metadata
license: mit
library_name: sklearn
tags:
- sklearn
- skops
- tabular-regression
model_format: pickle
model_file: MLR-model.pkl
widget:
- structuredData:
CAS:
- 696-71-9
- 94-02-0
- 15128-82-2
CID:
- 12766
- 7170
- 27057
CanonicalSMILES:
- canonical: OC1CCCCCCC1
original: C1CCCC(CCC1)O
- canonical: CCOC(=O)CC(=O)c1ccccc1
original: CCOC(=O)CC(=O)C1=CC=CC=C1
- canonical: O=[N+]([O-])c1ncccc1O
original: C1=CC(=C(N=C1)[N+](=O)[O-])O
Cor1-C420 Adduct (M+H):
- no Adduct
- no Adduct
- no Adduct
Cor1-C420 Depletion 24 h (%):
- 1
- 1
- 1
Cor1-C420 Dimer (%):
- 2
- 5
- 4
Cor1-C420 Kmax (1/mM/min):
- 0.000006979399898264935
- 0.000006979399898264935
- 0.000006979399898264935
DPRA Cysteine depletion (%):
- .nan
- 11.2
- .nan
DPRA Lysine depletion (%):
- .nan
- 0.9
- .nan
InChI:
- InChI=1S/C8H16O/c9-8-6-4-2-1-3-5-7-8/h8-9H,1-7H2
- InChI=1S/C11H12O3/c1-2-14-11(13)8-10(12)9-6-4-3-5-7-9/h3-7H,2,8H2,1H3
- InChI=1S/C5H4N2O3/c8-4-2-1-3-6-5(4)7(9)10/h1-3,8H
InChIKey:
- FHADSMKORVFYOS-UHFFFAOYSA-N
- GKKZMYDNDDMXSE-UHFFFAOYSA-N
- QBPDSKPWYWIHGA-UHFFFAOYSA-N
IsomericSMILES:
- canonical: OC1CCCCCCC1
original: C1CCCC(CCC1)O
- canonical: CCOC(=O)CC(=O)c1ccccc1
original: CCOC(=O)CC(=O)C1=CC=CC=C1
- canonical: O=[N+]([O-])c1ncccc1O
original: C1=CC(=C(N=C1)[N+](=O)[O-])O
KeratinoSens EC1.5 (uM):
- 249.6822169
- 62.9764329
- 4000
KeratinoSens EC3 (uM):
- 4000
- 689
- 4000
KeratinoSens IC50 (uM):
- 4000
- 4000
- 4000
KeratinoSens Imax:
- 2.830997136
- 3.299878249
- 1.036847118
KeratinoSens Log EC1.5 (uM):
- 2.3973876117256947
- 1.7991780577657597
- 3.6020599913279625
KeratinoSens Log IC50 (uM):
- 3.6020599913279625
- 3.6020599913279625
- 3.6020599913279625
LLNA EC3 (%):
- 100
- 100
- 100
LLNA Log EC3 (%):
- 2
- 2
- 2
MW:
- 128.21
- 192.21
- 140.1
OPERA Boiling point (°C):
- 186.863
- 276.068
- 323.069
OPERA Henry constant (atm/m3):
- 0.00000784426
- 5.86618e-7
- 9.47507e-8
OPERA Log D at pH 5.5:
- 2.36
- 1.87
- -0.01
OPERA Log D at pH 7.4:
- 2.36
- 1.87
- -1.69
OPERA Melting point (°C):
- 25.1423
- 49.3271
- 128.292
OPERA Octanol-air partition coefficient Log Koa:
- 6.08747
- 6.56126
- 6.36287
OPERA Octanol-water partition coefficient LogP:
- 2.3597
- 1.86704
- 0.398541
OPERA Vapour pressure (mm Hg):
- 0.0839894
- 0.000406705
- 0.00472604
OPERA Water solubility (mol/L):
- 0.0510404
- 0.01476
- 0.0416421
OPERA pKaa:
- 10.68
- .nan
- 5.31
OPERA pKab:
- .nan
- .nan
- .nan
SMILES:
- canonical: OC1CCCCCCC1
original: OC1CCCCCCC1
- canonical: CCOC(=O)CC(=O)c1ccccc1
original: CCOC(=O)CC(=O)c1ccccc1
- canonical: O=[N+]([O-])c1ncccc1O
original: OC1=CC=CN=C1[N+]([O-])=O
TIMES Log Vapour pressure (Pa):
- 0.8564932564458658
- -0.2851674875666674
- -0.9385475209128068
Vapour pressure (Pa):
- 7.1861
- 0.5186
- 0.1152
cLogP:
- 2.285000000003492
- 1.206000000005588
- 0.5590000000020154
hCLAT CV75 (ug/mL):
- .nan
- 571.0951916
- .nan
hCLAT Call:
- .nan
- 0
- .nan
hCLAT EC150 (ug/mL):
- .nan
- .nan
- .nan
hCLAT EC200 (ug/mL):
- .nan
- .nan
- .nan
hCLAT MIT (ug/mL):
- .nan
- .nan
- .nan
kDPRA Call: []
kDPRA Log rate (1/s/M):
- .nan
- .nan
- .nan
Model description
[More Information Needed]
Intended uses & limitations
[More Information Needed]
Training Procedure
[More Information Needed]
Hyperparameters
Click to expand
| Hyperparameter | Value |
|---|---|
| copy_X | True |
| fit_intercept | True |
| n_jobs | |
| positive | False |
Model Plot
LinearRegression()In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
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LinearRegression()
Evaluation Results
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How to Get Started with the Model
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Model Card Authors
This model card is written by following authors:
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Citation
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BibTeX:
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model_card_authors
Tomaz Mohoric
limitations
This model is intended for educational purposes.
model_description
This is a multiple linear regression model on a skin sensitisation dataset.