PSOVina2LS
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README.md
psovina2ls_1.0.zip

README.md

=======================================================================

PSOVina2LS version 1.0

Allan H. Lin & Giotto H. K. Tai & Shirley W. I. Siu

Computational Biology and Bioinformatics Lab (CBBio)

University of Macau

Visit http://cbbio.cis.umac.mo for more information.

PSOVina2LS was developed based on the framework of PSOVina.

For more information about Vina, please visit http://vina.scripps.edu.

=======================================================================

  1. REQUIRED SOFTWARE

    For successful compilation, please install Boost (version 1.59.0)

    from http://www.boost.org. For preparing molecules for docking,

    please install AutoDockTools (ADT) from http://mgltools.scripps.edu.

  2. INSTALLATION

    The installation basically follows the installation of AutoDock Vina.

    The steps are simple:

    a. unpack the files

    b. cd psovina2ls_1.0/build//release

    c. modify Makefile to suit your system setting

    d. type "make" to compile

    The binary psovina2ls 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.

  3. RUNNING PSOVINA2LS

    You can run psovina2ls as the way you run vina but additional three

    parameters (optional) are used to specify how the PSO algorithm performs

    searching:

    % /psovina2ls

    PSO parameters (optional):

    --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 
    

    2LS parameters (optional): --Cr arg(=15) Roughing condition --R arg(=0.1) Roughing factor

    For example, docking Kifunensine in the Mannosidase enzyme (PDBID 1ps3 from

    the PDBbind v2012 dataset) using PSOVina2LS with default PSO parameters in a

    8-core computer and return the lowest energy prediction:

    % /prepare_ligand4.py -l 1ps3_ligand.mol2 \

    -o 1ps3_ligand.pdbqt -A 'hydrogens' -U 'nphs_lps_waters'

    % /prepare_receptor4.py -r 1ps3_protein.pdb \

    -o 1ps3_protein.pdbqt -A 'hydrogens' -U 'nphs_lps_waters'

    % /psovina2ls \

    --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 downloaded in our web site.

  4. DEVELOP PSOVINA2LS

    If you are interested in the source code of PSOVina2LS for any academic

    purposes, please note that the following files were newly developed

    in our work or modified based on PSOVina:

    src/lib/quasi_newton.cpp

    src/lib/pso_mutate.cpp

  5. CITATION

    Please cite our paper if you have used PSOVina2LS. It would be nice to let us

    know that you found PSOVina2LS useful by sending us an email.

    Allan H. Lin & Giotto H. K. Tai & Shirley W. I. Siu

    Improving The Efficiency of PSOVina for Protein-Ligand Docking By Two-Stage Local Search

    (Submitted)

    Please check out our homepage for the updated citation.

  6. CONTACT US

    Developer: Allan H. Lin lhang33@126.com, Giotto H. K. Tai giottotai@yahoo.com.hk

    Project P.I.: Shirley W. I. Siu shirleysiu@umac.mo

    Computational Biology and Bioinformatics Lab, University of Macau

    http://cbbio.cis.umac.mo

    http://www.cis.umac.mo/~shirleysiu