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      SwarmDock and the Use of Normal Modes in Protein-Protein Docking

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          Abstract

          Here is presented an investigation of the use of normal modes in protein-protein docking, both in theory and in practice. Upper limits of the ability of normal modes to capture the unbound to bound conformational change are calculated on a large test set, with particular focus on the binding interface, the subset of residues from which the binding energy is calculated. Further, the SwarmDock algorithm is presented, to demonstrate that the modelling of conformational change as a linear combination of normal modes is an effective method of modelling flexibility in protein-protein docking.

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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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            FireDock: fast interaction refinement in molecular docking.

            Nelly Andrusier, Ruth Nussinov, Haim J. Wolfson (2007)
            Here, we present FireDock, an efficient method for the refinement and rescoring of rigid-body docking solutions. The refinement process consists of two main steps: (1) rearrangement of the interface side-chains and (2) adjustment of the relative orientation of the molecules. Our method accounts for the observation that most interface residues that are important in recognition and binding do not change their conformation significantly upon complexation. Allowing full side-chain flexibility, a common procedure in refinement methods, often causes excessive conformational changes. These changes may distort preformed structural signatures, which have been shown to be important for binding recognition. Here, we restrict side-chain movements, and thus manage to reduce the false-positive rate noticeably. In the later stages of our procedure (orientation adjustments and scoring), we smooth the atomic radii. This allows for the minor backbone and side-chain movements and increases the sensitivity of our algorithm. FireDock succeeds in ranking a near-native structure within the top 15 predictions for 83% of the 30 enzyme-inhibitor test cases, and for 78% of the 18 semiunbound antibody-antigen complexes. Our refinement procedure significantly improves the ranking of the rigid-body PatchDock algorithm for these cases. The FireDock program is fully automated. In particular, to our knowledge, FireDock's prediction results are comparable to current state-of-the-art refinement methods while its running time is significantly lower. The method is available at http://bioinfo3d.cs.tau.ac.il/FireDock/. 2007 Wiley-Liss, Inc.
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              A graph-theory algorithm for rapid protein side-chain prediction.

              Adrian A Canutescu, Andrew A Shelenkov, Roland L. Dunbrack (2003)
              Fast and accurate side-chain conformation prediction is important for homology modeling, ab initio protein structure prediction, and protein design applications. Many methods have been presented, although only a few computer programs are publicly available. The SCWRL program is one such method and is widely used because of its speed, accuracy, and ease of use. A new algorithm for SCWRL is presented that uses results from graph theory to solve the combinatorial problem encountered in the side-chain prediction problem. In this method, side chains are represented as vertices in an undirected graph. Any two residues that have rotamers with nonzero interaction energies are considered to have an edge in the graph. The resulting graph can be partitioned into connected subgraphs with no edges between them. These subgraphs can in turn be broken into biconnected components, which are graphs that cannot be disconnected by removal of a single vertex. The combinatorial problem is reduced to finding the minimum energy of these small biconnected components and combining the results to identify the global minimum energy conformation. This algorithm is able to complete predictions on a set of 180 proteins with 34342 side chains in <7 min of computer time. The total chi(1) and chi(1 + 2) dihedral angle accuracies are 82.6% and 73.7% using a simple energy function based on the backbone-dependent rotamer library and a linear repulsive steric energy. The new algorithm will allow for use of SCWRL in more demanding applications such as sequence design and ab initio structure prediction, as well addition of a more complex energy function and conformational flexibility, leading to increased accuracy.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Int J Mol Sci
                Journal ID (publisher-id): ijms
                Title: International Journal of Molecular Sciences
                Publisher: Molecular Diversity Preservation International (MDPI)
                ISSN (Electronic): 1422-0067
                Publication date Collection: 2010
                Publication date (Electronic): 28 September 2010
                Volume: 11
                Issue: 10
                Pages: 3623-3648
                Affiliations
                Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, Lincoln’s Inn Fields Laboratories, 44 Lincoln’s Inn Fields, London, WC2A 3LY, UK
                Author notes
                * Author to whom correspondence should be addressed; E-Mail: Paul.Bates@ 123456cancer.org.uk ; Tel.: +44-20-7269-3223; Fax: +44-20-7269-3258.
                Article
                Publisher ID: ijms-11-03623
                DOI: 10.3390/ijms11103623
                PMC ID: 2996808
                PubMed ID: 21152290
                SO-VID: 2ef5a356-43ec-419e-8f3a-c442de115132
                Copyright © © 2010 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.
                License:

                This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/3.0/).

                History
                Date received : 2 July 2010
                Date revision received : 29 July 2010
                Date accepted : 16 September 2010
                Categories
                Subject: Article

                ScienceOpen disciplines: Molecular biology
                Keywords: rtb,particle swarm optimisation,capri,pso,elastic network model,normal mode analysis,protein flexibility
                Data availability:
                ScienceOpen disciplines: Molecular biology
                Keywords: rtb, particle swarm optimisation, capri, pso, elastic network model, normal mode analysis, protein flexibility

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