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Prediction of bioactivity from chemical structure Small Molecule Bioactivity Resources At The EBI Jérémy Besnard [email_address]
Myself ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Prediction of bioactivity ,[object Object],[object Object],[object Object],[object Object],[object Object],QSAR – Quantitative Structure-Activity Relationship Some slides are adapted from Richard Lewis (Novartis) presentation at the University of Sheffield Practical introduction to  Chemoinformatics  course  (next in 2011)
Example ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Molecular Weight 180 220 250 290 340 380 450 500 Activity (pIC50) 4 4.3 4.8 5.4 4.8 5.8 7.5 7.7
QSAR Activity  = IC50, Ki, Ratios… Molecular Descriptors Topological (shape, size) Physical & Thermodynamics Chemical feature (substructure) Activity =  f (Molecular Descriptors) Statistics
The absolute basics ,[object Object],[object Object],[object Object],[object Object],[object Object]
Advantages of Models ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Activity ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Molecular descriptors ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],www.moleculardescriptors.eu
Fingerprint ,[object Object],[object Object],[object Object],Acid Cl Amide 6 aromatic ring …
Focus on Fingerprint ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
FCFP:  Initial Atom Codes
Extending the Initial Atom Codes ,[object Object],[object Object],O N A A A A O N A A A A A Each iteration adds bits that represent larger and  larger structures Iteration 0 Iteration 1 Iteration 2
Generating the Fingerprint ,[object Object],[object Object],[object Object],[object Object]
Data Sets
Validity of a model ,[object Object],The Trouble with QSAR (or How I Learned To Stop Worrying and Embrace Fallacy),  Johnson, J. Chem. Inf. Model., 2008, 48 (1), pp 25–26
Training and Test Sets ,[object Object],[object Object],[object Object],[object Object],http:// www.cs.cmu.edu/~awm/tutorials http://research.cs.tamu.edu/prism/lectures/iss/iss_l13.pdf
Space of the sets ,[object Object]
Training vs Test Sets ,[object Object],[object Object],[object Object],Test Set Test Set Test Set
Questions?
Statistical Methods Activity Molecular Descriptors Training and test sets Activity =  f (Molecular Descriptors) Statistics
Categorical ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Recursive Partitioning ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Molecular Weight >450 ≤  450 Polar surface area >100 0 , 10 ≤ 100 2 , 0 cLogP Acid Group 0 , 7 >4.2 ≤  4.2 18 , 2 1 , 5 Yes No 21 Actives ,  24 Inactives 2 , 10 19 , 14 19 , 7 MW: 178 PSA: 37 LogP: 3 MW: 205 PSA: 20 LogP: 3
Substructural Analysis ,[object Object],[object Object],[object Object],Act i  = Nb of active compounds containing fragment i Inact i  = Nb of inactive compounds containing fragment i
Naïve Bayesian Classifiers ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Ref:  New Methods for Ligand-Based Virtual Screening:  Use of Data Fusion and Machine Learning to Enhance the Effectiveness of Similarity Searching , Hert et al., J. Chem. Inf. Model., 2006, 46 (2), pp 462–470
Validation ,[object Object],[object Object],[object Object],[object Object]
Specificity & Sensitivity ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],TP=True Positive TN=True Negative FP=False Positive FN=False Negative ,[object Object],http:// en.wikipedia.org/wiki/Sensitivity_and_specificity
ROC curve ,[object Object],Coefficient = Area Under Curve  1 is ideal, 0.5 is random http:// www.medcalc.be/manual/roc.php
Enrichment curve ,[object Object],[object Object],There 40% of the active in the top 10%. This plot doesn’t tell how many compounds this represents (could be 40 actives and 10,000 inactive in the top 10%)
Other methods ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Questions?
Regression ,[object Object],[object Object],[object Object]
Historical ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],p-σ-π  Analysis. A Method for the Correlation of Biological Activity and Chemical Structure , Hansch et al.,  J. Am. Chem. Soc., 1964, 86 (8), pp 1616–1626 Parabolic dependence of drug action upon  lipophilic  character as revealed by a study of hypnotics , Hansch et al.,  J. Med. Chem., 1968, 11 (1), pp 1–11
Deriving a QSAR equation ,[object Object],[object Object],[object Object],[object Object]
Quality ,[object Object],[object Object],Almost the same R 2
Cross validation ,[object Object],[object Object],[object Object]
Designing QSAR experiment ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Regression algorithms ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Not limited ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Regression + Category ,[object Object]
After ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Outliers ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],On Outliers and Activity  Cliffs−Why  QSAR Often Disappoints , Maggiora, J. Chem. Inf. Model.2006, 46, 1535−1535 Structure−Activity  Relationship Anatomy by Network-like Similarity Graphs and Local  Structure−Activity  Relationship Indices , Wawer et al.,  J. Med. Chem., 2008, 51 (19), pp 6075–6084
A model is a model ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Real correlation? ,[object Object],Why do we Sometimes get Nonsense-Correlations between Time-Series?--A Study in Sampling and the Nature of Time-Series ,  Yule,  Journal of the Royal Statistical Society , Vol. 89, No. 1. (Jan., 1926), pp. 1-63
Further – Multiple Targets ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Principle ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
References ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Questions
Practicals Using Pipeline Pilot Regression and Classification

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Prediction Of Bioactivity From Chemical Structure

  • 1. Prediction of bioactivity from chemical structure Small Molecule Bioactivity Resources At The EBI Jérémy Besnard [email_address]
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  • 5. QSAR Activity = IC50, Ki, Ratios… Molecular Descriptors Topological (shape, size) Physical & Thermodynamics Chemical feature (substructure) Activity = f (Molecular Descriptors) Statistics
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  • 12. FCFP: Initial Atom Codes
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  • 21. Statistical Methods Activity Molecular Descriptors Training and test sets Activity = f (Molecular Descriptors) Statistics
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  • 24. Molecular Weight >450 ≤ 450 Polar surface area >100 0 , 10 ≤ 100 2 , 0 cLogP Acid Group 0 , 7 >4.2 ≤ 4.2 18 , 2 1 , 5 Yes No 21 Actives , 24 Inactives 2 , 10 19 , 14 19 , 7 MW: 178 PSA: 37 LogP: 3 MW: 205 PSA: 20 LogP: 3
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  • 50. Practicals Using Pipeline Pilot Regression and Classification