Representing structures of the multiple conformational states of proteins

21 August 2023, Version 2
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Biomolecules exhibit dynamic behavior that single-state models of their structures cannot fully capture. We review some recent advances for investigating multiple conformations of biomolecules, including experimental methods, molecular dynamics simulations, and machine learning. We also address the challenges associated with representing single- and multiple-state models in data archives, with a particular focus on NMR structures. Establishing standardized representations and annotations will facilitate effective communication and understanding of these complex models to the broader scientific community.

Keywords

Biomolecular NMR
X-ray Crystallography
Cryogenic Electron Microscopy
Protein Dynamics
AI-based Modeling

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Comment number 1, Gaetano Montelione: Nov 25, 2023, 00:17

This work is now published: Ramelot TA, Tejero R, Montelione GT. Representing structures of the multiple conformational states of proteins. Curr. Opin. Struct. Biol. 83, 102703. 2023