ArticleBiophysical journal2020
Predicting Protein Functional Motions: an Old Recipe with a New Twist.
Article in Biophysical journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Article
- PETIMOT: a novel framework for inferring protein motions from sparse data using SE(3)-equivariant graph neural networks.Acta crystallographica. Section D, Structural biology · 2026Article
- Efficient sampling of large-scale transition pathways and intermediate conformations in sub-mesoscopic protein complexes.Nature communications · 2026Article
- SeaMoon: From protein language models to continuous structural heterogeneity.Structure (London, England : 1993) · 2025Article
- Engineering Protein Dynamics through Mutational Energy Landscape Traps.Journal of chemical information and modeling · 2025Article
- Assessment of Four Theoretical Approaches to Predict Protein Flexibility in the Crystal Phase and Solution.Journal of chemical theory and computation · 2024Article
- Reused Protein Segments Linked to Functional Dynamics.Molecular biology and evolution · 2024Article
- Explaining Conformational Diversity in Protein Families through Molecular Motions.Scientific data · 2024Article
- Article
- Structures of a deAMPylation complex rationalise the switch between antagonistic catalytic activities of FICD.Nature communications · 2021Article
- Interdomain Flexibility within NADPH Oxidase Suggested by SANS Using LMNG Stealth Carrier.Biophysical journal · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Large macromolecules, including proteins and their complexes, very often adopt multiple conformations. Some of them can be seen experimentally, for example with x-ray crystallography or cryo-electron microscopy. This structural heterogeneity is not occasional and is frequently linked with specific biological function. Thus, the accurate description of macromolecular conformational transitions is crucial for understanding fundamental mechanisms of life's machinery. We report on a real-time method to predict such transitions by extrapolating from instantaneous eigen motions, computed using the normal mode analysis, to a series of twists. We demonstrate the applicability of our approach to the prediction of a wide range of motions, including large collective opening-closing transitions and conformational changes induced by partner binding. We also highlight particularly difficult cases of very small transitions between crystal and solution structures. Our method guarantees preservation of the protein structure during the transition and allows accessing conformations that are unreachable with classical normal mode analysis. We provide practical solutions to describe localized motions with a few low-frequency modes and to relax some geometrical constraints along the predicted transitions. This work opens the way to the systematic description of protein motions, whatever their degree of collectivity. Our method is freely available as a part of the NOn-Linear rigid Block (NOLB) package.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.