QSAR and computational tools
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The document discusses the significance of computational chemistry in modern scientific research, highlighting notable contributions and accolades in the field. It emphasizes the benefits of quantitative structure-activity relationships (QSAR) for innovative chemical assessment, including cost reduction and enhanced experimental efficiency. Additionally, it addresses the challenges and accuracy issues in predictive modeling, advocating for the integration of computational methods alongside human expertise.
QSAR and computational tools
- 1. Emilio BENFENATI Istituto di Ricerche Farmacologiche Mario Negri
- 2. The second prize after the Nobel Prize in 1998 to John Pople and Alter Kohn for computational chemistry The Nobel Prizes in Chemistry 1998, 2013 The Nobel Prize in Chemistry 2013 has gone to Michael Levitt, Martin Karplus and Arieh Warshel, who “took the chemical experiments into cyberspace”
- 3. Chemistry and cyberspace All science is computer science (New York Times) Millions of data to be processed, more and more common In silico methods like the glue to integrate multiple evidences
- 4. Seven Reasons to use QSAR 1. Innovation (also in view of millions of new data - ToxCast) 2. Time for experiments 3. Occurrence of enough laboratories/resources 4. Reduction of costs 5. Use of animals 6. Prioritization needs 7. Pro-active approach for greener chemicals
- 5. = f ( )
- 6. CHEMICALS: GOOD and EVIL 6
- 8. MOLECULAR FRAGMENTS AND ALERTS ASHBY identified RESIDUES for GENOTOXIC EFFECTS
- 9. MUTAGENICITY: Performance of QSAR models 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1 CAESAR SARpy ACD T.E.S.T. Topkat ADMET out AD in AD 0,00 0,10 0,20 0,30 0,40 0,50 0,60 0,70 0,80 0,90 1,00 CAESAR SARpy Toxtree TEST Consensus out AD in AD Accuracy
- 10. Issues: Work in progress Max accuracy for carcinogenicity models: 0.75 (Toxtree, in VEGA) Max accuracy for devtox models: 0.78 (SARpy + P&G, in VEGA), but MCC 0.24 (false negatives) Problem 1: Complexity of the endpoints Problem 2: Lack of data
- 12. www.vega-qsar.eu
- 13. Read-across Read-across: a correlation or relationship between two separate things From a chemical point of view: Read-across is a method for data-gap filling where information from one or more chemicals is used to predict the same endpoint for a target chemical
- 14. www.toxgate.eu
- 16. CONCLUSIONS Computational models as support to human experts Navigation within data and reasoning No conflict between “computer” and man Multiple in silico approaches Integrating multiple approaches (weight of evidence) Comparison with the experimental uncertainty/vairability