1nc(N)nc(N)c1-c1ccc(Cl)cc1	Pyrimethamine
+Cc1ccccc1[C@@H](C(=O)NC1CCCCC1)N(C(=O)Cn1ccnc1C)c1cccc(F)c1	AGI-5198
+NC(=O)C1CCCc2c1[nH]c1ccc(Cl)cc21	Selisistat
+COc1cc(F)c(F)c(Nc2ccc(I)cc2F)c1NS(=O)(=O)C1(CC(O)CO)CC1	Refametinib
+CNC(=O)c1ccccc1Sc1ccc2c(C=Cc3ccccn3)n[nH]c2c1	Axitinib
+C[C@]12CC[C@@H]3c4ccc(O)cc4C[C@@H](CCCCCCCCC[S@](=O)CCCC(F)(F)C(F)(F)F)[C@H]3[C@@H]1CC[C@@H]2O	Fulvestrant
+CC(Oc1cc(-c2cnn(C3CCNCC3)c2)cnc1N)c1c(Cl)ccc(F)c1Cl	Crizotinib
+Cc1cc(-c2ncc(CC(=O)Nc3ccc(-c4cnccn4)cn3)cc2C)ccn1	LGK974
+CC1=C(/C=C/C(C)=C/C=C/C(C)=C/C(=O)O)C(C)(C)CCC1	Tretinoin
+Cc1cc(Nc2cc(N3CCN(C)CC3)nc(Sc3ccc(NC(=O)C4CC4)cc3)n2)n[nH]1	Tozasertib
+N#CC1=C(N)NC(=C2C(=O)C=CC=C2OCC2CC2)C=C1C1CCNCC1	KIN001-260
+C[C@@H](Nc1cc(F)cc(F)c1)c1cc(C(=O)N(C)C)cc2c(=O)cc(N3CCOCC3)oc12	AZD8186
+CNc1nc(Nc2ccc(C(=O)N3CCOCC3)cc2OC)ncc1Cl	HG-5-88-01
+NS(=O)(=O)OC[C@@H]1C[C@@H](n2ccc3c(N[C@H]4CCc5ccccc54)ncnc32)C[C@@H]1O	Pevonedistat
+CN(C)CCOc1ccc(-c2nc(=c3ccc4c(c3)CCC=4N=O)c(=C3C=CNC=C3)[nH]2)cc1	SB590885
+Cc1cc(C(C)Nc2ccccc2)c2nc(N3CCOCC3)cc(=O)n2c1	TGX221
+O=C(C=Cc1ccccc1)NC(NC(=S)Nc1cccc2cccnc12)C(Cl)(Cl)Cl	Salubrinal
+CCC1=C[C@@H]2CN(C1)Cc1c([nH]c3ccccc13)[C@@](C(=O)OC)(c1cc3c(cc1OC)N(C)[C@H]1[C@@](O)(C(=O)OC)[C@H](OC(C)=O)[C@]4(CC)C=CCN5CC[C@]31[C@@H]54)C2	Vinorelbine
+COC(=O)c1ccc2c(C(=Nc3ccc(N(C)C(=O)CN4CCN(C)CC4)cc3)c3ccccc3)c(O)[nH]c2c1	BIBF-1120
+Cc1cc(-c2ccc(CC(=O)Nc3ccc(-c4cccnc4)cc3)cc2)ccn1	Wnt-C59
+CC(C)c1ccc(-c2cc(=O)c3ccccc3o2)cc1	MN-64
+CN(NC(=O)CC(=O)NN(C)C(=S)c1ccccc1)C(=S)c1ccccc1	Elesclomol
+Nc1ccc(-c2ccc3ncc4ccc(=O)n(-c5cccc(C(F)(F)F)c5)c4c3c2)cn1	Torin 2
+CNC(=O)Nc1ccc(-c2nc(N3C[C@@H]4CC[C@H](C3)O4)c3cnn(C4CCC5(CC4)OCCO5)c3n2)cc1	WYE-125132
+COc1cc2ncn(-c3cc(OCc4ccccc4S(C)(=O)=O)c(C#N)s3)c2cc1OC	GSK319347A
+C=CC(=O)Nc1cc2c(Nc3ccc(F)c(Cl)c3)ncnc2cc1OCCCN1CCOCC1	CI-1033
+NC(=O)C(CCC(F)(F)F)N(Cc1ccc(-c2ncon2)cc1F)S(=O)(=O)c1ccc(Cl)cc1	Avagacestat
+CCOC(=O)C1=C(C)NC2=C(C(=O)CC(C)(C)C2)[C@@H]1c1ccc(-c2ccccc2)cc1	RVX-208
+O=C(Nc1cccc(Nc2ncc(Br)c(NCCc3cnc[nH]3)n2)c1)N1CCCC1	BX-912
+Cc1sc2c(c1C)C(c1ccc(Cl)cc1)=N[C@@H](CC(=O)Nc1ccc(O)cc1)c1nnc(C)n1-2	OTX015
+Cc1ccc(Nc2nccc(N(C)c3ccc4c(C)n(C)nc4c3)n2)cc1S(N)(=O)=O	Pazopanib
+Cc1nc(Nc2ncc(C(=O)Nc3c(C)cccc3Cl)s2)cc(N2CCN(CCO)CC2)n1	Dasatinib
+Nc1ccn([C@@H]2O[C@H](CO)[C@@H](O)C2(F)F)c(=O)n1	Gemcitabine
+O=C(C=Cc1cccc(S(=O)(=O)Nc2ccccc2)c1)NO	Belinostat
+O=C(O)CCCC[C@H](CCSCc1ccccc1)SCc1ccccc1	CPI-613
+O=[P@]1(N(CCCl)CCCl)NCCCO1	Cyclophosphamide
+CN[C@@H](C)C(=O)N[C@H](C(=O)N1CCC[C@H]1C(=O)N[C@H]1c2ccccc2C[C@H]1OCC#CC#CCO[C@@H]1Cc2ccccc2[C@@H]1NC(=O)[C@@H]1CCCN1C(=O)[C@@H](NC(=O)[C@H](C)NC)C1CCCCC1)C1CCCCC1	AZD5582
+C=CC(=O)N1CCCC(Nc2nc(Nc3ccc(N(C)C(=O)CC)cc3)nc3nc[nH]c23)C1	WZ-1-84
+Cc1ccc(-c2c(C(=O)CCl)n(CCCO)c3ncnc(N)c23)cc1	CMK
+COc1cc(Nc2ncc3c(n2)-c2ccc(Cl)cc2C(c2c(F)cccc2OC)=NC3)ccc1C(=O)O	Alisertib
+C=C(c1ccc(C(=O)O)cc1)c1cc2c(cc1C)C(C)(C)CCC2(C)C	Bexarotene
+CN(C)CC[C@H](CSc1ccccc1)Nc1ccc(S(=O)(=O)NC(=O)c2ccc(N3CCN(Cc4ccccc4-c4ccc(Cl)cc4)CC3)cc2)cc1[N+](=O)[O-]	ABT737
+COc1cc2ncnc(-n3nc(-c4ccccn4)nc3N)c2cc1OC	CP466722
+CCn1cc(-c2ccnc3[nH]c(-c4cccc(CN(C)C)c4)cc23)c(-c2ccc(NC(=O)N(C)C)cc2)n1	GSK1070916
+CCNC(=O)C1=C(c2ccc(CN3CCOCC3)cc2)C(=C2C=C(C(C)C)C(O)=CC2=O)ON1	Luminespib
+OCC(Cc1ccccc1)Nc1nc(Oc2ccc3c(c2)CCC3)nc2c1ncn2Cc1ccc(-c2ccccc2)cc1	QS11
+O=C(/C=C/N1C[C@H]2C[C@@H]1CN2c1ccccn1)c1ccccc1O	PFI3
+CCC(=O)Nc1cccc(Oc2nc(Nc3ccc(N4CCN(C)CC4)cc3OC)ncc2Cl)c1	WZ4003
+Cn1cc(C2=C(c3cn(C4CCN(Cc5ccccn5)CC4)c4ccccc34)C(=O)NC2=O)c2ccccc21	Enzastaurin
+O=C1NCCSc2c1sc1ccc(O)cc21	kb NB 142-70
+O=C1C(=NNc2ccc3cc(S(=O)(=O)O)ccc3c2)C=C(S(=O)(=O)O)c2cccnc21	NSC-87877
+Cc1nc(NC(=O)N2CCC[C@H]2C(N)=O)sc1-c1ccnc(C(C)(C)C(F)(F)F)c1	Alpelisib
+CC(C)C[C@H](NC(=O)[C@H](Cc1ccccc1)NC(=O)c1cnccn1)B(O)O	Bortezomib
+Fc1cc(-c2ccnc(Nc3ccc(-n4cnc(N5CCOCC5)n4)cc3)n2)cc(N2CCOCC2)c1	JNK-9L
+CC1(C)CCC(CN2CCN(c3ccc(C(=O)NS(=O)(=O)c4ccc(NCC5CCOCC5)c([N+](=O)[O-])c4)c(Oc4cnc5[nH]ccc5c4)c3)CC2)=C(c2ccc(Cl)cc2)C1	Venotoclax
+CCN1CCC(n2cc(CNc3cc(Cl)c4ncc(C#N)c(Nc5ccc(F)c(Cl)c5)c4c3)nn2)CC1	KIN001-266
+CC[C@@H](C)CNCC(=O)N1CCc2sccc2[C@@H]1COc1cccc(C)c1	RU-SKI 43
+O=C(NCCCNc1nc(Nc2cccc(NC(=O)N3CCCC3)c2)ncc1I)c1cccs1	BX795
+COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)/C=C/CN1CCCCC1	PF-00299804
+O=C(C=Cc1ccc(CN(CCO)CCc2c[nH]c3ccccc23)cc1)NO	Dacinostat
+Cc1ccc(Nc2cc(-c3cccc(N4C(=O)c5ccccc5C4=O)c3)ncn2)cc1NS(C)(=O)=O	KIN001-270
+CCn1cc(-c2cccc(C(F)(F)F)c2)c2sc(/C(N)=N/C3CCS(=O)(=O)CC3)cc2c1=O	I-BRD9
+CCc1cc(Nc2nccc(-c3c(-c4ccc(OC)c(C(=O)Nc5c(F)cccc5F)c4)nc4ccccn34)n2)c(OC)cc1N1CCC(N2CCN(S(C)(=O)=O)CC2)CC1	GSK1904529A
+CC1(C)CCC(CN2CCN(c3ccc(C(=O)NS(=O)(=O)c4ccc(NCC5CCOCC5)c([N+](=O)[O-])c4)c(Oc4cnc5[nH]ccc5c4)c3)CC2)=C(c2ccc(Cl)cc2)C1	Venetoclax
+CC(C)=CC[C@@H](O)C1=CC(=O)c2c(O)ccc(O)c2C1=O	Shikonin
+NC1=NC(=O)C(=Cc2ccc(O)cc2)S1	Mirin
+CC[C@@]1(O)C(=O)OCc2c1cc1n(c2=O)Cc2cc3c(CN(C)C)c(O)ccc3nc2-1	Topotecan
+CCNC(=O)CC1N=C(c2ccc(Cl)cc2)c2cc(OC)ccc2-n2c(C)nnc21	I-BET-762
+COC(=O)NC1(NC(=O)OC)NC(=O)c2cc(OC)c(OC)c(OC)c2N1	Gallibiscoquinazole
+COc1cc(N2CCN(C)CC2)ccc1Nc1nc(N)c(C(=O)c2c(Cl)cccc2Cl)s1	XMD14-99
+CC1(c2nc3c(C(N)=O)cccc3[nH]2)CCCN1	Veliparib
+CC1=C2CC3C(CC=C4CC(O)CCC43C)C2CCC12OC1CC(C)CNC1C2C	Cyclopamine
+CN1CCN(CCOc2cc(OC3CCOCC3)c3c(Nc4c(Cl)ccc5c4OCO5)ncnc3c2)CC1	Saracatinib
+Cc1sc2c(c1C)C(c1ccc(Cl)cc1)=NC(CC(=O)OC(C)(C)C)c1nnc(C)n1-2	JQ1
+O=c1[nH]c2ccccc2n1C1CCN(Cc2ccc(-c3nc4cc5[nH]cnc5cc4nc3-c3ccccc3)cc2)CC1	AKT inhibitor VIII
+Nc1cc(C(F)(F)F)c(-c2cc(N3CCOCC3)nc(N3CCOCC3)n2)cn1	Buparlisib
+Cc1ccc(NC(=O)c2ccc(CN3CCN(C)CC3)cc2)cc1Nc1nccc(-c2cccnc2)n1	Imatinib
+CN(C)Cc1cccc(NC(=C2C(=O)Nc3cc(C(=O)N(C)C)ccc32)c2ccccc2)c1	BIX02189
+COCCNCCCn1c(C(=O)CF)c(-c2ccc(C)cc2)c2c(N)ncnc21	FMK
+CN(C)C(=O)c1cc2cnc(Nc3ccc(N4CCNCC4)cn3)nc2n1C1CCCC1	Ribociclib
+Cn1cc(-c2ccc3c(c2)CCN3C(=O)Cc2cccc(C(F)(F)F)c2)c2c(N)ncnc21	GSK2606414
+COc1cc(N2CCN(C)CC2)ccc1Nc1ncc2c(n1)N(C)c1ccccc1C(=O)N2C	XMD8-85
+NCC(=O)Nc1ccc(-n2nc(C(F)(F)F)cc2-c2ccc3c(ccc4ccccc43)c2)cc1	OSU-03012
+c1ccc2c(CCNc3ccc(Nc4ccncc4)cc3)c[nH]c2c1	Serdemetan
+COc1nc(N)nc2c1ncn2[C@@H]1O[C@H](CO)[C@@H](O)[C@@H]1O	Nelarabine
+Cn1cc(-c2cnn3c(N)c(Br)c([C@@H]4CCCNC4)nc23)cn1	MK-8776
+O=C1c2c(O)ccc(O)c2C(=O)c2c(NCCNCCO)ccc(NCCNCCO)c21	Mitoxantrone
+NC1(C(=O)N[C@@H](CCO)c2ccc(Cl)cc2)CCN(c2ncnc3[nH]ccc23)CC1	AZD5363
+COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(OC(=O)C(C)(CO)CO)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C	Temsirolimus
+Cn1ncc(Cl)c1-c1cc(C(=O)N[C@H](CN)Cc2ccc(F)c(F)c2)oc1Cl	Uprosertib
+CCC(Nc1ncnc2nc[nH]c12)c1nc2cccc(F)c2c(=O)n1-c1ccccc1	Idelalisib
+CN[C@@H](C)C(=O)N[C@H](C(=O)N1CCC[C@H]1c1nc(C(=O)c2ccc(F)cc2)cs1)C1CCCCC1	LCL161
+CC1=C(C(=O)Nc2cc3cn[nH]c3cc2F)C(c2ccc(C(F)(F)F)cc2)CC(=O)N1	GSK429286A
+COc1ccc(COc2ccc(Cc3cnc(N)nc3N)cc2OC)cc1	GW-2580
+S=C(NCc1ccc2c(c1)OCO2)N1CCN(c2ncnc3c2oc2ccccc23)CC1	Amuvatinib
+CCCC(=O)OCc1ccc(OC(=O)\C=C(/C)\C=C\C=C(/C)\C=C\C2=C(C)CCCC2(C)C)cc1	VNLG/124
+C=CC(=O)Nc1cc(-n2c(=O)ccc3cnc4ccc(-c5ccc(NS(C)(=O)=O)cc5)cc4c32)ccc1C	QL-XII-61
+CC1(C)Cc2c(c(nn2-c2ccc(C(N)=O)c(N[C@H]3CC[C@H](O)CC3)c2)C(F)(F)F)C(=O)C1	SNX-2112
+O=C(CCCCCCNC(=O)c1cnc(N(c2ccccc2)c2ccccc2)nc1)NO	ACY-1215
+O=C(O)CSc1cc(NS(=O)(=O)c2ccc(Br)cc2)c2ccccc2c1O	UMI-77
+CCN1CCN(Cc2ccc(NC(=O)c3ccc(C)c(C=Cc4cnc5[nH]ccc5c4OC)c3)cc2C(F)(F)F)CC1	HG6-64-1
+Cc1cc2c(C(=O)NC[C@H](C)c3ccccc3)c(O)c(O)cc2c(O)c1-c1c(C)cc2c(C(=O)NC[C@H](C)c3ccccc3)c(O)c(O)cc2c1O	Sabutoclax
+Oc1cccc(c1)-c1nc(N2CCOCC2)c2oc3ncccc3c2n1	PI-103
+CC(O)=C(C#N)C(=O)Nc1cc(Br)ccc1Br	LFM-A13
+Cc1cnc(-c2ccccc2C(C)C)nc1NCc1ccc(-n2ccnn2)cc1	ML323
+CCCc1cc(C)[nH]c(=O)c1CNC(=O)c1cc(-c2ccnc(N3CCN(C)CC3)c2)cc2c1cnn2C(C)C	GSK343
+NC(N)=N/C(N)=N\CCc1ccccc1	Phenformin
+Cc1cccc(-c2[nH]c(C(C)(C)C)nc2-c2ccc3c(c2)OCO3)n1	SB505124
+CC(C)C(C(=O)Nc1ccc(C(=O)NO)cc1)c1ccccc1	AR-42
+COc1ccc(C2=NC(c3ccc(Cl)cc3)C(c3ccc(Cl)cc3)N2C(=O)N2CCNC(=O)C2)c(OC(C)C)c1	Nutlin-3a (-)
+NC(=O)c1ccc(N(C(N)=O)c2c(F)cccc2F)nc1-c1ccc(F)cc1F	VX-702
+CC(C)N(C[C@H]1O[C@@H](n2cnc3c(N)ncnc32)[C@H](O)[C@@H]1O)C1CC(CCc2nc3cc(C(C)(C)C)ccc3[nH]2)C1	EPZ5676
+CCN(CC)CCCCNc1ncc2cc(-c3cc(OC)cc(OC)c3)c(NC(=O)NC(C)(C)C)nc2n1	PD173074
+C[C@@H](c1ccc2nccn2c1)n1nnc2ncc(-c3cnn(C)c3)nc21	Savolitinib
+CN(C)C/C=C/C(=O)Nc1cccc(C(=O)Nc2cccc(Nc3ncc(Cl)c(-c4c[nH]c5ccccc45)n3)c2)c1	THZ-2-102-1
+C=CC(=O)Nc1cc(-n2c(=O)ccc3cnc4ccc(-c5cn[nH]c5)cc4c32)ccc1C	QL-X-138
+COc1nc(C)cnc1NS(=O)(=O)c1cccnc1-c1ccc(-c2nnco2)cc1	Zibotentan
+CCOc1cc2ncc(C#N)c(Nc3ccc(F)c(Cl)c3)c2cc1NC(=O)C=CCN(C)C	Pelitinib
+CC(=O)OC1C(C)OC(Oc2c(-c3ccc(O)cc3)oc3cc(O)cc(O)c3c2=O)C(O)C1OC(C)=O	SL0101
+CN1CC[C@H](c2c(O)cc(O)c3c(=O)cc(-c4ccccc4Cl)oc23)[C@H](O)C1	Flavopiridol
+CN(C)CCCCC(=O)Nc1ccc(NC(=S)NC(=O)c2ccc(C(C)(C)C)cc2)cc1	Tenovin-6
+CC\C(=C(\c1ccc(\C=C\C(=O)O)cc1)/c2ccc3[nH]ncc3c2)\c4ccc(F)cc4Cl	GDC0810
+CC(=O)Oc1ccc(C2(c3ccc(OC(C)=O)cc3)C(=O)Nc3ccccc32)cc1	Acetalax
+N[C@@H]1CCCN(c2c(/C=C3/SC(=O)NC3=O)cccc2-c2ccccc2)C1	Kobe2602
+CC[C@]1(O)C[C@H]2CN(CCc3c([nH]c4ccccc34)[C@@](C(=O)OC)(c3cc4c(cc3OC)N(C=O)[C@H]3[C@@](O)(C(=O)OC)[C@H](OC(C)=O)[C@]5(CC)C=CCN6CC[C@]43[C@@H]65)C2)C1	Vincristine
+N#CCC(C1CCCC1)n1cc(-c2ncnc3[nH]ccc23)cn1	Ruxolitinib
+Nc1ncc(-c2ccc3ncc4ccc(=O)n(-c5ccc(N6CCNCC6)c(Cl)c5)c4c3c2)cn1	QL-VIII-58
+Cc1ccc(C(=O)Nc2ccc(CN3CCN(C)CC3)c(C(F)(F)F)c2)cc1C#Cc1cnc2cccnn12	Ponatinib
+Cc1ccc(NC(=O)c2ccc(CN3CCN(C)CC3)cc2)cc1Nc1nc(-c2cccnc2)cs1	Masitinib
+C=CC(=O)N1CCc2ccc(-n3c(=O)ccc4cnc5ccc(-c6cnn(C)c6)cc5c43)cc21	QL-XII-47
+Cn1ncnc1C1C2=c3c(cc(F)cc3=NC1c1ccc(F)cc1)C(=O)NN2	Talazoparib
+O=C(O)c1ccc(-c2c[nH]c3ncc(-c4ccccc4)cc23)cc1C1CCCC1	GSK650394
+CC(C)N(CCCNC(=O)Nc1ccc(C(C)(C)C)cc1)C[C@H]1O[C@@H](n2ccc3c(N)ncnc32)[C@H](O)[C@@H]1O	EPZ004777
+C/C(=N\NC(=S)N1CCC1)c1ccccn1	NSC319726
+CCC(C)C(NC(=O)C(CCC(N)=O)NC(=O)C(CCC(=O)O)NC(=O)C(CCC(N)=O)NC(=O)C(CC(C)C)NC(=O)C(NC(=O)C(CO)NC(=O)C(N)C(C)O)C(C)O)C(=O)NCC(=O)NC(Cc1c[nH]c2ccccc12)C(=O)O	TW 37
+C=CC(=O)Nc1cc(NC(=O)c2ccc(C)c(NC(=O)c3ccno3)c2)cc(C(F)(F)F)c1	QL-XI-92
+O=C(/C=C/N1C[C@H]2C[C@@H]1CN2c1ccccn1)c1ccccc1O	PFI-3
+COc1cc2c(Oc3ccc(NC(=O)C4(C(=O)Nc5ccc(F)cc5)CC4)cc3F)ccnc2cc1OCCCN1CCOCC1	Foretinib
+COC1CC2CCC(C)C(O)(O2)C(=O)C(=O)N2CCCCC2C(=O)OC(C(C)CC2CCC(O)C(OC)C2)CC(=O)C(C)C=C(C)C(O)C(OC)C(=O)C(C)CC(C)C=CC=CC=C1C	Rapamycin
+N#CC(c1ccnc(NCCc2cccnc2)n1)c1nc2ccccc2s1	AS601245
+C=C1C(=O)OC(CCCCCCCC)C1C(=O)O	C-75
+O=C(Nc1ccc(Nc2nccc(Nc3cc(C4CCCC4)[nH]n3)n2)cc1)Nc1cccc(C(F)(F)F)c1	CD532
+CCOc1nc(NC(=O)Cc2cc(OC)ccc2OC)cc(N)c1C#N	JNK Inhibitor VIII
+COc1cc2nccc(Oc3ccc(NC(=O)C4(C(=O)Nc5ccc(F)cc5)CC4)cc3)c2cc1OC	Cabozantinib
+C=CCNC1=C2CC(C)CC(OC)C(O)C(C)C=C(C)C(OC(N)=O)C(OC)C=CC=C(C)C(=O)NC(=CC1=O)C2=O	Tanespimycin
+COC[C@]1(CO)C(=O)C2CCN1CC2	PRIMA-1MET
+CCc1c2c(nc3ccc(OC(=O)N4CCC(N5CCCCC5)CC4)cc13)-c1cc3c(c(=O)n1C2)COC(=O)[C@]3(O)CC	Irinotecan
+CC(C)Nc1cc(-c2c[nH]c(C(=O)N[C@H](CO)c3cccc(Cl)c3)c2)c(Cl)cn1	Ulixertinib
+NC(=O)c1cccc2cn(-c3ccc([C@@H]4CCCNC4)cc3)nc12	Niraparib
+OCCCNc1cc(-c2ccnc(Nc3cccc(Cl)c3)n2)ccn1	CGP-60474
+COc1cc(Nc2c(C#N)cnc3cc(OCCCN4CCN(C)CC4)c(OC)cc23)c(Cl)cc1Cl	Bosutinib
+Oc1ccc(Nc2nc(-c3ccc(Cl)cc3)cs2)cc1	Sphingosine Kinase 1 Inhibitor II
+COC(=O)C(CCSC)NC(=O)c1ccc(NCC(N)CS)cc1-c1ccccc1	FTI-277
+COc1cc2ncnc(Nc3cccc(Cl)c3F)c2cc1OC(=O)N1CCN(C)C[C@H]1C	AZD3759
+Cc1nc(-c2cn3c(n2)-c2ccc(-c4cnn(C(C)(C)C(N)=O)c4)cc2OCC3)n(C(C)C)n1	Taselisib
+CCN1CCN(Cc2ccc(NC(=O)c3ccc(C)c(Oc4ccnc5[nH]ccc45)c3)cc2C(F)(F)F)CC1	NG-25
+Cn1cncc1C(N)(c1ccc(Cl)cc1)c1ccc2c(c1)c(-c1cccc(Cl)c1)cc(=O)n2C	Tipifarnib
+CC(C)(C)OC(=O)Nc1ccc(-c2cc(C(=O)NCCCCCCC(=O)NO)no2)cc1	CAY10603
+COc1cc(O)c2c(c1)C=CCC(O)C(O)C(=O)C=CCC(C)OC2=O	(5Z)-7-Oxozeaenol
+CCCCCCCCCCCC1=C(O)C(=O)C=C(O)C1=O	Embelin
+CCOc1ccccc1N/N=C1/C(=O)N(c2nc(-c3ccccc3)cs2)N=C1C	BAM7
+CC1(O)CC(c2nc(-c3ccc4ccc(-c5ccccc5)nc4c3)c3c(N)nccn23)C1	Linsitinib
+NC[C@@](O)(c1ccc(Cl)cc1)c1ccc(-c2cn[nH]c2)cc1	AT13148
+Cc1cnc(Nc2ccc(OCCN3CCCC3)cc2)nc1Nc1cccc(S(=O)(=O)NC(C)(C)C)c1	Fedratinib
+Cc1ccc(C(=O)Nc2cccc(C(F)(F)F)c2)cc1Nc1nc(-c2cccnc2)nc2c1cnn2C	NVP-BHG712
+N=c1nc(N2CCCCC2)cc(N)n1O	Cisplatin
+CO[C@@]12[C@H](COC(N)=O)C3=C(C(=O)C(C)=C(N)C3=O)N1C[C@@H]1N[C@@H]12	Mitomycin-C
+O=C(O)CNC(=O)c1c(O)c2ccccc2n(Cc2ccccc2)c1=O	IOX2
+CN(Cc1cnc2nc(N)nc(N)c2n1)c1ccc(C(=O)N[C@@H](CCC(=O)O)C(=O)O)cc1	Methotrexate
+CC(C)NC[C@@H](C(=O)N1CCN(c2ncnc3c2[C@H](C)C[C@H]3O)CC1)c1ccc(Cl)cc1	Ipatasertib
+O=C(Nc1cccc(C(F)(F)F)c1)Nc1cc(S(=O)(=O)NC2CC2)ccc1-c1ccsc1	AGI-6780
+COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@H](N)[C@H](O)[C@H](C)O1	Doxorubicin
+COc1cc(C)c(Sc2cnc(NC(=O)c3ccc(CNC(C)C(C)(C)C)cc3)s2)cc1C(=O)N1CCN(C(C)=O)CC1	BMS-509744
+CCC(=C(c1ccccc1)c1ccc(OCCN(C)C)cc1)c1ccccc1	Tamoxifen
+CS(=O)(=O)CCNCc1ccc(-c2ccc3ncnc(Nc4ccc(OCc5cccc(F)c5)c(Cl)c4)c3c2)o1	Lapatinib
+CC(/C=C/C(=O)NO)=C\[C@@H](C)C(=O)c1ccc(N(C)C)cc1	Trichostatin A
+CS(=O)(=O)c1ccc(-c2cnc(N)c(C(=O)Nc3ccccc3)n2)cc1	VE821
+C=C1C(=O)O[C@H]2C[C@@H]1CC[C@@]1(C)O[C@@H]1CC/C(C)=C\CC[C@@]2(C)O	Sinularin
+Cc1[nH]c2ccccc2c1CCNCc1ccc(/C=C/C(=O)NO)cc1	Panobinostat
+Ic1cccc(CSc2nnc(-c3ccncc3)o2)c1	KIN001-042
+NC(=O)c1cccc(-c2cc(Nc3ccc(OC(F)(F)F)cc3)ncn2)c1	GNF-2
+C[C@@H]1COCCN1c1cc(C2([S@](C)(=N)=O)CC2)nc(-c2ccnc3[nH]ccc23)n1	AZD6738
+NC(=O)c1ncn(C2OC(COP(=O)(O)O)C(O)C2O)c1N	AICA Ribonucleotide
+COC1(c2sc3c(N4CCOCC4)nc(-c4cnc(N)nc4)nc3c2C)COC1	GNE-317
+CS(=O)(=O)c1ccc(C(=O)Nc2ccc(Cl)c(-c3ccccn3)c2)c(Cl)c1	Vismodegib
+Cc1[nH]nc2ccc(-c3cncc(OCC(N)Cc4c[nH]c5ccccc45)c3)cc12	A-443654
+Cc1csc(=NC2CCCCC2)n1/N=C/c1ccc(O)c(O)c1O	MIM1
+O=C(NOCC(O)CO)c1ccc(F)c(F)c1Nc1ccc(I)cc1F	PD0325901
+NC(CSC(c1ccccc1)(c1ccccc1)c1ccccc1)C(=O)O	S-Trityl-L-cysteine
+CCc1nc(-c2cccc(C)c2)c(-c2ccnc(NC(=O)c3ccccc3)c2)s1	TAK-715
+COc1cc(C(=O)NC2CCN(C)CC2)ccc1Nc1ncc2c(n1)N(C1CCCC1)C(C)CC(=O)N2C	NPK76-II-72-1
+Nc1nc2[nH]cc(CCc3ccc(C(=O)N[C@H](CCC(=O)O)C(=O)O)cc3)c2c(=O)[nH]1	Pemetrexed
+CCNc1cc(NC2CCC(O)CC2)nc(Nc2ccc3c(ccn3Cc3ccccc3)c2)n1	CGP-082996
+C#Cc1cccc(Nc2ncnc3cc(OCCOC)c(OCCOC)cc23)c1	Erlotinib
+CC(=O)Nc1cccc(-n2c(=O)n(C3CC3)c(=O)c3c(Nc4ccc(I)cc4F)n(C)c(=O)c(C)c32)c1	Trametinib
+COCC(=O)NCC=Cc1ccc2ncnc(Nc3ccc(Oc4ccc(C)nc4)c(C)c3)c2c1	CP724714
+COc1cc2c(cc1NS(=O)(=O)c1ccc(Br)cc1C)n(C)c(=O)n2C	OF-1
+CON(C)C(=O)N1N=C(c2cc(F)ccc2F)S[C@@]1(CCCN)c1ccccc1	ARRY-520
+COc1ccccc1S(=O)(=O)Nc1ccc2c(c1)CN(C)C(=O)N2	PFI-1
+C=CC(=O)N1CCC[C@@H](n2nc(-c3ccc(Oc4ccccc4)cc3)c3c(N)ncnc32)C1	Ibrutinib
+Cn1ncc(Cl)c1-c1cc(C(=O)N[C@H](CN)Cc2cccc(F)c2)sc1Cl	Afuresertib
+COCC[n+]1c2c(n(Cc3cnccn3)c1C)C(=O)c1ccccc1C2=O	Sepantronium bromide
+Cc1[nH]c(C=C2C(=O)Nc3ccc(S(=O)(=O)Cc4c(Cl)cccc4Cl)cc32)c(C)c1C(=O)N1CCCC1CN1CCCC1	PHA-665752
+CNC(=O)c1cc(Oc2ccc(NC(=O)Nc3ccc(Cl)c(C(F)(F)F)c3)cc2)ccn1	Sorafenib
+CCn1c(=O)c(-c2ccn[nH]2)cc2c(C)nc(N)nc21	Voxtalisib
+CC(N)c1ccc(C(=O)Nc2ccnc3[nH]ccc23)cc1.Cl	Y-39983
+C=CC(=O)Nc1cc(Nc2nccc(-c3cn(C)c4ccccc34)n2)c(OC)cc1N(C)CCN(C)C	Osimertinib
+CC(=O)O[C@@]12CO[C@@H]1C[C@H](O)[C@@]1(C)C(=O)[C@H](O)C3=C(C)[C@@H](OC(=O)[C@H](O)[C@@H](NC(=O)OC(C)(C)C)c4ccccc4)C[C@@](O)([C@@H](OC(=O)c4ccccc4)[C@@H]12)C3(C)C	Docetaxel
+O=c1nc(-c2ccc(C(F)(F)F)cc2)[nH]c2c1CSCC2	XAV939
+O=C(NC(COc1ccc2[nH]c(=O)[nH]c2c1)c1ccccc1)c1cccn(Cc2ccc(F)c(F)c2)c1=O	KIN001-244
+COC1C(N(C)C(=O)c2ccccc2)CC2OC1(C)n1c3ccccc3c3c4c(c5c6ccccc6n2c5c31)C(=O)NC4	Midostaurin
+COc1cc2ncnc(Nc3cc(Br)c(O)c(Br)c3)c2cc1OC	WHI-P97
+COc1cc(/C=C/C(=O)N2CCC=CC2=O)cc(OC)c1OC	Piperlongumine
+CS(=O)(=O)N1CCN(Cc2cc3nc(-c4cccc5[nH]ncc45)nc(N4CCOCC4)c3s2)CC1	Pictilisib
+O=C1NC(=O)C(=Cc2ccc3nccnc3c2)S1	AS605240
+Cn1cc(C=C2C(=O)Nc3cccnc32)c2ccccc21	GW441756
+COc1ccc(Cn2ccc3ccc(C(=O)NO)cc32)cc1	PCI-34051
+CCc1cc2c(cc1N1CCC(N3CCOCC3)CC1)C(C)(C)c1[nH]c3cc(C#N)ccc3c1C2=O	Alectinib
+CCCCCCCCc1ccc(CCC(N)(CO)CO)cc1.Cl	FTY-720
+Cc1cccc(-c2[nH]c(C(C)(C)C)nc2-c2ccc3nccnc3c2)n1	SB52334
+CCC1(O)C(=O)OCc2c1cc1n(c2=O)Cc2cc3ccccc3nc2-1	Camptothecin
+Cn1cc(C2=C(c3ccc(Cl)cc3Cl)C(=O)NC2=O)c2ccccc21	SB216763
+O=c1cc(N2CCOCC2)oc2c(-c3cccc4c3sc3ccccc34)cccc12	NU7441
+O=S(=O)(c1ccccc1)N(CC(F)(F)F)c1ccc(C(O)(C(F)(F)F)C(F)(F)F)cc1	T0901317
+COc1cc2ncnc(Nc3ccc(F)c(Cl)c3)c2cc1OCCCN1CCOCC1	Gefitinib
+CCn1c(=O)c2cc(C(N)=O)c(N)nc2n(C2CC2)c1=O	eEF2K Inhibitor, A-484954
+Cc1nnc(-c2ccc(N3CCC(Oc4cc(F)ccc4Cl)CC3)nn2)o1	CAY10566
+Cc1ccc(F)c(NC(=O)Nc2ccc(-c3cccc4[nH]nc(N)c34)cc2)c1	Linifanib
+CCn1c(-c2nonc2N)nc2cnc(Oc3cccc(NC(=O)c4ccc(OCCN5CCOCC5)cc4)c3)cc21	GSK269962A
+CCOc1cc(N2CCC(O)CC2)ccc1Nc1ncc2c(n1)N(C)c1ccccc1C(=O)N2C	XMD8-92
+COc1cc2ncn(-c3cc(OCc4ccccc4C(F)(F)F)c(C(N)=O)s3)c2cc1OC	GW843682X
+COc1ccc(-n2c(SCCCN3C(=O)c4cccc5cccc(c45)C3=O)nnc2-c2ccncc2)cc1	WIKI4
+CC1(C)CCC(c2ccc(Cl)cc2)=C(CN2CCN(c3ccc(C(=O)NS(=O)(=O)c4ccc(NC(CCN5CCOCC5)CSc5ccccc5)c(S(=O)(=O)C(F)(F)F)c4)cc3)CC2)C1	Navitoclax
+CN(c1ncccc1CNc1nc(Nc2ccc3c(c2)CC(=O)N3)ncc1C(F)(F)F)S(C)(=O)=O	PF-562271
+CC1(C)CNc2cc(NC(=O)c3cccnc3NCc3ccncc3)ccc21	Motesanib
+COc1cc(C(=O)NC2CCN(C)CC2)ccc1Nc1ncc2c(n1)N(C1CCCC1)CCC(=O)N2C(C)C	XMD11-85h
+COc1ccc(C(=O)C[C@@]2(O)C(=O)Nc3c(Cl)ccc(Cl)c32)cc1	YK-4-279
+CS(=O)(=O)c1ccc(-c2cnc(N)c(C(=O)Nc3ccccc3)n2)cc1	A-83-01
+CCN(CC)CCNC(=O)c1c(C)[nH]c(C=C2C(=O)Nc3ccc(F)cc32)c1C	Sunitinib
+CC(C)(C)NS(=O)(=O)c1cncc(-c2cc(F)c3nc(N)nn3c2)c1	CZC24832
+C[C@H](Nc1ncnc2nc[nH]c12)c1cc2ccc(F)cc2nc1-c1ccccn1	AMG-319
+COC(=O)CNC(=O)C(=O)OC	DMOG
+CNCc1ccc(-c2cc(-c3nc(-c4ccc(S(=O)(=O)C(C)C)cc4)cnc3N)on2)cc1	VE-822
+CN(C)CC=CC(=O)Nc1ccc(C(=O)Nc2cccc(Nc3nccc(-c4cccnc4)n3)c2)cc1	ZG-10
+COc1cc(N2CCC(O)CC2)ccc1Nc1cc(Nc2ccccc2S(=O)(=O)C(C)C)c2cc[nH]c2n1	MPS-1-IN-1
+COc1cc(C2c3cc4c(cc3C(OC3OC5COC(C)OC5C(O)C3O)C3COC(=O)C23)OCO4)cc(OC)c1O	Etoposide
+Cl.Cl.O=c1cc(CN2CCOCC2)occ1OCCCCCSc1ccnc2cc(C(F)(F)F)ccc12	EHT-1864
+C=CC(=O)Nc1ccc2ncnc(Nc3ccc(OCc4cccc(F)c4)c(Cl)c3)c2c1	AST-1306
+Oc1c(F)cc(-c2cnccc2-c2ccc(N3CCOCC3)cc2)cc1F	LJI308
+Nc1ccc(C(=O)Nc2cccc(-c3nc(N4CCOCC4)c4oc5ncccc5c4n3)c2)cn1	YM201636
+COc1cc(=C2C=c3ccccc3=N2)[nH]c1=Cc1[nH]c(C)cc1C.CS(=O)(=O)O	Obatoclax Mesylate
+CCC1=CC(=C2NNC(C)=C2c2ccc3c(c2)OCCO3)C(=O)C=C1O	CCT-018159
+COc1cccc2c1C(=O)c1c(O)c3c(c(O)c1C2=O)C[C@@](O)(C(=O)CO)C[C@@H]3O[C@H]1C[C@@H](N)[C@H](O)[C@H](C)O1	Epirubicin
+COc1cc2c(NC3CCN(C(C)C)CC3)nc(N3CCC(F)(F)CC3)nc2cc1OCCCN1CCCC1	UNC0642
+Cc1cn(-c2cc(NC(=O)c3ccc(C)c(Nc4nccc(-c5cccnc5)n4)c3)cc(C(F)(F)F)c2)cn1	Nilotinib
+COc1cc2c(Nc3ccc(NC(=O)c4ccccc4)cc3)ncnc2cc1OCCCN1CCOCC1	ZM447439
+Cc1cc2c(F)c(Oc3ncnn4cc(OC[C@@H](C)O)c(C)c34)ccc2[nH]1	Brivanib, BMS-540215
+C=C1C(=O)O[C@H]2[C@H]1[C@@H](OC(=O)C=C(C)C)CC1=C[C@@H](C[C@@]3(C)O[C@H]23)OC1=O	Elephantin
+O=C1C(=Cc2cccs2)CCC1=Cc1cccs1	CCT007093
+Cc1cc(N2C[C@H](C)N[C@H](C)C2)ncc1-c1ccc(-c2nc(=O)c3ccn(C)c3[nH]2)cc1	AZ6102
+Nc1ccccc1NC(=O)c1ccc(CNC(=O)OCc2cccnc2)cc1	Entinostat
+O=C(Nc1cc(C(F)(F)F)cc(C(F)(F)F)c1)c1cc(Cl)ccc1O	IMD-0354
+Cc1c(N)nc([C@H](CC(N)=O)NC[C@H](N)C(N)=O)nc1C(=O)N[C@H](C(=O)N[C@H](C)[C@@H](O)[C@H](C)C(=O)N[C@H](C(=O)NCCc1nc(-c2nc(C(=O)NCCC[S+](C)C)cs2)cs1)[C@@H](C)O)[C@@H](OC1OC(CO)C(O)C(O)C1OC1OC(CO)C(O)C(OC(N)=O)C1O)c1cnc[nH]1	Bleomycin
+O=C1NC(=O)c2c1c(-c1ccccc1Cl)cc1[nH]c3ccc(O)cc3c21	Wee1 Inhibitor
+O=C(Nc1cccnc1)c1cc(-c2ccnc(F)c2)ccc1OCc1ccccc1	GSK2578215A
+NC(=O)c1cnc(N[C@@H]2CCCC[C@@H]2N)nc1Nc1cccc(-n2nccn2)c1	PRT062607
+CCC(CO)Nc1nc(NCc2ccccc2)c2ncn(C(C)C)c2n1	Seliciclib
+CCCC=CC=CC(=O)OC1C(=CC(=O)OC)CC2CC(C(C)O)OC(=O)CC(O)CC3CC(OC(C)=O)C(C)(C)C(O)(CC4CC(=CC(=O)OC)CC(C=CC(C)(C)C1(O)O2)O4)O3	Bryostatin 1
+Cc1ccc2nc(NC(=O)CSc3nc4c(c(=O)n3-c3ccccc3)SCC4)sc2c1	IWP-2
+Nc1ccn([C@@H]2O[C@H](CO)[C@@H](O)[C@@H]2O)c(=O)n1	Cytarabine
+Cc1ccc(NC(=O)c2cccc(C(C)(C)C#N)c2)cc1Nc1ccc2ncn(C)c(=O)c2c1	AZ628
+CC(=O)c1c(C)c2cnc(Nc3ccc(N4CCNCC4)cn3)nc2n(C2CCCC2)c1=O	Palbociclib
+Cn1cc(-c2ccc3nnc(C(F)(F)c4ccc5ncccc5c4)n3n2)cn1	JNJ38877605
+CCc1cncnc1N1CCN(Cc2nc3ccc(C(F)(F)F)cc3[nH]2)CC1	PF-4708671
+CC[C@]1(O)C[C@@H]2CN(CCc3c([nH]c4ccccc34)[C@@](C(=O)OC)(c3cc4c(cc3OC)N(C)[C@H]3[C@@](O)(C(=O)OC)[C@H](OC(C)=O)[C@]5(CC)C=CCN6CC[C@]43[C@@H]65)C2)C1	Vinblastine
+CNC(=O)CN1CCC(Oc2cc3c(Nc4cccc(Cl)c4F)ncnc3cc2OC)CC1	Sapitinib
+COc1cc(-c2nn(C3CCC(N4CCN(C(C)=O)CC4)CC3)c3ncnc(N)c23)ccc1NC(=O)c1cc2ccccc2n1C	A-770041
+CC(=O)c1cc([N+](=O)[O-])c(Sc2ccc(F)cc2F)s1	P22077
+CCC(=O)OCN1C(=O)C=CC1=O	MIRA-1
+CC(C)(C)c1nc(-c2cccc(NS(=O)(=O)c3c(F)cccc3F)c2F)c(-c2ccnc(N)n2)s1	Dabrafenib
+O=C1N=C(NCc2cccs2)SC1=Cc1ccc2ncccc2c1	RO-3306
+O=C(CCCCCCC(=O)Nc1ccccc1)NO	Vorinostat
+O=C(Nc1ccc2[nH]nc(-c3ccncc3)c2c1)[C@@H]1CCN(CC(=O)N2CCN(c3ccc(-c4ncccn4)cc3)CC2)C1	SCH772984
+COc1cc2c(Oc3ccc4[nH]c(C)cc4c3F)ncnc2cc1OCCCN1CCCC1	Cediranib
+C=C1C(=O)OC2C1CCC(C)=CCCC1(C)OC21	Parthenolide
+O=C(NC1CCNCC1)c1[nH]ncc1NC(=O)c1c(Cl)cccc1Cl	AT-7519
+Cc1c(N)nc([C@H](CC(N)=O)NC[C@H](N)C(N)=O)nc1C(=O)N[C@H](C(=O)N[C@H](C)[C@@H](O)[C@H](C)C(=O)N[C@H](C(=O)NCCc1nc(-c2nc(C(=O)NCCC[S+](C)C)cs2)cs1)[C@@H](C)O)[C@@H](O[C@@H]1O[C@@H](CO)[C@@H](O)[C@H](O)[C@@H]1O[C@H]1O[C@H](CO)[C@@H](O)[C@H](OC(N)=O)[C@@H]1O)c1cnc[nH]1	Bleomycin (50 uM)
+O=C(NC1CC1)c1cccc(-c2ccc3c(NC(=O)C4CC4)n[nH]c3c2)c1	XMD13-2
+O=C(c1ccc(C(=O)N2CCC(N3CCCC3)CC2)c(Nc2ccccc2)c1)N1CCC(N2CCCC2)CC1	UNC1215
+Nc1cccc2c1CN(C1CCC(=O)NC1=O)C2=O	Lenalidomide
+O=C(Nc1cccc(Nc2ncc(Br)c(NCCc3c[nH]cn3)n2)c1)N1CCCC1	LDN-193189
+C=CC(=O)Nc1cccc(Nc2nc(NC3CCC(N(C)C)CC3)nc3c2ncn3C(C)C)c1	WZ3105
+O=NN(CCCl)C(=O)NCCCl	Carmustine
+COc1ccc(-c2cc3nccn3c(Nc3ncccc3C(N)=O)n2)cc1OC.Cl.Cl	BAY-61-3606
+Cn1c(=O)n(-c2ccc(C(C)(C)C#N)cc2)c2c3cc(-c4cnc5ccccc5c4)ccc3ncc21	Dactolisib
+Oc1ccc2ccccc2c1SSc1c(O)ccc2ccccc12	IPA-3
+COc1ccc(N(C(=O)Oc2c(C)cccc2C)c2ccnc(Nc3ccc(N4CCN(C)CC4)cc3)n2)c(OC)c1	WH-4-023
+NCc1ccc(OCCCc2sc(-c3ccc4c(c3)/C(=N/Nc3nc5ccccc5s3)CCC4)nc2C(=O)O)cc1	WEHI-539
+O=C([O-])C(=O)[O-].[NH-][C@@H]1CCCC[C@H]1[NH-].[Pt+4]	Oxaliplatin
+O=C(c1cc(Cc2n[nH]c(=O)c3ccccc23)ccc1F)N1CCN(C(=O)C2CC2)CC1	Olaparib
+COc1cc2nccc(Oc3ccc(NC(=O)Nc4cc(C)on4)c(Cl)c3)c2cc1OC	Tivozanib
+CC(C)(C)c1cc(NC(=O)Nc2ccc(-c3cn4c(n3)sc3cc(OCCN5CCOCC5)ccc34)cc2)no1	Quizartinib
+CS(=O)(=O)O.Cc1ccc(C(=O)N(CCCN)C(c2nc3cc(Cl)ccc3c(=O)n2Cc2ccccc2)C(C)C)cc1	Ispinesib Mesylate
+CC(O)(CS(=O)(=O)c1ccc(F)cc1)C(=O)Nc1ccc(C#N)c(C(F)(F)F)c1	Bicalutamide
+Cc1ccc(-n2nc(C(C)(C)C)cc2NC(=O)Nc2ccc(OCCN3CCOCC3)c3ccccc23)cc1	Doramapimod
+Cc1cnc(CNC(=O)c2c(=O)c3ccc(N4CCCN(C)CC4)nc3n3c2sc2ccccc23)cn1	CX-5461

artifacts/model.json

@@ -0,0 +1 @@
+{"drug_sensitivity_min_max": true, "gene_expression_min_max": false, "gene_expression_standardize": false, "augment_smiles": false, "canonical": false, "kekulize": false, "all_bonds_explicit": false, "all_hs_explicit": false, "randomize": false, "remove_bonddir": false, "remove_chirality": false, "selfies": false, "smiles_start_stop_token": true, "number_of_genes": 2128, "smiles_padding_length": 465, "stacked_dense_hidden_sizes": [512], "activation_fn": "relu", "dropout": 0.4, "batch_norm": true, "filters": [64, 64, 64], "multiheads": [4, 4, 4, 4], "smiles_embedding_size": 16, "kernel_sizes": [[3, 16], [5, 16], [11, 16]], "smiles_attention_size": 64, "embed_scale_grad": false, "final_activation": true, "gene_to_dense": false, "batch_size": 2048, "dataset_device": "cuda", "lr": 0.001, "optimizer": "adam", "loss_fn": "mse", "epochs": 200, "save_model": 25, "smiles_vocabulary_size": 108, "drug_sensitivity_processing_parameters": {"processing": "min_max", "parameters": {"min": -11.998083341987641, "max": 12.359055999999999}}, "gene_expression_processing_parameters": {}, "number_of_parameters": 7217361}

attention.py

@@ -0,0 +1,126 @@
+"""Get/put submission results concerning attention from/on COS."""
+import os
+import json
+import dill
+import logging
+import numpy as np
+from typing import Iterable
+from configuration import GENES
+from cos import (
+    RESULTS_PREFIX,
+    bytes_from_key,
+    string_from_key,
+    bytes_to_key,
+)
+from utils import Drug
+from plots import embed_barplot
+from smiles import smiles_attention_to_svg
+
+logger = logging.getLogger("openapi_server:attention")
+
+
+def download_attention(workspace_id: str, task_id: str, sample_name: str) -> dict:
+    """
+    Download attention figures and related data.
+
+    Args:
+        workspace_id (str): workspace identifier.
+        task_id (str): task identifier.
+        sample_name (str): name of the sample.
+
+    Returns:
+        dict: attention figures and related data.
+    """
+
+    def _remote_to_bytes(basename: str) -> bytes:
+        object_name = os.path.join(workspace_id, task_id, sample_name, basename)
+        key = os.path.join(RESULTS_PREFIX, object_name)
+        return bytes_from_key(key)
+
+    drug_path = os.path.join(workspace_id, task_id, "drug.json")
+    key = os.path.join(RESULTS_PREFIX, drug_path)
+    drug = Drug(**json.loads(string_from_key(key)))
+    logger.debug(f"download attention results from COS for {drug.smiles}.")
+    # omic
+    logger.debug("gene attention.")
+    gene_attention = dill.loads(_remote_to_bytes("gene_attention.pkl"))
+    genes = np.array(GENES)
+    order = gene_attention.argsort()[::-1]  # descending
+    gene_attention_js, gene_attention_html = embed_barplot(
+        genes[order], gene_attention[order]
+    )
+    logger.debug("gene attention plots created.")
+    # smiles
+    logger.debug("SMILES attention.")
+    smiles_attention = dill.loads(_remote_to_bytes("smiles_attention.pkl"))
+    drug_attention_svg, drug_color_bar_svg = smiles_attention_to_svg(
+        drug.smiles, smiles_attention
+    )
+    logger.debug("SMILES attention plots created.")
+    return {
+        "drug": drug,
+        "sample_name": sample_name,
+        "sample_drug_attention_svg": drug_attention_svg,
+        "sample_drug_color_bar_svg": drug_color_bar_svg,
+        "sample_gene_attention_js": gene_attention_js,
+        "sample_gene_attention_html": gene_attention_html,
+    }
+
+
+def _upload_ndarray(sample_prefix: str, array: np.ndarray, filename: str) -> None:
+    bytes_to_key(dill.dumps(array), os.path.join(sample_prefix, f"{filename}.pkl"))
+
+
+def upload_attention(
+    prefix: str,
+    sample_names: Iterable[str],
+    omic_attention: np.ndarray,
+    smiles_attention: np.ndarray,
+) -> None:
+    """
+    Upload attention profiles.
+
+    Args:
+        prefix (str): base prefix used as a root.
+        sample_names (Iterable[str]): name of the samples.
+        omic_attention (np.ndarray): attention values for genes.
+        smiles_attention (np.ndarray): attention values for SMILES.
+
+    Raises:
+        ValueError: mismatch in sample names and gene attention.
+        ValueError: mismatch in sample names and SMILES attention.
+        ValueError: mismatch in number of genes and gene attention.
+    """
+    omic_entities = np.array(GENES)
+    # sanity checks
+    if len(sample_names) != omic_attention.shape[0]:
+        raise ValueError(
+            f"length of sample_names {len(sample_names)} does not "
+            f"match omic_attention {omic_attention.shape[0]}"
+        )
+    if len(sample_names) != len(smiles_attention):
+        raise ValueError(
+            f"length of sample_names {len(sample_names)} does not "
+            f"match smiles_attention {len(smiles_attention)}"
+        )
+    if len(omic_entities) != omic_attention.shape[1]:
+        raise ValueError(
+            f"length of omic_entities {len(omic_entities)} "
+            f"does not match omic_attention.shape[1] {omic_attention.shape[1]}"
+        )
+    # special case first
+    sample_name = "average"
+    # omic
+    res = {}
+    omic_alphas = omic_attention.mean(axis=0)
+    res["gene_attention"] = omic_alphas
+
+    # smiles
+    smiles_alphas = smiles_attention.mean(axis=0)
+    res["smiles_attention"] = smiles_alphas
+
+    # logging.debug('uploaded "average" attention figures.')
+    # for index, sample_name in enumerate(sample_names):
+    #     res[f"gene_attention_{index}"] = omic_attention[index]
+    #     res[f"smiles_attention_{index}"] = smiles_attention[index]
+    return res

configuration.py

@@ -0,0 +1,73 @@
+"""Configuration utils."""
+import os
+import json
+import dill
+import pandas as pd
+from pytoda.transforms import Compose
+from pytoda.smiles.transforms import SMILESToTokenIndexes, LeftPadding
+from cos import ensure_filepath_from_uri, COS_BUCKET_URI
+
+# model files
+MODEL_WEIGHTS_URI = ensure_filepath_from_uri(os.path.join(COS_BUCKET_URI, "model.pt"))
+MODEL_PARAMS_URI = ensure_filepath_from_uri(os.path.join(COS_BUCKET_URI, "model.json"))
+# SMILES language file
+SMILES_LANGUAGE_URI = ensure_filepath_from_uri(
+    os.path.join(COS_BUCKET_URI, "smiles_language.pkl")
+)
+# gene expression file
+GENE_EXPRESSION_URI = ensure_filepath_from_uri(
+    os.path.join(COS_BUCKET_URI, "gene_expression.csv.zip")
+)
+# genes file
+GENES_URI = ensure_filepath_from_uri(os.path.join(COS_BUCKET_URI, "genes.pkl"))
+# genes standardization parameters
+GENE_EXPRESSION_STANDARDIZATION_URI = ensure_filepath_from_uri(
+    os.path.join(COS_BUCKET_URI, "gene_expression_standardization.pkl")
+)
+# load the model
+with open(MODEL_PARAMS_URI) as fp:
+    MODEL_PARAMS = json.load(fp)
+MAX_LENGTH = MODEL_PARAMS["smiles_padding_length"]
+# load SMILES language
+with open(SMILES_LANGUAGE_URI, "rb") as fp:
+    SMILES_LANGUAGE = dill.load(fp)
+# load gene expression
+GENE_EXPRESSION = pd.read_csv(GENE_EXPRESSION_URI, compression="zip", low_memory=False)
+# load genes
+with open(GENES_URI, "rb") as fp:
+    GENES = dill.load(fp)
+# load gene standardization parameters
+with open(GENE_EXPRESSION_STANDARDIZATION_URI, "rb") as fp:
+    GENE_STANDARDIZATION_PARAMETERS = dill.load(fp)
+# smiles transformations
+SMILES_TRANSFORMS = [
+    SMILESToTokenIndexes(smiles_language=SMILES_LANGUAGE),
+    LeftPadding(padding_length=MAX_LENGTH, padding_index=SMILES_LANGUAGE.padding_index),
+]
+SMILES_TOKENIZE_FN = Compose(SMILES_TRANSFORMS)
+# prepare default gene expression data
+# NOTE: transpose and reset work around to ensure we have all needed genes
+GENE_EXPRESSION_DATA = GENE_EXPRESSION.T.reindex(GENES).fillna(0.0).T.values
+# NOTE: sub-selecting exisiting columns to remove all the genes
+to_drop = list(set(GENES) & set(GENE_EXPRESSION.columns))
+GENE_EXPRESSION_METADATA = GENE_EXPRESSION.drop(to_drop, axis=1)
+del GENE_EXPRESSION
+# housekeeping
+RESULTS_EXPIRATION_SECONDS = float(
+    os.environ.get(
+        "PACCMANN_RESULTS_EXPIRATION_SECONDS",
+        # every week
+        60 * 60 * 24 * 7,
+    )
+)
+# SMILES parameters
+# TODO: think whether we should enforce canonicalization
+CANON = {
+    "canonical": MODEL_PARAMS["canonical"],
+    "kekulize": MODEL_PARAMS["kekulize"],
+    "all_bonds_explicit": MODEL_PARAMS["all_bonds_explicit"],
+    "all_hs_explicit": MODEL_PARAMS["all_hs_explicit"],
+    "randomize": MODEL_PARAMS["randomize"],
+    "remove_bonddir": MODEL_PARAMS["remove_bonddir"],
+    "smiles_maximum_length": MODEL_PARAMS["smiles_padding_length"],
+}

