An optimized thermodynamics integration protocol for identifying beneficial mutations in antibody design.

ABSTRACT: Accurate identification of beneficial mutations is central to antibody design. Many knowledge-based (KB) computational approaches have been developed to predict beneficial mutations, but their accuracy leaves room for improvement. Thermodynamic integration (TI) is an alchemical free energy algorithm that offers an alternative technique for identifying beneficial mutations, but its performance has not been evaluated. In this study, we developed an efficient TI protocol with high accuracy for predicting binding free energy changes of antibody mutations. The improved TI method outperforms KB methods at identifying both beneficial and deleterious mutations. We observed that KB methods have higher accuracies in predicting deleterious mutations than beneficial mutations. A pipeline using KB meth

SUBMITTER: Sheng Z 

PROVIDER: S-EPMC10235760 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature