Literature DB >> 17853449

The SKE-DOCK server and human teams based on a combined method of shape complementarity and free energy estimation.

Genki Terashi1, Mayuko Takeda-Shitaka, Kazuhiko Kanou, Mitsuo Iwadate, Daisuke Takaya, Hideaki Umeyama.   

Abstract

We participated in rounds 6-12 of the critical assessment of predicted interaction (CAPRI) contest as the SKE-DOCK server and human teams. The SKE-DOCK server is based on simple geometry docking and a knowledge base scoring function. The procedure is summarized in the following three steps: (1) protein docking according to shape complementarity, (2) evaluating complex models, and (3) repacking side-chain of models. The SKE-DOCK server did not make use of biological information. On the other hand, the human team tried various intervention approaches. In this article, we describe in detail the processes of the SKE-DOCK server, together with results and reasons for success and failure. Good predicted models were obtained for target 25 by both the SKE-DOCK server and human teams. When the modeled receptor proteins were superimposed on the experimental structures, the smallest Ligand-rmsd values corresponding to the rmsd between the model and experimental structures were 3.307 and 3.324 A, respectively. Moreover, the two teams obtained 4 and 2 acceptable models for target 25. The overall result for both the SKE-DOCK server and human teams was medium accuracy for one (Target 25) out of nine targets. (c) 2007 Wiley-Liss, Inc.

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Year:  2007        PMID: 17853449     DOI: 10.1002/prot.21772

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  6 in total

Review 1.  Software for molecular docking: a review.

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

2.  The ClusPro web server for protein-protein docking.

Authors:  Dima Kozakov; David R Hall; Bing Xia; Kathryn A Porter; Dzmitry Padhorny; Christine Yueh; Dmitri Beglov; Sandor Vajda
Journal:  Nat Protoc       Date:  2017-01-12       Impact factor: 13.491

Review 3.  Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics.

Authors:  Tatiana Maximova; Ryan Moffatt; Buyong Ma; Ruth Nussinov; Amarda Shehu
Journal:  PLoS Comput Biol       Date:  2016-04-28       Impact factor: 4.475

4.  HopDock: a probabilistic search algorithm for decoy sampling in protein-protein docking.

Authors:  Irina Hashmi; Amarda Shehu
Journal:  Proteome Sci       Date:  2013-11-07       Impact factor: 2.480

Review 5.  Evolution of In Silico Strategies for Protein-Protein Interaction Drug Discovery.

Authors:  Stephani Joy Y Macalino; Shaherin Basith; Nina Abigail B Clavio; Hyerim Chang; Soosung Kang; Sun Choi
Journal:  Molecules       Date:  2018-08-06       Impact factor: 4.411

6.  Refinement of protein-protein complexes in contact map space with metadynamics simulations.

Authors:  Erik Pfeiffenberger; Paul A Bates
Journal:  Proteins       Date:  2018-10-30
  6 in total

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