Computational modeling approaches to quantitative structure–binding kinetics relationships in drug discovery

Pier G. De Benedetti, Francesca Fanelli

Index: 10.1016/j.drudis.2018.03.010

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Abstract

Highlights • The interplay of kinetic rates and binding affinity is essential in drug design/discovery. • Examples of linear correlations between kinetic rates and binding affinity are reported. • QSKR models based on empirical and computational molecular descriptors are shown. • Computational approaches to decipher at the atomic detail drug-binding kinetics are reviewed. Simple comparative correlation analyses and quantitative structure–kinetics relationship (QSKR) models highlight the interplay of kinetic rates and binding affinity as an essential feature in drug design and discovery. The choice of the molecular series, and their structural variations, used in QSKR modeling is fundamental to understanding the mechanistic implications of ligand and/or drug–target binding and/or unbinding processes. Here, we discuss the implications of linear correlations between kinetic rates and binding affinity constants and the relevance of the computational approaches to QSKR modeling.