81
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      QA-RecombineIt: a server for quality assessment and recombination of protein models

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          QA-RecombineIt provides a web interface to assess the quality of protein 3D structure models and to improve the accuracy of models by merging fragments of multiple input models. QA-RecombineIt has been developed for protein modelers who are working on difficult problems, have a set of different homology models and/or de novo models (from methods such as I-TASSER or ROSETTA) and would like to obtain one consensus model that incorporates the best parts into one structure that is internally coherent. An advanced mode is also available, in which one can modify the operation of the fragment recombination algorithm by manually identifying individual fragments or entire models to recombine. Our method produces up to 100 models that are expected to be on the average more accurate than the starting models. Therefore, our server may be useful for crystallographic protein structure determination, where protein models are used for Molecular Replacement to solve the phase problem. To address the latter possibility, a special feature was added to the QA-RecombineIt server. The QA-RecombineIt server can be freely accessed at http://iimcb.genesilico.pl/qarecombineit/.

          Related collections

          Most cited references47

          • Record: found
          • Abstract: found
          • Article: not found

          LIBSVM: A library for support vector machines

          LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this package since the year 2000. The goal is to help users to easily apply SVM to their applications. LIBSVM has gained wide popularity in machine learning and many other areas. In this article, we present all implementation details of LIBSVM. Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Distance-scaled, finite ideal-gas reference state improves structure-derived potentials of mean force for structure selection and stability prediction.

            The distance-dependent structure-derived potentials developed so far all employed a reference state that can be characterized as a residue (atom)-averaged state. Here, we establish a new reference state called the distance-scaled, finite ideal-gas reference (DFIRE) state. The reference state is used to construct a residue-specific all-atom potential of mean force from a database of 1011 nonhomologous (less than 30% homology) protein structures with resolution less than 2 A. The new all-atom potential recognizes more native proteins from 32 multiple decoy sets, and raises an average Z-score by 1.4 units more than two previously developed, residue-specific, all-atom knowledge-based potentials. When only backbone and C(beta) atoms are used in scoring, the performance of the DFIRE-based potential, although is worse than that of the all-atom version, is comparable to those of the previously developed potentials on the all-atom level. In addition, the DFIRE-based all-atom potential provides the most accurate prediction of the stabilities of 895 mutants among three knowledge-based all-atom potentials. Comparison with several physical-based potentials is made.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              AMoRe: an automated package for molecular replacement

              J. Navaza (1994)
                Bookmark

                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                July 2013
                21 May 2013
                21 May 2013
                : 41
                : Web Server issue
                : W389-W397
                Affiliations
                1Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, Trojdena 4, Warsaw PL-02-109, Poland, 2Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children's Hospital, 700 Childrens Drive, Columbus, OH 43205, USA and 3Laboratory of Bioinformatics, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Umultowska 89, Poznan PL-61-614, Poland
                Author notes
                *To whom correspondence should be addressed. Tel: +48 22 597 07 53; Fax: +48 22 597 07 15; Email: marcinp@ 123456genesilico.pl or iamb@ 123456genesilico.pl
                Article
                gkt408
                10.1093/nar/gkt408
                3692112
                23700309
                15634585-3ce7-42c5-88d0-43b312c61b38
                © The Author(s) 2013. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 2 March 2013
                : 20 April 2013
                : 23 April 2013
                Page count
                Pages: 9
                Categories
                Articles
                Custom metadata
                1 July 2013

                Genetics
                Genetics

                Comments

                Comment on this article