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GEODES: geometric descriptors for the assessment of global and local flexibility of proteins during molecular dynamics simulation

  • Karina Pats
  • , Igor Glukhov
  • , Stepan Petrosian
  • , Maria Mamaeva
  • , Alexey Sergushichev
  • , Marie Dominique Devignes
  • , Ferdinand Molnar
  • Nazarbayev University
  • St. Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO)
  • Bioinformatics Institute
  • Washington University St. Louis
  • Université de Lorraine

Research output: Contribution to journal › Article › peer-review

Abstract

Molecular dynamics simulations offer insights into macromolecular structures and functions through extensive time-series atomic data. Two widely used metrics for assessing these simulations are RMSD and RMSF. While RMSD measures conformational convergence, it suffers from degeneracy, where different conformations can produce identical values relative to a reference. RMSF indicates relative mobility but lacks temporal specificity. As both metrics provide only global perspectives, there is a pressing need for novel metrics to capture local flexibility with temporal resolution.We introduce GEODES, a novel complementary 3D geometrical descriptor approach, and compare its effectiveness with conventional analyses using RMSD and RMSF. Through molecular dynamics simulations of the vitamin D receptor trimeric complex, we demonstrate that GEODES significantly enhances the molecular dynamics analysis workflow, offering deeper insights into the structural dynamics and interactions of this complex. This innovative and versatile approach holds great promise for applications in drug discovery, structural biology, and bioinformatics. The GEODES Python3 script toolbox is available at https://github.com/rinnifox/GEODES.

Original languageEnglish
Pages (from-to)64259-64270
Number of pages12
JournalIEEE Access
Volume13
DOIs
Publication statusPublished - 2025

Funding

This work was supported by the Nazarbayev University under Collaborative Research Proposal 091019CRP2108 to F.M., ITMO University grant No. 621314 for Ph.D. and Master students, Modelling Biomolecules and theirs Interaction - Data Science for Health (MBI-DS4H) platform hosted by Inria/Loria and funded by Contrat Plan État Région, Innovations, Technologiques, Modélisation & Médicine Personalisée (CPER IT2MP) and Fonds Européen de Développement Régional (FEDER). The authors would like to thank the anonymous reviewers for their valuable suggestions. They thank EComputing facilities included the Grid'5000 testbed (https://www.grid5000.fr).

FundersFunder number
European Regional Development Fund
Data Science for Health
Nazarbayev University091019CRP2108, 621314
Contrat Plan État Région, Innovations, Technologiques, Modélisation & Médicine PersonaliséeCPER IT2MP

    Keywords

    • calcitriol
    • GEODES
    • Geometrical descriptors
    • Local and global stability
    • Molecular dynamics trajectory analysis
    • RMSD and RMSF
    • Structural flexibility
    • Temporal and spatial dynamics
    • transcriptional coactivator
    • vitamin D receptor

    ASJC Scopus subject areas

    • General Computer Science
    • General Materials Science
    • General Engineering

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