cos.py

@@ -0,0 +1,155 @@
+"""COS utitities."""
+import logging
+import os
+import tempfile
+from io import BufferedReader
+from typing import List, Optional, Tuple
+from urllib.parse import urlparse
+
+import boto3
+from boto3_type_annotations.s3 import Bucket
+from botocore.client import Config
+
+logger = logging.getLogger(__name__)
+
+
+def connect_bucket(s3_uri: str) -> Tuple[Bucket, List[str]]:
+    parsed_uri = urlparse(s3_uri)
+    # parse bucket and path, where path can be empty list
+    _, bucket_name, *split_key = parsed_uri.path.split("/")
+    # parsing credentials and host
+    credentials, host = parsed_uri.netloc.split("@")
+    # getting keys
+    access, secret = credentials.split(":")
+    # establish connection
+    connection = boto3.resource(
+        "s3",
+        endpoint_url="http://{}".format(host),
+        aws_access_key_id=access,
+        aws_secret_access_key=secret,
+        config=Config(signature_version="s3v4"),
+        region_name="us-east-1",
+    )
+    return connection.Bucket(bucket_name), split_key
+
+
+def ensure_filepath_from_uri(file_uri: str) -> str:
+    """
+    Get a file on the local storage.
+    In case the file_uri provided is a S3 URI, dowloads the
+    file and return the local path.
+    Args:
+        file_uri (str): a uri, either filesystem or S3.
+    Returns:
+        str: the path to the file on the local filesystem.
+    """
+    if file_uri.startswith("s3://"):
+        try:
+            bucket, split_key = connect_bucket(file_uri)
+            path = os.path.join(*split_key)
+            # create a file handle for storing the file locally
+            a_file = tempfile.NamedTemporaryFile(delete=False)
+            # make sure we close the file
+            a_file.close()
+            # download the file
+            bucket.download_file(path, a_file.name)
+            return a_file.name
+        except Exception:
+            message = "Getting file from COS failed " "for the provided URI: {}".format(
+                file_uri
+            )
+            logger.exception(message)
+            raise RuntimeError(message)
+    else:
+        logger.debug(f"Searching for {file_uri}")
+        if os.path.exists(file_uri):
+            return file_uri
+        else:
+            message = "File not found on local filesystem."
+            logger.error(message)
+            raise RuntimeError(message)
+
+
+# COS configuration
+COS_BUCKET_URI = os.environ.get(
+    "COS_BUCKET_URI", os.path.join(os.getcwd(), "artifacts")
+)
+COS_UPLOAD_POLICY = os.environ.get("COS_UPLOAD_POLICY", "public-read-write")
+# results prefix
+RESULTS_PREFIX = "results"
+
+
+def download_from_key(key: str, file_path: Optional[str] = None) -> None:
+    """Download a single file from COS.
+    If no file_path is given, object name is taken as relative local path.
+    Args:
+        key (str): S3 key.
+        file_path (str, optional): Path of downloaded file. Defaults to None.
+    """
+    file_path = key if file_path is None else file_path
+    os.makedirs(os.path.dirname(file_path), exist_ok=True)
+    BUCKET.download_file(key, file_path)
+
+
+def upload_to_key(file_path: str, key: str) -> None:
+    """Upload local file to COS.
+    Args:
+        file_path (str): Local filepath.
+        key (str): S3 key.
+    """
+    BUCKET.upload_file(file_path, key)
+
+
+def fileobject_to_key(readable_binary: BufferedReader, key: str) -> None:
+    """Upload readable, binary file from handle to COS.
+    Args:
+        readable_binary (BufferedReader): filehandle, e.g. opened in 'rb' mode.
+        key (str): S3 key.
+    """
+    BUCKET.upload_fileobj(readable_binary, key)
+
+
+def delete_from_key(key_or_prefix: str) -> None:
+    """Delete all files matching given prefix from COS.
+    Args:
+        key_or_prefix (str): S3 uri including object name prefix.
+    """
+    BUCKET.objects.filter(Prefix=key_or_prefix).delete()
+
+
+def string_to_key(string: str, key: str) -> None:
+    """Upload string as object to COS.
+    Args:
+        string (str): object to be stored.
+        key (str): S3 key.
+    """
+    BUCKET.put_object(Key=key, Body=string.encode())
+
+
+def bytes_to_key(some_bytes: bytes, key: str) -> None:
+    """Upload bytes as object to COS.
+    Args:
+        some_bytes (bytes): object to be stored.
+        key (str): S3 key.
+    """
+    BUCKET.put_object(Key=key, Body=some_bytes)
+
+
+def string_from_key(key: str) -> str:
+    """Get object from COS as string.
+    Args:
+        key (str): S3 key.
+    Returns:
+        str: object.
+    """
+    return BUCKET.Object(key).get()["Body"].read().decode("utf-8")
+
+
+def bytes_from_key(key: str) -> bytes:
+    """Get object from COS as bytes.
+    Args:
+        key (str): S3 key.
+    Returns:
+        bytes: object.
+    """
+    return BUCKET.Object(key).get()["Body"].read()

forward.py

@@ -0,0 +1,56 @@
+"""Inference utilities."""
+import logging
+import torch
+import numpy as np
+from paccmann_predictor.models.paccmann import MCA
+from pytoda.transforms import Compose
+from pytoda.smiles.transforms import ToTensor
+from configuration import (
+    MODEL_WEIGHTS_URI,
+    MODEL_PARAMS,
+    SMILES_LANGUAGE,
+    SMILES_TRANSFORMS,
+)
+
+logger = logging.getLogger("openapi_server:inference")
+# NOTE: to avoid segfaults
+torch.set_num_threads(1)
+
+
+def predict(
+    smiles: str, gene_expression: np.ndarray, estimate_confidence: bool = False
+) -> dict:
+    """
+    Run PaccMann prediction.
+
+    Args:
+        smiles (str): SMILES representing a compound.
+        gene_expression (np.ndarray): gene expression data.
+        estimate_confidence (bool, optional): estimate confidence of the
+            prediction. Defaults to False.
+    Returns:
+        dict: the prediction dictionaty from the model.
+    """
+    logger.debug("running predict.")
+    logger.debug("gene expression shape: {}.".format(gene_expression.shape))
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    logger.debug("device selected: {}.".format(device))
+    logger.debug("loading model for prediction.")
+    model = MCA(MODEL_PARAMS)
+    model.load_state_dict(torch.load(MODEL_WEIGHTS_URI, map_location=device))
+    model.eval()
+    if estimate_confidence:
+        logger.debug("associating SMILES language for confidence estimates.")
+        model._associate_language(SMILES_LANGUAGE)
+    logger.debug("model loaded.")
+    logger.debug("set up the transformation.")
+    smiles_transform_fn = Compose(SMILES_TRANSFORMS + [ToTensor(device=device)])
+    logger.debug("starting the prediction.")
+    with torch.no_grad():
+        _, prediction_dict = model(
+            smiles_transform_fn(smiles).view(1, -1).repeat(gene_expression.shape[0], 1),
+            torch.tensor(gene_expression).float(),
+            confidence=estimate_confidence,
+        )
+    logger.debug("successful prediction.")
+    return prediction_dict

plots.py

@@ -0,0 +1,86 @@
+"""Plotting utilities."""
+import numpy as np
+from typing import Tuple
+from bokeh.layouts import column
+from bokeh.models import CustomJS, Slider
+from bokeh.plotting import figure, Figure, ColumnDataSource
+from bokeh.embed import components
+
+
+def barplot(attended: np.ndarray, weights: np.ndarray) -> Figure:
+    """
+    Bokeh barplot showing top k attention weights.
+
+    k is interactively changable via a slider.
+
+    Args:
+        attended (np.ndarray): Names of the attended entities
+        weights (np.ndarray): Attention weights
+
+    Returns:
+        bokeh.plotting.Figure: Can be visualized for debugging,
+            via bokeh.plotting (i.e. output_file, show)
+    """
+    K = 4
+    # reset from slider callback
+    source = ColumnDataSource(
+        data=dict(attended=attended, weights=weights),
+    )
+    top_k_slider = Slider(start=1, end=len(attended), value=K, step=1, title="k")
+    p = figure(
+        x_range=source.data["attended"][:K],  # adapted by callback
+        plot_height=350,
+        title="Top k Gene Attention Weights",
+        toolbar_location="below",
+        tools="pan,wheel_zoom,box_zoom,save,reset",
+    )
+    p.vbar(x="attended", top="weights", source=source, width=0.9)
+    # define the callback
+    callback = CustomJS(
+        args=dict(
+            source=source,
+            xrange=p.x_range,
+            yrange=p.y_range,
+            attended=attended,
+            weights=weights,
+            top_k=top_k_slider,
+        ),
+        code="""
+        var data = source.data;
+        const k = top_k.value;
+
+        data['attended'] = attended.slice(0, k)
+        data['weights'] = weights.slice(0, k)
+
+        source.change.emit();
+
+        // not need if data is in descending order
+        var yrange_arr = data['weights'];
+        var yrange_max = Math.max(...yrange_arr) * 1.05;
+        yrange.end = yrange_max;
+
+        xrange.factors = data['attended'];
+
+        source.change.emit();
+    """,
+    )
+    top_k_slider.js_on_change("value", callback)
+    layout = column(top_k_slider, p)
+    p.xgrid.grid_line_color = None
+    p.y_range.start = 0
+    return layout
+
+
+def embed_barplot(attended: np.ndarray, weights: np.ndarray) -> Tuple[str, str]:
+    """Bokeh barplot showing top k attention weights.
+    k is interactively changable via a slider.
+
+
+    Args:
+        attended (np.ndarray): Names of the attended entities
+        weights (np.ndarray): Attention weights
+
+    Returns:
+        Tuple[str, str]: javascript and html
+    """
+    return components(barplot(attended, weights))

requirements.txt

@@ -1,30 +1,20 @@
--f https://download.pytorch.org/whl/cpu/torch_stable.html
--f https://data.pyg.org/whl/torch-1.12.1+cpu.html
-# pip==20.2.4
-torch==1.12.1
-torch-scatter
-torch-spline-conv
-torch-sparse
-torch-geometric
-torchvision==0.13.1
-torchaudio==0.12.1
-gt4sd>=1.1.6
-diffusers==0.6.0
-molgx>=0.22.0a1
-molecule_generation
-nglview
-PyTDC==0.3.7
-gradio==3.12.0
-markdown-it-py>=2.1.0
-mols2grid>=0.2.0
-numpy==1.23.5
-pandas>=1.0.0
-terminator @ git+https://github.com/IBM/regression-transformer@gt4sd
-guacamol_baselines @ git+https://github.com/GT4SD/guacamol_baselines.git@v0.0.2
-moses @ git+https://github.com/GT4SD/moses.git@v0.1.0
-paccmann_chemistry @ git+https://github.com/PaccMann/paccmann_chemistry@0.0.4
-paccmann_generator @ git+https://github.com/PaccMann/paccmann_generator@0.0.2
-paccmann_gp @ git+https://github.com/PaccMann/paccmann_gp@0.1.1
-paccmann_omics @ git+https://github.com/PaccMann/paccmann_omics@0.0.1.1
-paccmann_predictor @ git+https://github.com/PaccMann/paccmann_predictor@sarscov2
-reinvent_models @ git+https://github.com/GT4SD/reinvent_models@v0.0.1
+rdkit-pypi
+pytoda @git+https://git@github.com/PaccMann/paccmann_datasets@0.0.3
+paccmann_predictor @ git+https://github.com/PaccMann/paccmann_predictor@0.0.1.1
+tqdm
+connexion==2.6.0
+swagger-ui-bundle==0.0.2
+python_dateutil==2.6.0
+setuptools>=21.0.0
+numpy>=1.14.3
+scikit-learn==0.21.3
+pandas==0.24.1
+torch>=1.3.0
+matplotlib>=2.2.2
+seaborn>=0.9.0
+boto3==1.11.16
+boto3_type_annotations==0.3.1
+gunicorn==20.0.4
+regex==2020.1.8
+bokeh==1.4.0
+importlib_resources

