Systematic analysis of the relationship between fold-dependent flexibility and artificial intelligence protein structure prediction.

ABSTRACT: Artificial Intelligence (AI)-based deep learning methods for predicting protein structures are reshaping knowledge development and scientific discovery. Recent large-scale application of AI models for protein structure prediction has changed perceptions about complicated biological problems and empowered a new generation of structure-based hypothesis testing. It is well-recognized that proteins have a modular organization according to archetypal folds. However, it is yet to be determined if predicted structures are tuned to one conformation of flexible proteins or if they represent average conformations. Further, whether or not the answer is protein fold-dependent. Therefore, in this study, we analyzed 2878 proteins with at least ten distinct experimental structures available, from which w

SUBMITTER: Haque N 

PROVIDER: S-EPMC11594405 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature