Multistep Reaction Based De Novo Drug Design: Generating Synthetically Feasible Design Ideas
| Autor: | Roman J. Dorfman, Victoria C. Francis, Bree L. Richey, Brian B. Masek, Stephan Nagy, Karen DuBrucq, David S. Baker, Farhad Soltanshahi |
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| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Quantitative structure–activity relationship Computer science Databases Pharmaceutical General Chemical Engineering Evolutionary algorithm Chemistry Techniques Synthetic Library and Information Sciences Machine learning computer.software_genre 01 natural sciences 03 medical and health sciences Humans Computer Simulation ADME business.industry Drug discovery General Chemistry 0104 chemical sciences Computer Science Applications 010404 medicinal & biomolecular chemistry 030104 developmental biology Docking (molecular) Drug Design Feasibility Studies Artificial intelligence business computer Algorithms |
| Zdroj: | Journal of chemical information and modeling. 56(4) |
| ISSN: | 1549-960X |
| Popis: | We describe a "multistep reaction driven" evolutionary algorithm approach to de novo molecular design. Structures generated by the approach include a proposed synthesis path intended to aid the chemist in assessing the synthetic feasibility of the ideas that are generated. The methodology is independent of how the design ideas are scored, allowing multicriteria drug design to address multiple issues including activity at one or more pharmacological targets, selectivity, physical and ADME properties, and off target liabilities; the methods are compatible with common computer-aided drug discovery "scoring" methodologies such as 2D- and 3D-ligand similarity, docking, desirability functions based on physiochemical properties, and/or predictions from 2D/3D QSAR or machine learning models and combinations thereof to be used to guide design. We have performed experiments to assess the extent to which known drug space can be covered by our approach. Using a library of 88 generic reactions and a database of ∼20 000 reactants, we find that our methods can identify "close" analogs for ∼50% of the known small molecule drugs with molecular weight less than 300. To assess the quality of the in silico generated synthetic pathways, synthesis chemists were asked to rate the viability of synthesis pathways: both "real" and in silico generated. In silico reaction schemes generated by our methods were rated as very plausible with scores similar to known literature synthesis schemes. |
| Databáze: | OpenAIRE |
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