Hidden Structural States of Proteins Revealed by Conformer Selection with AlphaFold-NMR.

ABSTRACT: We introduce AlphaFold-NMR, a novel approach to NMR structure determination that reveals previously undetected protein conformational states. Unlike conventional NMR methods that rely on NOE-derived spatial restraints, AlphaFold-NMR combines AI-driven conformational sampling with Bayesian scoring of realistic protein models against NOESY and chemical shift data. This method uncovers alternative conformational states of the enzyme Gaussia luciferase, involving large-scale changes in the lid, binding pockets, and other surface cavities. It also identifies similar yet distinct conformational states of the human tumor suppressor Cyclin-Dependent Kinase 2-Associated Protein 1. These studies demonstrate the potential of AI-based modeling with enhanced sampling to generate diverse structur

SUBMITTER: Huang YJ 

PROVIDER: S-EPMC11230435 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature