Structure-based methods for predicting target mutation-induced drug resistance and rational drug design to overcome the problem

Drug resistance has become one of the biggest challenges in drug discovery and/or development and has attracted great research interests worldwide. During the past decade, computational strategies have been developed to predict target mutation-induced drug resistance. Meanwhile, various molecular design strategies, including targeting protein backbone, targeting highly conserved residues and dual/multiple targeting, have been used to design novel inhibitors for combating the drug resistance. In this article we review recent advances in development of computational methods for target mutation-induced drug resistance prediction and strategies for rational design of novel inhibitors that could be effective against the possible drug-resistant mutants of the target.

► Recently developed structure-based computational methods are capable of predicting target mutation-induced drug resistance.
► It is possible to account for possible mutation-induced drug resistance during the drug discovery.
► Various molecular design strategies have been used to rationally design novel drugs with reduced resistance risk.
► The use of structure-based methods will become more and more popular in the battle against drug resistance.