An integrated protein structure fitness scoring approach for identifying native-like model structures.

ABSTRACT: The structural information of a protein is pivotal to comprehend its functions, protein-protein and protein-ligand interactions. There is a widening gap between the number of known protein sequences and that of experimentally determined structures. The protein structure prediction has emerged as an efficient alternative to deliver the reliable structural information of proteins. However, it remains a challenge to identify the best model among the many predicted by one or a few structure prediction methods. Here we report ProFitFun-Meta, a neural network based pure single model scoring method for assessing the quality of predicted model structures by an effective combination structural information of various backbone dihedral angle and residue surface accessibility preferences of amino acid

SUBMITTER: Kaushik R 

PROVIDER: S-EPMC9708444 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature