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      GRAMM-X public web server for protein–protein docking

      research-article
      Author(s): 1 , * , 1 , 2 , *
      Publication date (Electronic):
      Journal: Nucleic Acids Research
      Publisher: Oxford University Press

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          Abstract

          Protein docking software GRAMM-X and its web interface ( http://vakser.bioinformatics.ku.edu/resources/gramm/grammx) extend the original GRAMM Fast Fourier Transformation methodology by employing smoothed potentials, refinement stage, and knowledge-based scoring. The web server frees users from complex installation of database-dependent parallel software and maintaining large hardware resources needed for protein docking simulations. Docking problems submitted to GRAMM-X server are processed by a 320 processor Linux cluster. The server was extensively tested by benchmarking, several months of public use, and participation in the CAPRI server track.

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          ClusPro: an automated docking and discrimination method for the prediction of protein complexes.

          S. R. Comeau, D. W. Gatchell, S Vajda … (2004)
          Predicting protein interactions is one of the most challenging problems in functional genomics. Given two proteins known to interact, current docking methods evaluate billions of docked conformations by simple scoring functions, and in addition to near-native structures yield many false positives, i.e. structures with good surface complementarity but far from the native. We have developed a fast algorithm for filtering docked conformations with good surface complementarity, and ranking them based on their clustering properties. The free energy filters select complexes with lowest desolvation and electrostatic energies. Clustering is then used to smooth the local minima and to select the ones with the broadest energy wells-a property associated with the free energy at the binding site. The robustness of the method was tested on sets of 2000 docked conformations generated for 48 pairs of interacting proteins. In 31 of these cases, the top 10 predictions include at least one near-native complex, with an average RMSD of 5 A from the native structure. The docking and discrimination method also provides good results for a number of complexes that were used as targets in the Critical Assessment of PRedictions of Interactions experiment. The fully automated docking and discrimination server ClusPro can be found at http://structure.bu.edu
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            Molecular surface recognition: determination of geometric fit between proteins and their ligands by correlation techniques.

            E Katchalski-Katzir, Edward Eisenstein, Ilya A. Vakser … (1992)
            A geometric recognition algorithm was developed to identify molecular surface complementarity. It is based on a purely geometric approach and takes advantage of techniques applied in the field of pattern recognition. The algorithm involves an automated procedure including (i) a digital representation of the molecules (derived from atomic coordinates) by three-dimensional discrete functions that distinguishes between the surface and the interior; (ii) the calculation, using Fourier transformation, of a correlation function that assesses the degree of molecular surface overlap and penetration upon relative shifts of the molecules in three dimensions; and (iii) a scan of the relative orientations of the molecules in three dimensions. The algorithm provides a list of correlation values indicating the extent of geometric match between the surfaces of the molecules; each of these values is associated with six numbers describing the relative position (translation and rotation) of the molecules. The procedure is thus equivalent to a six-dimensional search but much faster by design, and the computation time is only moderately dependent on molecular size. The procedure was tested and validated by using five known complexes for which the correct relative position of the molecules in the respective adducts was successfully predicted. The molecular pairs were deoxyhemoglobin and methemoglobin, tRNA synthetase-tyrosinyl adenylate, aspartic proteinase-peptide inhibitor, and trypsin-trypsin inhibitor. A more realistic test was performed with the last two pairs by using the structures of uncomplexed aspartic proteinase and trypsin inhibitor, respectively. The results are indicative of the extent of conformational changes in the molecules tolerated by the algorithm.
            Article 0 comments Cited 169 times – based on 0 reviews     Review now
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              Development and testing of an automated approach to protein docking.

              Andrei Tovchigrechko, Ilya A. Vakser (2005)
              A new version of GRAMM was applied to Targets 14, 18, and 19 in CAPRI Round 5. The predictions were generated without manual intervention. Ten top-ranked matches for each target were submitted. The docking was performed by a rigid-body procedure with a smoothed potential function to accommodate conformational changes. The first stage was a global search on a fine grid with a projection of a smoothed Lennard-Jones potential. The top predictions from the first stage were subjected to the conjugate gradient minimization with the same smoothed potential. The resulting local minima were reranked according to the weighted sum of Lennard-Jones potential, pairwise residue-residue statistical preferences, cluster occupancy, and the degree of the evolutionary conservation of the predicted interface. For Targets 14 and 18, the conformation of the complex was predicted with root-mean-square deviation (RMSD) of the ligand interface atoms 0.68 A and 1.88 A correspondingly. For Target 19, the interface areas on both proteins were correctly predicted. The performance of the procedure was also analyzed on the benchmark of bound-unbound protein complexes. The results show that, on average, conformations of only 3 side-chains need to be optimized during docking of unbound structures before the backbone changes become a limiting factor. The GRAMM-X docking server is available for public use at http://www.bioinformatics.ku.edu.
              Article 0 comments Cited 45 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Nucleic Acids Res
                Journal ID (publisher-id): Nucleic Acids Research
                Title: Nucleic Acids Research
                Publisher: Oxford University Press
                ISSN (Print): 0305-1048
                ISSN (Electronic): 1362-4962
                Publication date Collection: 01 July 2006
                Publication date (Print): 01 July 2006
                Publication date (Electronic): 14 July 2006
                Volume: 34
                Issue: Web Server issue
                Pages: W310-W314
                Affiliations
                1Center for Bioinformatics, The University of Kansas 2030 Becker Drive, Lawrence, KS 66047, USA
                2Department of Molecular Biosciences, The University of Kansas 2030 Becker Drive, Lawrence, KS 66047, USA
                Author notes
                *To whom correspondence should be addressed. Tel: 785 864 1057; Fax: 785 864 5558; Email: andrey@ 123456ku.edu

                *Correspondence may also be addressed to Ilya A. Vakser. Tel: 785 864 1057; Fax: 785 864 5558; Email: vakser@ 123456ku.edu

                Article
                DOI: 10.1093/nar/gkl206
                PMC ID: 1538913
                PubMed ID: 16845016
                SO-VID: 2a179f64-f047-44c9-b270-37cd491dbd6b
                Copyright © © The Author 2006. Published by Oxford University Press. All rights reserved
                License:

                The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

                History
                Date received : 15 February 2006
                Date revision received : 22 March 2006
                Date accepted : 22 March 2006
                Categories
                Subject: Article

                ScienceOpen disciplines: Genetics
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                ScienceOpen disciplines: Genetics

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