DynaRepo: the repository of macromolecular conformational dynamics

Proteins, RNA, and DNA are central to virtually all cellular processes, often assembling into macromolecular complexes to perform their functions. While these molecules are inherently dynamic, most methods for studying their mechanisms focus on static structures. Recent deep learning advances in protein structure prediction highlight the potential of data-driven approaches, yet dynamic behavior that is critical for interactions such as antibody-antigen recognition, intrinsically disordered proteins, and protein-nucleic acid binding, remains underexplored. To address this gap, we present DynaRepo, a repository of macromolecular conformational dynamics comprising $\sim$450 complexes and $\sim$270 single-chain proteins from PDBbind, the Structural Antibody Database (SAbDab), and benchmark sets. Each complex was simulated in triplicate for 500 ns, totaling $>$1100 $\mu$s of molecular dynamics data, with extensive pre-calculated analyses. DynaRepo provides a foundation for dynamics-aware deep learning frameworks and is freely available at: https://dynarepo.inria.fr/.

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Publication Details

Journal
Nucleic Acids Research
Published
2025-11-13
DOI
https://doi.org/10.1093/nar/gkaf1130
Citations
4
Primary Topic
Protein Structure and Dynamics
Type
article
Field-Weighted Citation Impact
3.22

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article

DynaRepo: the repository of macromolecular conformational dynamics

Emmanuelle Bignon, Yasaman Karami, Hamed Khakzad, Omid Mokhtari
4 citations
Nucleic Acids Research
Protein Structure and Dynamics
3.22
article

DynaRepo: the repository of macromolecular conformational dynamics

Emmanuelle Bignon, Yasaman Karami, Hamed Khakzad, Omid Mokhtari
article en
4 citations

Abstract

Proteins, RNA, and DNA are central to virtually all cellular processes, often assembling into macromolecular complexes to perform their functions. While these molecules are inherently dynamic, most methods for studying their mechanisms focus on static structures. Recent deep learning advances in protein structure prediction highlight the potential of data-driven approaches, yet dynamic behavior that is critical for interactions such as antibody-antigen recognition, intrinsically disordered proteins, and protein-nucleic acid binding, remains underexplored. To address this gap, we present DynaRepo, a repository of macromolecular conformational dynamics comprising $\sim$450 complexes and $\sim$270 single-chain proteins from PDBbind, the Structural Antibody Database (SAbDab), and benchmark sets. Each complex was simulated in triplicate for 500 ns, totaling $>$1100 $\mu$s of molecular dynamics data, with extensive pre-calculated analyses. DynaRepo provides a foundation for dynamics-aware deep learning frameworks and is freely available at: https://dynarepo.inria.fr/.

Nucleic Acids ResearchVol. 54(D1)
Laboratoire Lorrain de Recherche en Informatique et ses Applications (FR), Laboratoire de Physique et Chimie Théoriques, Université de Lorraine (FR)
Agence Nationale de la Recherche, Grand Équipement National De Calcul Intensif
Openalex Percentile: Top 7%
Protein Structure and Dynamics
3.22
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