Integrating computational lead optimization diagnostics with analog design and candidate selection

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Abstract

Aim: Combining computational lead optimization diagnostics with analog design and computational approaches for assessing optimization efforts are discussed and the compound optimization monitor is introduced. Methods: Approaches for compound potency prediction are described and a new analog design algorithm is introduced. Calculation protocols are detailed. Results & discussion: The study rationale is explained. Compound optimization monitor diagnostics are combined with a thoroughly evaluated approach for compound design and candidate prioritization. The diagnostic scoring scheme is further extended. Future perspective: Opportunities for practical applications of the integrated computational methodology are described and further development perspectives are discussed. Lay abstract Compound optimization is a central task in medicinal chemistry, which has many potential pitfalls. Computational approaches that help to better understand and guide chemical optimization efforts are highly desirable, but only a few are currently available. We have aimed to develop a computational methodology that combines, for the first time, the evaluation of progress in chemical optimization with the design of new candidate compounds.

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APA

Yonchev, D., & Bajorath, J. (2020). Integrating computational lead optimization diagnostics with analog design and candidate selection. Future Science OA, 6(3). https://doi.org/10.2144/fsoa-2019-0131

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