Literature DB >> 17986206

pso@autodock: a fast flexible molecular docking program based on Swarm intelligence.

Vigneshwaran Namasivayam1, Robert Günther.   

Abstract

On the quest of novel therapeutics, molecular docking methods have proven to be valuable tools for screening large libraries of compounds determining the interactions of potential drugs with the target proteins. A widely used docking approach is the simulation of the docking process guided by a binding energy function. On the basis of the molecular docking program autodock, we present pso@autodock as a tool for fast flexible molecular docking. Our novel Particle Swarm Optimization (PSO) algorithms varCPSO and varCPSO-ls are suited for rapid docking of highly flexible ligands. Thus, a ligand with 23 rotatable bonds was successfully docked within as few as 100 000 computing steps (rmsd = 0.87 A), which corresponds to only 10% of the computing time demanded by autodock. In comparison to other docking techniques as gold 3.0, dock 6.0, flexx 2.2.0, autodock 3.05, and sodock, pso@autodock provides the smallest rmsd values for 12 in 37 protein-ligand complexes. The average rmsd value of 1.4 A is significantly lower then those obtained with the other docking programs, which are all above 2.0 A. Thus, pso@autodock is suggested as a highly efficient docking program in terms of speed and quality for flexible peptide-protein docking and virtual screening studies.

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Year:  2007        PMID: 17986206     DOI: 10.1111/j.1747-0285.2007.00588.x

Source DB:  PubMed          Journal:  Chem Biol Drug Des        ISSN: 1747-0277            Impact factor:   2.817


  18 in total

1.  Structure-Activity Relationship of Purine and Pyrimidine Nucleotides as Ecto-5'-Nucleotidase (CD73) Inhibitors.

Authors:  Anna Junker; Christian Renn; Clemens Dobelmann; Vigneshwaran Namasivayam; Shanu Jain; Karolina Losenkova; Heikki Irjala; Sierra Duca; Ramachandran Balasubramanian; Saibal Chakraborty; Frederik Börgel; Herbert Zimmermann; Gennady G Yegutkin; Christa E Müller; Kenneth A Jacobson
Journal:  J Med Chem       Date:  2019-03-21       Impact factor: 7.446

Review 2.  Software for molecular docking: a review.

Authors:  Nataraj S Pagadala; Khajamohiddin Syed; Jack Tuszynski
Journal:  Biophys Rev       Date:  2017-01-16

3.  A comparison of various optimization algorithms of protein-ligand docking programs by fitness accuracy.

Authors:  Liyong Guo; Zhiqiang Yan; Xiliang Zheng; Liang Hu; Yongliang Yang; Jin Wang
Journal:  J Mol Model       Date:  2014-06-17       Impact factor: 1.810

4.  SwarmDock and the use of normal modes in protein-protein docking.

Authors:  Iain H Moal; Paul A Bates
Journal:  Int J Mol Sci       Date:  2010-09-28       Impact factor: 5.923

5.  The AutoDock suite at 30.

Authors:  David S Goodsell; Michel F Sanner; Arthur J Olson; Stefano Forli
Journal:  Protein Sci       Date:  2020-09-12       Impact factor: 6.725

Review 6.  Advances and challenges in protein-ligand docking.

Authors:  Sheng-You Huang; Xiaoqin Zou
Journal:  Int J Mol Sci       Date:  2010-08-18       Impact factor: 5.923

7.  Discovery of potent nucleotide pyrophosphatase/phosphodiesterase3 (NPP3) inhibitors with ancillary carbonic anhydrase inhibition for cancer (immuno)therapy.

Authors:  Sang-Yong Lee; Vigneshwaran Namasivayam; Nader M Boshta; Arianna Perotti; Salahuddin Mirza; Silvia Bua; Claudiu T Supuran; Christa E Müller
Journal:  RSC Med Chem       Date:  2021-06-16

8.  DARC 2.0: Improved Docking and Virtual Screening at Protein Interaction Sites.

Authors:  Ragul Gowthaman; Sergey Lyskov; John Karanicolas
Journal:  PLoS One       Date:  2015-07-16       Impact factor: 3.240

9.  Energy Landscape Topography Reveals the Underlying Link Between Binding Specificity and Activity of Enzymes.

Authors:  Wen-Ting Chu; Jin Wang
Journal:  Sci Rep       Date:  2016-06-14       Impact factor: 4.379

10.  Attracting cavities for docking. Replacing the rough energy landscape of the protein by a smooth attracting landscape.

Authors:  Vincent Zoete; Thierry Schuepbach; Christophe Bovigny; Prasad Chaskar; Antoine Daina; Ute F Röhrig; Olivier Michielin
Journal:  J Comput Chem       Date:  2015-11-12       Impact factor: 3.376

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