Developing MELD-accelerated Molecular Dynamics Protocols to Simulate the Binding of the P53-Derived Ligand to the MDM-2, X Protein

In this study, we focus on developing computational methods to predict protein-ligand binding affinities, with applications in peptide drug discovery. Molecular Dynamics (MD) simulations can capture the complex conformational behavior of proteins, but their high computational cost limits their efficiency. MELD, or Modeling Employing Limited Data, is a Bayesian approach that integrates external information to accelerate sampling of low- energy, high-probability conformations. Building on previous work by Morrone et al., which successfully applied MELD to P53-MDM2 complexes, we hypothesize that we can effectively compute the relative binding affinities while reducing steric clashes and mitigating the effect of slowed diffusion on simulation convergence time. We present optimized MELD protocols that reproduce Morrone’s results within 1% of the target value, supporting the method’s accuracy and efficiency for peptide-based drug discovery.

Publication Details

Journal
RIT Scholar Works (Rochester Institute of Technology)
Published
2025-05-01
Primary Topic
Orthoptera Research and Taxonomy
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article
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article

Developing MELD-accelerated Molecular Dynamics Protocols to Simulate the Binding of the P53-Derived Ligand to the MDM-2, X Protein

RIT Scholar Works (Rochester Institute of Technology)
Orthoptera Research and Taxonomy
article

Developing MELD-accelerated Molecular Dynamics Protocols to Simulate the Binding of the P53-Derived Ligand to the MDM-2, X Protein

article en

Abstract

In this study, we focus on developing computational methods to predict protein-ligand binding affinities, with applications in peptide drug discovery. Molecular Dynamics (MD) simulations can capture the complex conformational behavior of proteins, but their high computational cost limits their efficiency. MELD, or Modeling Employing Limited Data, is a Bayesian approach that integrates external information to accelerate sampling of low- energy, high-probability conformations. Building on previous work by Morrone et al., which successfully applied MELD to P53-MDM2 complexes, we hypothesize that we can effectively compute the relative binding affinities while reducing steric clashes and mitigating the effect of slowed diffusion on simulation convergence time. We present optimized MELD protocols that reproduce Morrone’s results within 1% of the target value, supporting the method’s accuracy and efficiency for peptide-based drug discovery.

RIT Scholar Works (Rochester Institute of Technology)
Openalex Percentile: Top 41%
Orthoptera Research and Taxonomy
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