OSPREY Predicts Resistance Mutations Using Positive and Negative Computational Protein Design.

ABSTRACT: Drug resistance in protein targets is an increasingly common phenomenon that reduces the efficacy of both existing and new antibiotics. However, knowledge of future resistance mutations during pre-clinical phases of drug development would enable the design of novel antibiotics that are robust against not only known resistant mutants, but also against those that have not yet been clinically observed. Computational structure-based protein design (CSPD) is a transformative field that enables the prediction of protein sequences with desired biochemical properties such as binding affinity and specificity to a target. The use of CSPD to predict previously unseen resistance mutations represents one of the frontiers of computational protein design. In a recent study (Reeve et al. Proc Natl Acad Sc

SUBMITTER: Ojewole A 

PROVIDER: S-EPMC5192561 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature