CBI!"# 11/5/2011
ChEMBL$%&'%()*+,-./0123&%456)78
池田 和由 ChEMBL
kaz@ebi.ac.uk

Topics / 9:)6;5<•! What is ChEMBL? / =>?@,AB•! Contents / $%&CD,EFGH•! Other ChEMBL resources /IJ)K)LM%(•! Questions / NOWho are we? / PQB•! ChEMBLR=>?@SATUV=>?L5WXY)EMBL-EBI
ZT2008[Z\]^_`abcZdef^g%h•! ijRklmn(oSpEFfqr^$%&'%(stu@vh6l(6wx)yzR£4.7MSZ{|qEBI}~•€Q^)p•‚ƒ•! L%„%AJohn OveringtonT…>†%A‡ˆ13‰

Research & Databases at the EBI Literature and ontologies
CiteXplore, GOGenomes
EnsemblEnsembl Genomes
EGA
Nucleotide sequence
ENA

Protein families,motifs and domains
InterPro

Functionalgenomics
ArrayExpress
Expression Atlas

Macromolecular
PDBeProtein activity
IntAct , PRIDE
Pathways
Reactome

Protein Sequences
UniProt•! ChEMBL database•! Curation
Chemogenomics•! Interface
ChEMBL•! Research group•! IMI eTox•! Industrial collaborations

Chemicalentities
ChEBI

Systems
BioModels
BioSamples

What is ChEMBLdb? / =>?@,AB•!
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-./23EFeŠ‹Rdrug-like cmpdsS)$%&'%(Œ•\Ž8•„t>•%‘’“eŠ‹)”•–—˜, ™•mš›SARbc&%456R&>m<Nœ•Sbc
žŸ 30[¡)MedChem¢£
ChEMBL->&%®¯%(R:9°S
PubChemœ•)Y¤$%&
FDA¥¦.
§¨©ªœ«¬RHTTPSS=>?@Wikipedia

Drug Discovery Process-./EF™•§(
TargetDiscovery•!Target
identification•!Microarray
profiling•!Targetvalidation•!Assay
development•!Biochemistry•!Clinical/Animal
disease models

Lead
Discovery•!Highthroughput
Screening (HTS)•!Fragment-based
screening•!Focusedlibraries•!Screening
collection

Clinical Trials

Lead
Optimisation

PreclinicalDevelopment•!Medicinal
Chemistry•!Structure-based
drug design•!Selectivity screens•!ADMET screens•!Cellular/Animal
disease models•!Pharmacokinetics•!Toxicology•!In vivo safety
pharmacology•!Formulation•!Dose prediction

Discovery

Phase
1

PK
tolerability

Phase
2

Phase
3

Efficacy

Safety&Efficacy

Development

Med. Chem. SAR

LaunchIndication
Discovery &expansion

Use

Clinical Candidates

Drugs~12,000 candidates

~2000
承認薬
（drugs）

ChEMBL$%&'%(> 690万件 生物活性（bioactivities）> 110万個 化合物（compounds）> 8千個 ターゲット(targets)What is ChEMBL data? / =>?@$%&,AB

CompoundeŠ‹
Target&%456

Bioactivity
Compound ±‹²³

>Thrombin
MAHVRGLQLPGCLALAALCSLVHSQHVFLAPQQARSLLQRVRRANTFLEEVRKGNLERECVEETCSYEEAFEALESSTATDVFWAKYTACETARTPRDKLAACLEGNCAEGLGTNYRGHVNITRSGIECQLWRSRYPHKPEINSTTHPGADLQENFCRNPDSSTTGPWCYTTDPTVRRQECSIPVCGQDQVTVAMTPRSEGSSVNLSPPLEQCVPDRGQQYQGRLAVTTHGLPCLAWASAQAKALSKHQDFNSAVQLVENFCRNPDGDEEGVWCYVAGKPGDFGYCDLNYCEEAVEEETGDGLDEDSDRAIEGRTATSEYQTFFNPRTFGSGEADCGLRPLFEKKSLEDKTERELLESYIDGRIVEGSDAEIGMSPWQVMLFRKSPQELLCGASLISDRWVLTAAHCLLYPPWDKNFTENDLLVRIGKHSRTRYERNIEKISMLEKIYIHPRYNWRENLDRDIALMKLKKPVAFSDYIHPVCLPDRETAASLLQAGYKGRVTGWGNLKETWTANVGKGQPSVLQVVNLPIVERPVCKDSTRIRITDNMFCAGYKPDEGKRGDACEGDSGGPFVMKSPFNNRWYQMGIVSWGEGCDRDGKYGFYTHVFRLKKWIQKVIDQFGE

Ki=4.5nM

Assay

SAR Data
APTT 11min

Extraction and Curation / ´µ,¨©¶%·¸>•! MedChem¹Wº%»@)¼½¢£¾¿ManuallyZ´µRY¤ÀÁS-! J Med Chem, Bioorg Med Chem Lett, J Nat Prod etc•! ->Ât(\T¨©¶%&%RChemistry,Biology)JQÃQ
)ÄÅÆSZ{Çg¯5<-! Chemical: Incorrect structures, Duplications, Missing salts etc-! Biogical: Normalise gene names, Assign Uniprot IDs, Target
classification, Confidence scores•! ÈÉÊœª5™$%6R3, 4ËÌZÍÎS

External Data Import / Ò£Óbc•! PubChemとのデータ共有-! Confirmatory (eŠ‹%&>m<N)Single Interaction Value))Ï
sÈÉÊZ->Ð%6Ñ
-! PubChemもChEMBLの文献情報を取り込んでいる。
-! 化合物のオーバーラップは、2%以下。

•! Neglected Disease Dataset（主にマラリアデータ）-! GSK & Novartis Malaria Screening Data-! Drugs for Neglected Diseases Initiative (DNDi) etc
10,909 化合物
ChEMBL
Literature

PubChem
Assays667,868

410,112
FJ Gamo et al. Nature 465(7296)
305-310 (2010)

ChEMBL Schema / (¨%Ô£Ó&%456eŠ‹
ÕÖRª5§-S-./Compounds / eŠ‹eŠ‹™•mš›!

•! eŠ‹)—˜bcATMolfileÑ
•! eŠ‹)×ØATStandard InChIsÙÚR(š¶Û=Ü(6L%sÝÞS•! ™•mš›)ßàRMW, PSA, logP, Ro5,Med_Chem_Friendly etc)eŠ‹ •! MolregnoATInternalœeŠ‹ID)îï
bc•! CHEMBL_IDATDBÛ®›·º@)IDÑCompounds, Assays, TargetsáqZârqãä%<œIDÑ-! prefixの”CHEMBL”が数字の前につく-! 例：CHEMBL123 (molregno=22942,chebi_id=122942)

eŠ‹
—˜!

•! åæçPpT&>m<NTèéêëìRíZ-./T—˜bcœfS

Targets / &%456RðÊSðÊ`a)îïbcðÊ`a)<l(•! íZ&>m<NÑKZñòTCell-Lineœ•Ñ•! ðÊ&>m<N)×ØATUniprot AccessionsÙÚÑ€¿ZóôÊZ`õÑ-!

e.g. Enzyme > Kinase > Protein Kinase > TK > EGFR•! &%456)ªö->p÷frøê
-! Compound known only to bind to receptor family-! e.g. activity reported vs. ‘Muscarinic
receptors’-! Compound binds to multi-complex-! e.g. Ion channel
ProteinDNA

Organism

Cell LineExperiments / ÕÖª5§-!
ª5§-,&%456!

ð#e€Q^²³"(nM)!

²³bc!

•! ª5§-ZAT&%456,eŠ‹)ùŠsúÈf^BindingûYZT
Functional,ADMETpüÇÑ
•! ²³bc)u>‘Ð->6AýþÑ
-! IC50 (half maximal inhibitory
concentration)-! Ki (binding affinity)-! MIC (minimum inhibitory concentration)-! % Inhibition (of activity)•! Rÿ!q\AœrpS²³")ð#es$œ|qrÇ-! Standard Values, Units and Types

疾患Functional Assays)%õ
Whole organism assays(e.g., anti-infectives/parasitics)(e.g., human ovarian cancer cell line cytotoxicity)

Tissue or cell-based disease model(e.g., glucose uptake by adipocytes)

Tissue or cell-based assay for target effect(e.g., contraction of guinea-pig ileum)

Target association

Disease association

Disease-derived cell-line

Cell-based assay over-expressing target(e.g., GPCR calcium mobilisation)

14標的分子Marketed Drugs / -./bc•! FDA¥¦.)bcsOrange Book¾¿´µ•! &'-./bcRRecent Drug ApprovalsSA?•(\)*+'

Rule of FivecompliantDrug class
Small molecule,peptide, antibody
etc.

First-in-class?

Single Enantiomer?

Prodrug?
Boxedwarning?

OralDelivery?

Parenteral Topical
Delivery? delivery?

Web Services / t¯?ö%,(•! REST APIZ{Ç™•(lh¾¿)ª<§(p’“•! Compound (similarity & substructure), Target, Bioactivity Search•! JAVA, Perl, Python)ö>™@-%‘s./•! XML, JSON)ªt6™5601söÐ%6•! 例：CHEMBL_IDによる化合物検索•! https://www.ebi.ac.uk/chemblws/compounds/CHEMBL1

ChEMBL for Drug Discovery

Physchem Property Space and Affinity

分子量ケミカルスペースとアフィニティ

RO5

アフィニティDrugs

GoodALogP!"#$%&'()*()+&*,-,&./%%0&123!24)*5&- Potency generally
increases with MWTBad

分子量
<300

300-400

400-500 500-600 >600

Physchem Property Space and ADMET`a5=Üv@(2%(,.‹34
6,-&'(2,7,(8,'(8(-9&.&:;<0&RO5

バイオアベイラビリティ

Drugs

ALogPBadGood- High MWT tends to lead topoor ADMET properties

`a5
<300

300-400

400-500

500-600>600

Drug-likeness Trends / プロパティトレンド
QED Drug-likeness Trend

Bickerton et al. 2012

% of compounds in Year

Rule of Five Trend

リピンスキーRO5Year£ÓeŠ‹)67ATRO5™•mš›s89Ñ&:;<[\A6¶>‘A=>€QqrœrComparison of Dataset / $%&§56)?@Median Property

4.5
4418
369

3.5

401353

32.5

MW
ALOGP
AROM

21.5
10.5
0

ChEMBL_13

PubChemDrug*chembl_13 data from literature*cmpds with MWT >1000 not included
21Drug>1999

BEI

Ligand Efficiency,ª®›äš›BEIA
pXC50*1000/MWTSEIA
pXC50*100/PSA
Colored byActivity ValueSEI•! Better to optimise compounds with highest efficiency not highest potency•! Puts compounds with different MWTs on same scale
22C. Abad-Zaptero DDT, 2005,10,464-469

Prevalent Rings in ChEMBL / ™L†¶>6L>(B%_<=1990%_2001-2010

23in pre 1990 top 12 but not in 2001-2010 top 12in 2001-2010 top 12 but not in pre 1990 top 12
Very few rings in the majority of bioactive molecules
similar to P Ertl J Med Chem 2006, 49,4568-4573% - no. of times ring appears /total no of rings reported for thatyear range

How to search in ChEMBL

Searching ChEMBLdb•! Identifying Compounds interacting with SpecificTargets-! Text search for protein names/synonyms-! Browse protein or organism tree-! Sequence search using BLAST•! Compound Searching-! Search by substructure or similarity-! Search by compound name-! Search by lists (smiles, names, IDs)

ChEMBLdb Interface
Browse Targets
ターゲットブラウザ

Research Results
Serotonin Receptor (セロトニン受容体)

DrugInformationCalc.
properties

Clickable structure

Parent and SaltForms

Database links

Webinar / t¯,»%EC (5/30)

Other ChEMBL Resources
DrugEBIlity•!創薬標的バリデーションDBeTOX•!トキシコロジー

Druggability

ChEMBL-NTD•!熱帯病の医薬品候補化合物DBMalariaSARfari•!Kinase/GPCRのSAR情報DB

Protein Family
FocusedProtein Families ChEMBL Timeline / &-hl->
40000

Number of Bioactivities

35000

GPCR
Kinase

30000

Protease
Ion Channel

25000

Nuclear Receptor
20000

Transporter

15000
10000
5000
01980

1985

1990

1995

Year

2000

2005

2010

Protein Families in ChEMBL / ®DÜL%Kinase

GPCR

12%
33%
Ion Channel

5%% of Bioactivities inChEMBLdb

Protease

9%

ChEMBLdb Contents (Targets)% of Bioactivities
in ChEMBLdb

Top10 by Target Class
KinaseProtease

Ion Channel

GPCR

TranscriptionFactor

Trends in GPCR Family
Number of Bioactivities by Target (Top50)
Year: 2009 ~ Current

