Machine learning/molecular dynamic protein structure prediction approach to investigate the protein conformational ensemble.

ABSTRACT: Proteins exist in several different conformations. These structural changes are often associated with fluctuations at the residue level. Recent findings show that co-evolutionary analysis coupled with machine-learning techniques improves the precision by providing quantitative distance predictions between pairs of residues. The predicted statistical distance distribution from Multi Sequence Analysis reveals the presence of different local maxima suggesting the flexibility of key residue pairs. Here we investigate the ability of the residue-residue distance prediction to provide insights into the protein conformational ensemble. We combine deep learning approaches with mechanistic modeling to a set of proteins that experimentally showed conformational changes. The predicted protein models w

SUBMITTER: Audagnotto M 

PROVIDER: S-EPMC9200820 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature