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Modeling P450 SItes of Metabolism (LB596)
Author(s) -
Swamidass S. Joshua
Publication year - 2014
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.28.1_supplement.lb596
Subject(s) - computer science , drug metabolism , computational biology , drug discovery , small molecule , metabolism , isozyme , biochemical engineering , chemistry , bioinformatics , biology , enzyme , biochemistry , engineering
Our group has been working on ways to improve the design and use of P450 modeling technologies. This is important because a large proportion of drugs are metabolized by P450 enzymes, and variants in P450s commonly cause patients to respond differently to medicines. We are pursuing two innovations in this area. First, we have developed P450 models that can predict what atoms are metabolized on molecules based on their structure. Our approach uses training data, molecules where the sites of metabolism are known, to build a predictive model that can accurately predict how new molecules are metabolized by 9 separate P450 isozymes. Knowing which atoms are modified‐‐‐the sites of P450 metabolism‐‐‐enables chemists to modify molecules to improve their metabolic profiles. Second, we developed a strategy for that can make use of region‐resolution site‐of‐metabolism data, instead of exclusively relying on the atom‐resolution data to which prior methods are confined. This unique capability can be leveraged to improve the accuracy of prediction of sites of metabolism on molecule, until now, impossible to predict. Our hope is to extend this technology to model how P450 variants metabolize drugs differently from one another. Effective modeling of metabolism can help overcome the central challenges in modern drug discovery and development: reducing the cost and risk of developing new drugs by ensuring the right medicines are given to the right patients.