MD-Ligand-Receptor: A High-Performance Computing Tool for Characterizing Ligand-Receptor Binding Interactions in Molecular Dynamics Trajectories.
computational modeling of molecular systems
molecular dynamics
nucleic acid–ligand interactions
protein–ligand interactions
Journal
International journal of molecular sciences
ISSN: 1422-0067
Titre abrégé: Int J Mol Sci
Pays: Switzerland
ID NLM: 101092791
Informations de publication
Date de publication:
19 Jul 2023
19 Jul 2023
Historique:
received:
23
06
2023
revised:
15
07
2023
accepted:
18
07
2023
medline:
31
7
2023
pubmed:
29
7
2023
entrez:
29
7
2023
Statut:
epublish
Résumé
Molecular dynamics simulation is a widely employed computational technique for studying the dynamic behavior of molecular systems over time. By simulating macromolecular biological systems consisting of a drug, a receptor and a solvated environment with thousands of water molecules, MD allows for realistic ligand-receptor binding interactions (lrbi) to be studied. In this study, we present MD-ligand-receptor (MDLR), a state-of-the-art software designed to explore the intricate interactions between ligands and receptors over time using molecular dynamics trajectories. Unlike traditional static analysis tools, MDLR goes beyond simply taking a snapshot of ligand-receptor binding interactions (lrbi), uncovering long-lasting molecular interactions and predicting the time-dependent inhibitory activity of specific drugs. With MDLR, researchers can gain insights into the dynamic behavior of complex ligand-receptor systems. Our pipeline is optimized for high-performance computing, capable of efficiently processing vast molecular dynamics trajectories on multicore Linux servers or even multinode HPC clusters. In the latter case, MDLR allows the user to analyze large trajectories in a very short time. To facilitate the exploration and visualization of lrbi, we provide an intuitive Python notebook (Jupyter), which allows users to examine and interpret the results through various graphical representations.
Identifiants
pubmed: 37511429
pii: ijms241411671
doi: 10.3390/ijms241411671
pmc: PMC10380688
pii:
doi:
Substances chimiques
Ligands
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
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