smiles.py

@@ -0,0 +1,211 @@
+"""SMILES utilities."""
+import os
+import regex
+import logging
+import matplotlib
+import matplotlib as mpl
+import matplotlib.cm as cm
+import matplotlib.pyplot as plt
+from io import StringIO
+from operator import itemgetter
+from typing import Callable, Iterable, Tuple
+from matplotlib.ticker import FormatStrFormatter, ScalarFormatter
+from rdkit import Chem
+from rdkit.Chem.Draw import rdMolDraw2D
+from configuration import SMILES_LANGUAGE, SMILES_TOKENIZE_FN
+
+logger = logging.getLogger(__name__)
+# NOTE: avoid segfaults in matplotlib
+matplotlib.use("Agg")
+
+MOLECULE_TOKENS = set(SMILES_LANGUAGE.token_to_index.keys())
+NON_ATOM_REGEX = regex.compile(r"^(\d|\%\d+|\p{P}+|\p{Math}+)$")
+NON_ATOM_TOKENS = set(
+    [token for token in MOLECULE_TOKENS if NON_ATOM_REGEX.match(token)]
+)
+CMAP = cm.Oranges
+COLOR_NORMALIZERS = {"linear": mpl.colors.Normalize, "logarithmic": mpl.colors.LogNorm}
+ATOM_RADII = float(os.environ.get("PACCMANN_ATOM_RADII", 0.5))
+SVG_WIDTH = int(os.environ.get("PACCMANN_SVG_WIDTH", 400))
+SVG_HEIGHT = int(os.environ.get("PACCMANN_SVG_HEIGHT", 200))
+COLOR_NORMALIZATION = os.environ.get("PACCMANN_COLOR_NORMALIZATION", "logarithmic")
+
+
+def validate_smiles(smiles: str) -> bool:
+    """
+    Validate a SMILES.
+
+    Args:
+        smiles (str): a SMILES string.
+
+    Returns:
+        bool: flag indicating whether the SMILES is a valid molecule.
+    """
+    molecule = Chem.MolFromSmiles(smiles)
+    return not (molecule is None)
+
+
+def canonicalize_smiles(smiles: str) -> str:
+    """
+    Canonicalize a SMILES.
+
+    Args:
+        smiles (str): a SMILES string.
+
+    Returns:
+        str: the canonicalized SMILES.
+    """
+    molecule = Chem.MolFromSmiles(smiles)
+    return Chem.MolToSmiles(molecule)
+
+
+def remove_housekeeping_from_tokens_and_smiles_attention(
+    tokens: Iterable[str], smiles_attention: Iterable[float]
+) -> Tuple[Iterable[str], Iterable[float]]:
+    """
+    Remove housekeeping tokens and corresponding attention weights.
+
+    Args:
+        tokens (Iterable[str]): tokens obtained from the SMILES.
+        smiles_attention (Iterable[float]): SMILES attention.
+
+    Returns:
+        Tuple[Iterable[str], Iterable[float]]: a tuple containing the filtered
+            tokens and attention values.
+    """
+    to_keep = [index for index, token in enumerate(tokens) if token in MOLECULE_TOKENS]
+    return (
+        list(itemgetter(*to_keep)(tokens)),
+        list(itemgetter(*to_keep)(smiles_attention)),
+    )
+
+
+def _get_index_and_colors(
+    values: Iterable[float],
+    tokens: Iterable[str],
+    predicate: Callable[[tuple], bool],
+    color_mapper: cm.ScalarMappable,
+) -> Tuple[Iterable[int], Iterable[tuple]]:
+    """
+    Get index and RGB colors from a color map using a rule.
+
+    Args:
+        values (Iterable[float]): values associated to tokens.
+        tokens (Iterable[str]): tokens.
+        predicate (Callable[[tuple], bool]): a predicate that acts on a tuple
+            of (value, object).
+        color_mapper (cm.ScalarMappable): a color mapper.
+
+    Returns:
+        Tuple[Iterable[int], Iterable[tuple]]: tuple with indexes and RGB
+            colors associated to the given index.
+    """
+    indices = []
+    colors = {}
+    for index, value in enumerate(
+        map(lambda t: t[0], filter(lambda t: predicate(t), zip(values, tokens)))
+    ):
+        indices.append(index)
+        colors[index] = color_mapper.to_rgba(value)
+    return indices, colors
+
+
+def smiles_attention_to_svg(
+    smiles: str, smiles_attention: Iterable[float]
+) -> Tuple[str, str]:
+    """
+    Generate an svg of the molecule highlighiting SMILES attention.
+
+    Args:
+        smiles (str): SMILES representing a molecule.
+        smiles_attention (Iterable[float]): SMILES attention.
+
+    Returns:
+        Tuple[str, str]: drawing, colorbar
+            the svg of the molecule highlighiting SMILES attention
+            and the svg displaying the colorbar
+    """
+    # remove padding
+    logger.debug("SMILES attention:\n{}.".format(smiles_attention))
+    logger.debug(
+        "SMILES attention range: [{},{}].".format(
+            min(smiles_attention), max(smiles_attention)
+        )
+    )
+    # get the molecule
+    molecule = Chem.MolFromSmiles(smiles)
+    tokens = [
+        SMILES_LANGUAGE.index_to_token[token_index]
+        for token_index in SMILES_TOKENIZE_FN(smiles)
+    ]
+    logger.debug("SMILES tokens:{}.".format(tokens))
+    tokens, smiles_attention = remove_housekeeping_from_tokens_and_smiles_attention(
+        tokens, smiles_attention
+    )  # yapf:disable
+    logger.debug(
+        "tokens and SMILES attention after removal:\n{}\n{}.".format(
+            tokens, smiles_attention
+        )
+    )
+    logger.debug(
+        "SMILES attention range after padding removal: [{},{}].".format(
+            min(smiles_attention), max(smiles_attention)
+        )
+    )
+    # define a color map
+    normalize = COLOR_NORMALIZERS.get(COLOR_NORMALIZATION, mpl.colors.LogNorm)(
+        vmin=min(smiles_attention), vmax=min(1.0, 2 * max(smiles_attention))
+    )
+    color_mapper = cm.ScalarMappable(norm=normalize, cmap=CMAP)
+    # get atom colors
+    highlight_atoms, highlight_atom_colors = _get_index_and_colors(
+        smiles_attention, tokens, lambda t: t[1] not in NON_ATOM_TOKENS, color_mapper
+    )
+    logger.debug("atom colors:\n{}.".format(highlight_atom_colors))
+    # get bond colors
+    highlight_bonds, highlight_bond_colors = _get_index_and_colors(
+        smiles_attention, tokens, lambda t: t[1] in NON_ATOM_TOKENS, color_mapper
+    )
+    logger.debug("bond colors:\n{}.".format(highlight_bond_colors))
+    # add coordinates
+    logger.debug("compute 2D coordinates")
+    Chem.rdDepictor.Compute2DCoords(molecule)
+    # draw the molecule
+    logger.debug("get a drawer")
+    drawer = rdMolDraw2D.MolDraw2DSVG(SVG_WIDTH, SVG_HEIGHT)
+    logger.debug("draw the molecule")
+    drawer.DrawMolecule(
+        molecule,
+        highlightAtoms=highlight_atoms,
+        highlightAtomColors=highlight_atom_colors,
+        highlightBonds=highlight_bonds,
+        highlightBondColors=highlight_bond_colors,
+        highlightAtomRadii={index: ATOM_RADII for index in highlight_atoms},
+    )
+    logger.debug("finish drawing")
+    drawer.FinishDrawing()
+    # the drawn molecule as str
+    logger.debug("drawing to string")
+    drawing = drawer.GetDrawingText().replace("\n", " ")
+    # the respective colorbar
+    logger.debug("draw the colorbar")
+    fig, ax = plt.subplots(figsize=(0.5, 6))
+    mpl.colorbar.ColorbarBase(
+        ax,
+        cmap=CMAP,
+        norm=normalize,
+        orientation="vertical",
+        extend="both",
+        extendrect=True,
+    )
+    # instead of LogFormatterSciNotation
+    logger.debug("format the colorbar")
+    ax.yaxis.set_minor_formatter(ScalarFormatter())
+    ax.yaxis.set_major_formatter(FormatStrFormatter("%.2f"))  # fixes 0.1, 0.20
+    # the colorbar svg as str
+    logger.debug("colorbar to string")
+    file_like = StringIO()
+    plt.savefig(file_like, format="svg", bbox_inches="tight")
+    colorbar = file_like.getvalue().replace("\n", " ")
+    plt.close(fig)
+    return drawing, colorbar

submission.py

@@ -0,0 +1,124 @@
+"""Submission-related utilities."""
+import os
+import json
+import logging
+import numpy as np
+import pandas as pd
+from io import StringIO
+from typing import Optional
+from sklearn.preprocessing import StandardScaler
+from configuration import (
+    GENE_EXPRESSION_DATA,
+    GENE_EXPRESSION_METADATA,
+    GENES,
+    GENE_STANDARDIZATION_PARAMETERS,
+)
+from cos import RESULTS_PREFIX, string_to_key
+from forward import predict
+
+# from attention import upload_attention
+
+logger = logging.getLogger("openapi_server:submission")
+
+
+def submission(
+    drug: dict,
+    workspace_id: str,
+    task_id: str,
+    estimate_confidence: bool = False,
+    omics_file: Optional[str] = None,
+) -> None:
+    """
+    Submit PaccMann prediction
+
+    Args:
+        drug (dict): drug to analyse in dictionary format.
+        workspace_id (str): workspace identifier for the submission.
+        task_id (str): task identifier.
+        estimate_confidence (bool, optional): estimate confidence of the
+            prediction. Defaults to False.
+        omics_file (Optional[str], optional): binary string containing
+            expression data. Defaults to None.
+    """
+    prefix = os.path.join(RESULTS_PREFIX, workspace_id, task_id)
+    logger.debug("processing omic data.")
+    # NOTE: this trick is used in case a single example is passed
+    single_example = False
+    result = {}
+    if omics_file is None:
+        gene_expression, gene_expression_metadata = (
+            GENE_EXPRESSION_DATA,
+            GENE_EXPRESSION_METADATA,
+        )
+    else:
+        logger.debug("parsing uploaded omic data.")
+        logger.debug(omics_file)
+        gene_expression_df = pd.read_csv(omics_file, low_memory=False)
+        logger.debug(gene_expression_df.columns)
+        to_drop = list(set(GENES) & set(gene_expression_df.columns))
+        gene_expression_data, gene_expression_metadata = (
+            gene_expression_df.T.reindex(GENES).fillna(0.0).T,
+            gene_expression_df.drop(to_drop, axis=1),
+        )
+        logger.debug("peek parsed expression and metadata.")
+        logger.debug("gene_expression_data:\n{}".format(gene_expression_data.head()))
+        logger.debug(
+            "gene_expression_metadata:\n{}".format(gene_expression_metadata.head())
+        )
+        if gene_expression_data.shape[0] < 2:
+            logger.debug(
+                "single example, standardizing with default parameters:\n{}".format(
+                    GENE_STANDARDIZATION_PARAMETERS
+                )
+            )
+            single_example = True
+            gene_expression = (
+                gene_expression_data.values - GENE_STANDARDIZATION_PARAMETERS[0]
+            ) / GENE_STANDARDIZATION_PARAMETERS[1]
+            gene_expression = np.vstack(2 * [gene_expression])
+            logger.debug(gene_expression.shape)
+        else:
+            gene_expression = StandardScaler().fit_transform(
+                gene_expression_data.values
+            )
+        logger.debug("gene_expression:\n{}".format(gene_expression[:10]))
+    logger.debug("omic data prepared if present.")
+    prediction_dict = predict(
+        smiles=drug["smiles"],
+        gene_expression=gene_expression,
+        estimate_confidence=estimate_confidence,
+    )
+    # from tensors
+    for key, value in prediction_dict.items():
+        prediction_dict[key] = value.numpy()[:1] if single_example else value.numpy()
+
+    result.update(prediction_dict)
+    # merge for single table, index is unique identifier for samples.
+    gene_expression_metadata["IC50 (min/max scaled)"] = prediction_dict["IC50"]
+    gene_expression_metadata["IC50 (log(μmol))"] = prediction_dict[
+        "log_micromolar_IC50"
+    ]
+    if estimate_confidence:
+        gene_expression_metadata["epistemic_confidence"] = prediction_dict[
+            "epistemic_confidence"
+        ]
+        gene_expression_metadata["aleatoric_confidence"] = prediction_dict[
+            "aleatoric_confidence"
+        ]
+    logger.debug("uploaded predicted sensitivity table including metadata.")
+    # attention
+    # result.update(
+    #     upload_attention(
+    #         prefix,
+    #         sample_names=list(map(str, gene_expression_metadata.index)),
+    #         omic_attention=prediction_dict["gene_attention"],
+    #         smiles_attention=prediction_dict["smiles_attention"],
+    #     )
+    # )
+    logger.debug("uploaded attention for each sample.")
+    logger.debug("uploading drug information and sensitivity.")
+    # prediction (is sensitivity_json in API)
+    logger.debug("uploaded drug information and sensitivity.")
+
+    # NOTE: Ordering corresponds to IDs in GEP metadata!
+    return result

