ProInterVal: Validation of Protein-Protein Interfaces through Learned Interface Representations.

ABSTRACT: Proteins are vital components of the biological world and serve a multitude of functions. They interact with other molecules through their interfaces and participate in crucial cellular processes. Disruption of these interactions can have negative effects on organisms, highlighting the importance of studying protein-protein interfaces for developing targeted therapies for diseases. Therefore, the development of a reliable method for investigating protein-protein interactions is of paramount importance. In this work, we present an approach for validating protein-protein interfaces using learned interface representations. The approach involves using a graph-based contrastive autoencoder architecture and a transformer to learn representations of protein-protein interaction interfaces from unl

SUBMITTER: Ovek D 

PROVIDER: S-EPMC11040718 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature