MOARF, an Integrated Workflow for Multiobjective Optimization: Implementation, Synthesis, and Biological Evaluation | Zendy

Nicholas C. Firth | Zendy; Butrus Atrash | Zendy; Nathan Brown | Zendy; Julian Blagg | Zendy

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MOARF, an Integrated Workflow for Multiobjective Optimization: Implementation, Synthesis, and Biological Evaluation

Author(s) -

Nicholas C. Firth,

Butrus Atrash,

Nathan Brown,

Julian Blagg

Publication year - 2015

Publication title -

journal of chemical information and modeling

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.24

H-Index - 160

eISSN - 1549-960X

pISSN - 1549-9596

DOI - 10.1021/acs.jcim.5b00073

Subject(s) - pharmacophore , workflow , computer science , scope (computer science) , multi objective optimization , chemical space , fragment (logic) , combinatorial chemistry , biochemical engineering , mathematical optimization , drug discovery , chemistry , algorithm , mathematics , engineering , machine learning , database , stereochemistry , biochemistry , programming language

We describe the development and application of an integrated, multiobjective optimization workflow (MOARF) for directed medicinal chemistry design. This workflow couples a rule-based molecular fragmentation scheme (SynDiR) with a pharmacophore fingerprint-based fragment replacement algorithm (RATS) to broaden the scope of reconnection options considered in the generation of potential solution structures. Solutions are ranked by a multiobjective scoring algorithm comprising ligand-based (shape similarity) biochemical activity predictions as well as physicochemical property calculations. Application of this iterative workflow to optimization of the CDK2 inhibitor Seliciclib (CYC202, R-roscovitine) generated solution molecules in desired physicochemical property space. Synthesis and experimental evaluation of optimal solution molecules demonstrates CDK2 biochemical activity and improved human metabolic stability.

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