MSLDOCK: Multi-Swarm Optimization for Flexible Ligand Docking and Virtual Screening

2021 ◽  
Vol 61 (3) ◽  
pp. 1500-1515
Author(s):  
Chao Li ◽  
Jun Sun ◽  
Vasile Palade
Keyword(s):  
Virtual Screening ◽  
Ligand Docking ◽  
Swarm Optimization ◽  
Flexible Ligand ◽  
Flexible Ligand Docking

Similarity-driven flexible ligand docking

2000 ◽  
Vol 40 (4) ◽  
pp. 623-636 ◽  
Author(s):  
Xavier Fradera ◽  
Ronald M.A. Knegtel ◽  
Jordi Mestres
Keyword(s):  
Ligand Docking ◽  
Flexible Ligand ◽  
Flexible Ligand Docking

scholarly journals PSOVina: The hybrid particle swarm optimization algorithm for protein–ligand docking

2015 ◽  
Vol 13 (03) ◽  
pp. 1541007 ◽  
Author(s):  
Marcus C. K. Ng ◽  
Simon Fong ◽  
Shirley W. I. Siu
Keyword(s):  
Particle Swarm Optimization ◽  
Virtual Screening ◽  
Particle Swarm ◽  
Ligand Docking ◽  
Conformational Search ◽  
Search Problem ◽  
Data Set ◽  
Swarm Optimization ◽  
Screening Experiments ◽  
Hybrid Particle Swarm Optimization

Protein–ligand docking is an essential step in modern drug discovery process. The challenge here is to accurately predict and efficiently optimize the position and orientation of ligands in the binding pocket of a target protein. In this paper, we present a new method called PSOVina which combined the particle swarm optimization (PSO) algorithm with the efficient Broyden–Fletcher–Goldfarb–Shannon (BFGS) local search method adopted in AutoDock Vina to tackle the conformational search problem in docking. Using a diverse data set of 201 protein–ligand complexes from the PDBbind database and a full set of ligands and decoys for four representative targets from the directory of useful decoys (DUD) virtual screening data set, we assessed the docking performance of PSOVina in comparison to the original Vina program. Our results showed that PSOVina achieves a remarkable execution time reduction of 51–60% without compromising the prediction accuracies in the docking and virtual screening experiments. This improvement in time efficiency makes PSOVina a better choice of a docking tool in large-scale protein–ligand docking applications. Our work lays the foundation for the future development of swarm-based algorithms in molecular docking programs. PSOVina is freely available to non-commercial users at http://cbbio.cis.umac.mo .

Extracting Information from Flexible Receptor-Flexible Ligand Docking Experiments

2008 ◽  
pp. 104-114 ◽  
Author(s):  
Karina S. Machado ◽  
Evelyn K. Schroeder ◽  
Duncan D. Ruiz ◽  
Ana Wink ◽  
Osmar Norberto de Souza
Keyword(s):  
Ligand Docking ◽  
Flexible Ligand ◽  
Flexible Ligand Docking

Highly Flexible Ligand Docking: Benchmarking of the DockThor Program on the LEADS-PEP Protein–Peptide Data Set

2020 ◽  
Vol 60 (2) ◽  
pp. 667-683 ◽  
Author(s):  
Karina B. Santos ◽  
Isabella A. Guedes ◽  
Ana L. M. Karl ◽  
Laurent E. Dardenne
Keyword(s):  
Ligand Docking ◽  
Data Set ◽  
Flexible Ligand ◽  
Flexible Ligand Docking ◽  
Peptide Data

CIFDock: A novel CHARMM-based flexible receptor - flexible ligand docking protocol

2021 ◽  
Author(s):  
Sai Lakshmana Vankayala ◽  
Luke Warrensford ◽  
Amanda Pittman ◽  
Joseph Larkin ◽  
Henry Woodcock
Keyword(s):  
Ligand Docking ◽  
Flexible Ligand ◽  
Docking Protocol ◽  
Flexible Ligand Docking
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