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PSOVina - Fast Protein-Ligand Docking Tool based on PSO and AutoDock Vina 

Studying phase transition temperature of pentadecane using MD simulations

A fast docking tool based on the efficient optimization algorithm of Particle Swarm Intelligence and the framework of AutoDock Vina. Based on the initial PSO implementation, our PSOVina method has undergone several important improvements to enhance the docking accuary and achieve remarkable efficiency as compared to the original AutoDock Vina. 


Releases

Download

(Freely available for academic use only, please read our Open Source License)

Required Software

For successful compilation, please install Boost (version 1.59 or above). For preparing molecules for docking,  please install AutoDockTools (ADT).

Installation

The installation basically follows the installation of AutoDock Vina:
a. unpack the files
b. cd psovina-x.x/build/<your-platform>/release
c. modify Makefile to suit your system setting
d. type "make" to compile

The binary psovina will be generated at the current directory. You can copy this binary to a directory in your PATH e.g. /usr/local/bin, or add the path of the current directory to your PATH.

Running PSOVina

You can run psovina as the way you run vina but additional three parameters (optional) are used to specify how the PSO algorithm perform searching:
--num_particles arg (=8) Number of particles
--w arg (=0.36) Inertia weight
--c1 arg (=0.99) Cognitive weight
--c2 arg (=0.99) Social weight

 
For example, docking Kifunensine in the Mannosidase enzyme (PDBID 1ps3 from the PDBbind v2012 dataset) using PSOVina with default PSO parameters in a 8-core computer and obtain the lowest energy prediction:

% <path-to-AutoDockTools>/prepare_ligand4.py -l 1ps3_ligand.mol2 -o 1ps3_ligand.pdbqt -A 'hydrogens' -U 'nphs_lps_waters'

% <path-to-AutoDockTools>/prepare_receptor4.py -r 1ps3_protein.pdb -o 1ps3_protein.pdbqt -A 'hydrogens' -U 'nphs_lps_waters'

% <path-to-psovina>/psovina --receptor 1ps3_protein.pdbqt --ligand 1ps3_ligand.pdbqt  --center_x  31.951 --center_y 65.5053 --center_z 7.63888 --size_x  33.452 --size_y 27.612  --size_z  35.136  --num_modes 1 --cpu 8

   More test cases can be available soon.

Develop PSOVina

If you are interested in the source code of PSOVina for any academic purposes, please note that the following files were newly developedin our work or modified based on Vina:
        psovina-x.x/src/main/main.cpp
        psovina-x.x/src/lib/pso.h
        psovina-x.x/src/lib/pso.cpp
        psovina-x.x/src/lib/parallel_pso.h
        psovina-x.x/src/lib/parallel_pso.cpp
        psovina-x.x/src/lib/pso_mutate.h
        psovina-x.x/src/lib/pso_mutate.cpp
        psovina-x.x/src/lib/pso_search.h
        psovina-x.x/src/lib/pso_search.cpp


Citations

Please cite our paper if you have used PSOVina or its variants. It would also be nice to let us know that you found PSOVina useful by sending us an email:

For PSOVina 2.0:
Hio Kuan Tai, Siti Azma Jusoh, and Shirley W. I. Siu*. Efficient docking and virtual screening by chaos-embedded PSOVina. (submitted)

For PSOVina2LS:
Hio Kuan Tai, Hin Lin and Shirley W. I. Siu*. Improving the efficiency of PSOVina for protein-ligand docking by two-stage local search. The 2016 IEEE Congress on Evolutionary Computation (CEC), Vancouver, BC, 2016, pp. 770-777.

For PSOVina 1.0:
Marcus C. K. Ng, Simon Fong, and Shirley W. I. Siu*. PSOVina: The Hybrid Particle Swarm Optimization Algorithm for Protein-Ligand Docking. Journal of Bioinformatics and Computational Biology  13 (3), 1541007, 2015.


Contact Us

Developer: Giotto Tai giottotai_[at]yahoo_[dot]_com_[dot]_hk
Allan Linlhang33_[at]_126_[dot]_com
Marcus C. K. Ng  marcus.ckng_[at]_gmail_[dot]_com
Project P.I.: Shirley W. I. Siu shirley_siu_[at]_umac_[dot]_mo
(please remove all underscores)