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MELD in Action: Harnessing Data to Accelerate Molecular Dynamics

  • Jokent Gaza
  • , Emiliano Brini
  • , Justin L. MacCallum
  • , Ken A. Dill
  • , Alberto Perez
  • University of Florida
  • School of Chemistry and Materials Science
  • University of Calgary

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

We review MELD, an accelerator of Molecular Dynamics simulations of biomolecules. MELD (Modeling Employing Limited Data) integrates molecular dynamics (MD) with a variety of types of structural information through Bayesian inference, generating ensembles of protein and DNA structures having proper Boltzmann populations. MELD minimizes the computational sampling of irrelevant regions of phase space by applying energetic penalties to areas that conflict with the available data. MELD is effective in refining protein structures using NMR or cryo-EM data or predicting protein-ligand binding poses. As a plugin for OpenMM, MELD is interoperable with other enhanced sampling methods, offering a versatile tool for structural determination in computational chemistry and biophysics.

Original languageEnglish
Pages (from-to)1685-1693
Number of pages9
JournalJournal of Chemical Information and Modeling
Volume65
Issue number4
DOIs
StatePublished - Feb 24 2025

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