ArticleComputational and mathematical methods in medicine2018
Insights into the Molecular Mechanisms of Protein-Ligand Interactions by Molecular Docking and Molecular Dynamics Simulation: A Case of Oligopeptide Binding Protein.
Article in Computational and mathematical methods in medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.
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72 citing papers in PubMed, 237 citations in OpenAlex.
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12 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protein-ligand interactions are a necessary prerequisite for signal transduction, immunoreaction, and gene regulation. Protein-ligand interaction studies are important for understanding the mechanisms of biological regulation, and they provide a theoretical basis for the design and discovery of new drug targets. In this study, we analyzed the molecular interactions of protein-ligand which was docked by AutoDock 4.2 software. In AutoDock 4.2 software, we used a new search algorithm, hybrid algorithm of random drift particle swarm optimization and local search (LRDPSO), and the classical Lamarckian genetic algorithm (LGA) as energy optimization algorithms. The best conformations of each docking algorithm were subjected to molecular dynamic (MD) simulations to further analyze the molecular mechanisms of protein-ligand interactions. Here, we analyze the binding energy between protein receptors and ligands, the interactions of salt bridges and hydrogen bonds in the docking region, and the structural changes during complex unfolding. Our comparison of these complexes highlights differences in the protein-ligand interactions between the two docking methods. It also shows that salt bridge and hydrogen bond interactions play a crucial role in protein-ligand stability. The present work focuses on extracting the deterministic characteristics of docking interactions from their dynamic properties, which is important for understanding biological functions and determining which amino acid residues are crucial to docking interactions.
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