H3P2Y12

CRTH2EP3

Number of Bioactivities by Compound (Top100)
Year: 2009 ~ Current

Clozapine

P2X(2) Antagonist

Kinase SARfari
Binding Site Similarity

Kinome Tree Target Browser

3D Structure Analysis

Kinase Domains & Compounds

ChEMBL DrugEBIlity Portal

Druggability,Tractabiliy
TargetLigandProteinDruggable

Rule of Five

Drug-like
LigandEDrug-likenessF

EDruggabilityF* Lipinski & Hopkins, Nature 2004
MW

HBD

HBA

LogP

RotB

Druggability

100<MW<550!5! 10!5! 10

Tractability

200<MW<800!8! 15!8! 16

Druggability Result -Family=>2-?,5?5&C>?D4?)19&C>?D4?)19&=>2-?()&0(),5?5&

A7+;&B>4++,'(8(-9&=>2-?()&=@25!@,-,5?5&&A7+;&B>4++,'(8(-9&A7+;&B>4++,'(8(-9&Transcription Factor

Avg. Druggability(# of domains per each protein > 3)

Druggability Result -Site DetailsTyrosine protein kinase

Site4

Site1

Frequency

0.35

Small Drug Sites
All Data

0.3
0.25
0.2
0.15
0.1
0.05
056 60 64

68 72 76 80 84

88

Buried Surface Area [%]Druggability Plots
A7+;&B>4++,'8?&F12>?&=>2-@>23'()&P,8?1N)Q:&

B(@9*>2G28,-?&&6?*41-,5?&HBIC6J&A7+;&E)5?3'8?&F12>?&#(>18?5K&0)2L)&B>4+&M,>+?-5&=>2-?()&0(),5?&H!"##$J&M>,)51>(!N2)&C,1-2>&H%#&&'(J&O?3'>,)?&=>2-?()&H)#*J&Publication / ¢£•! Bellis LJ, Akhtar R, AlLazikani B, Atkinson F,
Bento AP, Chambers J,
Davies M, Gaulton A,
Hersey A, Ikeda K, KrügerFA, Light Y, McGlinchey S,Santos R, Stauch B,Overington JP.
Biochem Soc Trans. 2011 Oct;39(5):1365-70.

•! A. Gaulton, L. Bellis, J. Chambers, M. Davies, A. Hersey, Y. Light, S.
McGlinchey, R. Akhtar, F. Atkinson, A.P. Bento, B. Al-Lazikani, D.
Michalovich, & J.P. Overington, NAR. 2011 Database Issue.

The ChEMBL-og- / &'bc•! ChEMBL?•(-! http://chembl.blogspot.co.uk

Webinar / t¯,»%•! Û>l->§Ü»%Rt¯,»%S-! 16-May-2012 3:30pm Schema and sql querying-! 30-May-2012 9:00am Interface and Searching (日本語)-! 13-Jun-2012 3:30pm Interface and Searching-! 27-Jun-2012 3:30pm Schema and sql querying-! 11-Jul-2012 3:30pm Interface and Searching-!http://chembl.blogspot.co.uk/2012/02/chembl-webinarsfor-2012.html•! 5Ì30:RGSB:9*¡BHI5*{ƒ-! JChEMBL)->&%®¯(,Ž8KZ9rq-! LMNAOPR:9°S-! •œ^\êQR’“-! âOrŠSTABkaz@ebi.ac.uk

Help and Feedback / âOrŠST•! chembl-help@ebi.ac.uk•! kaz@ebi.ac.ukIR:9°S

Acknowledgment / UVMark Davies*
Shaun McGlinchey
Yvonne Light*
Louisa Bellis*
Ruth Akhtar
Francis Atkinson**

Patricia Bento
George Papadatos**
Jon Chambers**
Anna Gaulton**
Anne Hersey**
John Overington* **(前職が企業研究者* Pharma出身**)