Random drift particle swarm optimisation algorithm for highly flexible protein-ligand docking

DOI10.1016/J.JTBI.2018.08.034zbMath1406.92181OpenAlexW2889209375WikidataQ91250876 ScholiaQ91250876MaRDI QIDQ1712669

Peng Zhang

Publication date: 31 January 2019

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jtbi.2018.08.034

zbMATH Keywords

evolutionary computationparticle swarm optimisationautodock softwareprotein-ligand docking

Mathematics Subject Classification ID

Approximation methods and heuristics in mathematical programming (90C59) Biochemistry, molecular biology (92C40) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20) Software, source code, etc. for problems pertaining to biology (92-04)

Cites Work

• Unnamed Item
• Random drift particle swarm optimization algorithm: convergence analysis and parameter selection
• Minimization by Random Search Techniques

Related Items (1)

Insights into the molecular mechanisms of protein-ligand interactions by molecular docking and molecular dynamics simulation: a case of oligopeptide binding protein

Uses Software

• AutoDock
• DeepVS
• DockingApp
• GalaxyDock
• GalaxySite
• SODOCK
• jMetalCpp
• Python

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