utils.py

@@ -1,76 +1,325 @@
-import logging
-from collections import defaultdict
-from typing import List, Callable
-from gt4sd.properties import PropertyPredictorRegistry
-from gt4sd.algorithms.prediction.paccmann.core import PaccMann, AffinityPredictor
-import torch
-
-import mols2grid
-import pandas as pd
-
-logger = logging.getLogger(__name__)
-logger.addHandler(logging.NullHandler())
-
-
-def get_affinity_function(target: str) -> Callable:
-    return lambda mols: torch.stack(
-        list(
-            PaccMann(
-                AffinityPredictor(protein_targets=[target] * len(mols), ligands=mols)
-            ).sample(len(mols))
-        )
-    ).tolist()
-
-
-EVAL_DICT = {
-    "qed": PropertyPredictorRegistry.get_property_predictor("qed"),
-    "sa": PropertyPredictorRegistry.get_property_predictor("sas"),
-}
-
-
-def draw_grid_generate(
-    samples: List[str],
-    properties: List[str],
-    protein_target: str,
-    n_cols: int = 3,
-    size=(140, 200),
-) -> str:
+# coding: utf-8
+
+from __future__ import absolute_import
+
+import datetime
+import pprint
+import sys
+import typing
+from datetime import datetime  # noqa: F401
+from typing import Dict, List  # noqa: F401
+
+import six
+
+if sys.version_info < (3, 7):
+    import typing
+
+    def is_generic(klass):
+        """Determine whether klass is a generic class"""
+        return type(klass) == typing.GenericMeta
+
+    def is_dict(klass):
+        """Determine whether klass is a Dict"""
+        return klass.__extra__ == dict
+
+    def is_list(klass):
+        """Determine whether klass is a List"""
+        return klass.__extra__ == list
+
+else:
+
+    def is_generic(klass):
+        """Determine whether klass is a generic class"""
+        return hasattr(klass, "__origin__")
+
+    def is_dict(klass):
+        """Determine whether klass is a Dict"""
+        return klass.__origin__ == dict
+
+    def is_list(klass):
+        """Determine whether klass is a List"""
+        return klass.__origin__ == list
+
+
+def _deserialize(data, klass):
+    """Deserializes dict, list, str into an object.
+
+    :param data: dict, list or str.
+    :param klass: class literal, or string of class name.
+
+    :return: object.
+    """
+    if data is None:
+        return None
+
+    if klass in six.integer_types or klass in (float, str, bool, bytearray):
+        return _deserialize_primitive(data, klass)
+    elif klass == object:
+        return _deserialize_object(data)
+    elif klass == datetime.date:
+        return deserialize_date(data)
+    elif klass == datetime.datetime:
+        return deserialize_datetime(data)
+    elif typing_utils.is_generic(klass):
+        if typing_utils.is_list(klass):
+            return _deserialize_list(data, klass.__args__[0])
+        if typing_utils.is_dict(klass):
+            return _deserialize_dict(data, klass.__args__[1])
+    else:
+        return deserialize_model(data, klass)
+
+
+def _deserialize_primitive(data, klass):
+    """Deserializes to primitive type.
+
+    :param data: data to deserialize.
+    :param klass: class literal.
+
+    :return: int, long, float, str, bool.
+    :rtype: int | long | float | str | bool
+    """
+    try:
+        value = klass(data)
+    except UnicodeEncodeError:
+        value = six.u(data)
+    except TypeError:
+        value = data
+    return value
+
+
+def _deserialize_object(value):
+    """Return an original value.
+
+    :return: object.
+    """
+    return value
+
+
+def deserialize_date(string):
+    """Deserializes string to date.
+
+    :param string: str.
+    :type string: str
+    :return: date.
+    :rtype: date
+    """
+    try:
+        from dateutil.parser import parse
+
+        return parse(string).date()
+    except ImportError:
+        return string
+
+
+def deserialize_datetime(string):
+    """Deserializes string to datetime.
+
+    The string should be in iso8601 datetime format.
+
+    :param string: str.
+    :type string: str
+    :return: datetime.
+    :rtype: datetime
+    """
+    try:
+        from dateutil.parser import parse
+
+        return parse(string)
+    except ImportError:
+        return string
+
+
+def deserialize_model(data, klass):
+    """Deserializes list or dict to model.
+
+    :param data: dict, list.
+    :type data: dict | list
+    :param klass: class literal.
+    :return: model object.
+    """
+    instance = klass()
+
+    if not instance.openapi_types:
+        return data
+
+    for attr, attr_type in six.iteritems(instance.openapi_types):
+        if (
+            data is not None
+            and instance.attribute_map[attr] in data
+            and isinstance(data, (list, dict))
+        ):
+            value = data[instance.attribute_map[attr]]
+            setattr(instance, attr, _deserialize(value, attr_type))
+
+    return instance
+
+
+def _deserialize_list(data, boxed_type):
+    """Deserializes a list and its elements.
+
+    :param data: list to deserialize.
+    :type data: list
+    :param boxed_type: class literal.
+
+    :return: deserialized list.
+    :rtype: list
     """
-    Uses mols2grid to draw a HTML grid for the generated molecules
+    return [_deserialize(sub_data, boxed_type) for sub_data in data]
+
+
+def _deserialize_dict(data, boxed_type):
+    """Deserializes a dict and its elements.
+
+    :param data: dict to deserialize.
+    :type data: dict
+    :param boxed_type: class literal.
+
+    :return: deserialized dict.
+    :rtype: dict
+    """
+    return {k: _deserialize(v, boxed_type) for k, v in six.iteritems(data)}
+
+
+T = typing.TypeVar("T")
+
+
+class Model(object):
+    # openapiTypes: The key is attribute name and the
+    # value is attribute type.
+    openapi_types = {}
+
+    # attributeMap: The key is attribute name and the
+    # value is json key in definition.
+    attribute_map = {}
+
+    @classmethod
+    def from_dict(cls: typing.Type[T], dikt) -> T:
+        """Returns the dict as a model"""
+        return util.deserialize_model(dikt, cls)
+
+    def to_dict(self):
+        """Returns the model properties as a dict
+
+        :rtype: dict
+        """
+        result = {}
+
+        for attr, _ in six.iteritems(self.openapi_types):
+            value = getattr(self, attr)
+            if isinstance(value, list):
+                result[attr] = list(
+                    map(lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value)
+                )
+            elif hasattr(value, "to_dict"):
+                result[attr] = value.to_dict()
+            elif isinstance(value, dict):
+                result[attr] = dict(
+                    map(
+                        lambda item: (item[0], item[1].to_dict())
+                        if hasattr(item[1], "to_dict")
+                        else item,
+                        value.items(),
+                    )
+                )
+            else:
+                result[attr] = value
+
+        return result
+
+    def to_str(self):
+        """Returns the string representation of the model
+
+        :rtype: str
+        """
+        return pprint.pformat(self.to_dict())
+
+    def __repr__(self):
+        """For `print` and `pprint`"""
+        return self.to_str()
 
-    Args:
-        samples: The generated samples.
-        n_cols: Number of columns in grid. Defaults to 5.
-        size: Size of molecule in grid. Defaults to (140, 200).
+    def __eq__(self, other):
+        """Returns true if both objects are equal"""
+        return self.__dict__ == other.__dict__
 
-    Returns:
-        HTML to display
+    def __ne__(self, other):
+        """Returns true if both objects are not equal"""
+        return not self == other
+
+
+class Drug(Model):
+    """NOTE: This class is auto generated by OpenAPI Generator (https://openapi-generator.tech).
+
+    Do not edit the class manually.
     """
 
-    if protein_target != "":
-        EVAL_DICT.update({"affinity": get_affinity_function(protein_target)})
-
-    result = defaultdict(list)
-    result.update(
-        {"SMILES": samples, "Name": [f"Generated_{i}" for i in range(len(samples))]},
-    )
-    if "affinity" in properties:
-        properties.remove("affinity")
-        vals = EVAL_DICT["affinity"](samples)
-        result["affinity"] = vals
-    # Fill properties
-    for sample in samples:
-        for prop in properties:
-            value = EVAL_DICT[prop](sample)
-            result[prop].append(f"{prop} = {value}")
-
-    result_df = pd.DataFrame(result)
-    obj = mols2grid.display(
-        result_df,
-        tooltip=list(result.keys()),
-        height=1100,
-        n_cols=n_cols,
-        name="Results",
-        size=size,
-    )
-    return obj.data
+    def __init__(self, smiles=None, name=None):  # noqa: E501
+        """Drug - a model defined in OpenAPI
+
+        :param smiles: The smiles of this Drug.  # noqa: E501
+        :type smiles: str
+        :param name: The name of this Drug.  # noqa: E501
+        :type name: str
+        """
+        self.openapi_types = {"smiles": str, "name": str}
+
+        self.attribute_map = {"smiles": "smiles", "name": "name"}
+
+        self._smiles = smiles
+        self._name = name
+
+    @classmethod
+    def from_dict(cls, dikt) -> "Drug":
+        """Returns the dict as a model
+
+        :param dikt: A dict.
+        :type: dict
+        :return: The Drug of this Drug.  # noqa: E501
+        :rtype: Drug
+        """
+        return util.deserialize_model(dikt, cls)
+
+    @property
+    def smiles(self):
+        """Gets the smiles of this Drug.
+
+
+        :return: The smiles of this Drug.
+        :rtype: str
+        """
+        return self._smiles
+
+    @smiles.setter
+    def smiles(self, smiles):
+        """Sets the smiles of this Drug.
+
+
+        :param smiles: The smiles of this Drug.
+        :type smiles: str
+        """
+        if smiles is None:
+            raise ValueError(
+                "Invalid value for `smiles`, must not be `None`"
+            )  # noqa: E501
+
+        self._smiles = smiles
+
+    @property
+    def name(self):
+        """Gets the name of this Drug.
+
+
+        :return: The name of this Drug.
+        :rtype: str
+        """
+        return self._name
+
+    @name.setter
+    def name(self, name):
+        """Sets the name of this Drug.
+
+
+        :param name: The name of this Drug.
+        :type name: str
+        """
+
+        self._name = name