An accurate metalloprotein-specific scoring function and molecular docking program devised by a dynamic sampling and iteration optimization strategy

Journal of Chemical Information and Modeling
Fang BaiHonglin Li

Abstract

Metalloproteins, particularly zinc metalloproteins, are promising therapeutic targets, and recent efforts have focused on the identification of potent and selective inhibitors of these proteins. However, the ability of current drug discovery and design technologies, such as molecular docking and molecular dynamics simulations, to probe metal-ligand interactions remains limited because of their complicated coordination geometries and rough treatment in current force fields. Herein we introduce a robust, multiobjective optimization algorithm-driven metalloprotein-specific docking program named MpSDock, which runs on a scheme similar to consensus scoring consisting of a force-field-based scoring function and a knowledge-based scoring function. For this purpose, in this study, an effective knowledge-based zinc metalloprotein-specific scoring function based on the inverse Boltzmann law was designed and optimized using a dynamic sampling and iteration optimization strategy. This optimization strategy can dynamically sample and regenerate decoy poses used in each iteration step of refining the scoring function, thus dramatically improving both the effectiveness of the exploration of the binding conformational space and the sensitivity...Continue Reading

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Citations

Dec 20, 2015·Journal of Chemical Information and Modeling·Flavio Ballante, Garland R Marshall
Dec 19, 2015·Journal of Medicinal Chemistry·Damodara N ReddyGarland R Marshall
Sep 14, 2018·Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry·Wei XiaoHonglin Li
Dec 6, 2018·Physical Chemistry Chemical Physics : PCCP·Deliang ChenXiaolin Fan
Aug 29, 2019·Journal of Chemical Information and Modeling·Süleyman Selim Çınaroğlu, Emel Timuçin

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