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      An effective sequence-alignment-free superpositioning of pairwise or multiple structures with missing data

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          Abstract

          Background

          Superpositioning is an important problem in structural biology. Determining an optimal superposition requires a one-to-one correspondence between the atoms of two proteins structures. However, in practice, some atoms are missing from their original structures. Current superposition implementations address the missing data crudely by ignoring such atoms from their structures.

          Results

          In this paper, we propose an effective method for superpositioning pairwise and multiple structures without sequence alignment. It is a two-stage procedure including data reduction and data registration.

          Conclusions

          Numerical experiments demonstrated that our method is effective and efficient. The code package of protein structure superposition method for addressing the cases with missing data is implemented by MATLAB, and it is freely available from: http://sourceforge.net/projects/pssm123/files/?source=navbar

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13015-016-0079-3) contains supplementary material, which is available to authorized users.

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          Most cited references26

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          A discussion of the solution for the best rotation to relate two sets of vectors

          W Kabsch (1978)
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            SuperPose: a simple server for sophisticated structural superposition.

            The SuperPose web server rapidly and robustly calculates both pairwise and multiple protein structure superpositions using a modified quaternion eigenvalue approach. SuperPose generates sequence alignments, structure alignments, PDB (Protein Data Bank) coordinates and RMSD statistics, as well as difference distance plots and images (both static and interactive) of the superimposed molecules. SuperPose employs a simple interface that requires only PDB files or accession numbers as input. All other superposition decisions are made by the program. SuperPose is uniquely able to superimpose structures that differ substantially in sequence, size or shape. It is also capable of handling a much larger range of superposition queries and situations than many standalone programs and yields results that are intuitively more in agreement with known biological or structural data. The SuperPose web server is freely accessible at http://wishart.biology.ualberta.ca/SuperPose/.
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              Multiple sequence alignment.

              Multiple sequence alignments are an essential tool for protein structure and function prediction, phylogeny inference and other common tasks in sequence analysis. Recently developed systems have advanced the state of the art with respect to accuracy, ability to scale to thousands of proteins and flexibility in comparing proteins that do not share the same domain architecture. New multiple alignment benchmark databases include PREFAB, SABMARK, OXBENCH and IRMBASE. Although CLUSTALW is still the most popular alignment tool to date, recent methods offer significantly better alignment quality and, in some cases, reduced computational cost.
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                Author and article information

                Contributors
                jblu@lsec.cc.ac.cn
                xuguo@lsec.cc.ac.cn
                zsh@amss.ac.cn
                bzlu@lsec.cc.ac.cn
                Journal
                Algorithms Mol Biol
                Algorithms Mol Biol
                Algorithms for Molecular Biology : AMB
                BioMed Central (London )
                1748-7188
                21 June 2016
                21 June 2016
                2016
                : 11
                : 18
                Affiliations
                [ ]Human Genetics Resource Center, National Research Institute for Family Planning, Beijing, 100081 China
                [ ]Graduate School of Peking Union Medical College, Beijing, 100730 China
                [ ]National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190 China
                Article
                79
                10.1186/s13015-016-0079-3
                4915111
                27330544
                6edd06dd-95b2-4519-82c8-5234bbdc3cb6
                © The Author(s) 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 22 October 2015
                : 18 May 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Funded by: 863 program
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 11321061
                Award ID: 61379092
                Award Recipient :
                Funded by: Outstanding Young Scientist Program of CAS
                Funded by: the State Key Laboratory of Scientific/Engineering Computing, the Key Laboratory of Random Complex Structures and Data and the National Center for Mathematics and Interdisciplinary Sciences at CAS.
                Funded by: National Natural Science Foundation of China (CN)
                Award ID: 91530102
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 21573274
                Award Recipient :
                Funded by: the CAS Program for Cross and Cooperative Team of the Science and Technology Innovation
                Categories
                Research
                Custom metadata
                © The Author(s) 2016

                Molecular biology
                superposition,protein structure alignment,iterative closest point
                Molecular biology
                superposition, protein structure alignment, iterative closest point

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