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      VIPERdb 2: an enhanced and web API enabled relational database for structural virology

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          Abstract

          VIPERdb ( http://viperdb.scripps.edu) is a relational database and a web portal for icosahedral virus capsid structures. Our aim is to provide a comprehensive resource specific to the needs of the virology community, with an emphasis on the description and comparison of derived data from structural and computational analyses of the virus capsids. In the current release, VIPERdb 2, we implemented a useful and novel method to represent capsid protein residues in the icosahedral asymmetric unit (IAU) using azimuthal polar orthographic projections, otherwise known as Φ–Ψ (Phi–Psi) diagrams. In conjunction with a new Application Programming Interface (API), these diagrams can be used as a dynamic interface to the database to map residues (categorized as surface, interface and core residues) and identify family wide conserved residues including hotspots at the interfaces. Additionally, we enhanced the interactivity with the database by interfacing with web-based tools. In particular, the applications Jmol and STRAP were implemented to visualize and interact with the virus molecular structures and provide sequence–structure alignment capabilities. Together with extended curation practices that maintain data uniformity, a relational database implementation based on a schema for macromolecular structures and the APIs provided will greatly enhance the ability to do structural bioinformatics analysis of virus capsids.

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          Most cited references14

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          Knowledge-based protein secondary structure assignment.

          We have developed an automatic algorithm STRIDE for protein secondary structure assignment from atomic coordinates based on the combined use of hydrogen bond energy and statistically derived backbone torsional angle information. Parameters of the pattern recognition procedure were optimized using designations provided by the crystallographers as a standard-of-truth. Comparison to the currently most widely used technique DSSP by Kabsch and Sander (Biopolymers 22:2577-2637, 1983) shows that STRIDE and DSSP assign secondary structural states in 58 and 31% of 226 protein chains in our data sample, respectively, in greater agreement with the specific residue-by-residue definitions provided by the discoverers of the structures while in 11% of the chains, the assignments are the same. STRIDE delineates every 11th helix and every 32nd strand more in accord with published assignments.
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            3DCoffee: combining protein sequences and structures within multiple sequence alignments.

            Most bioinformatics analyses require the assembly of a multiple sequence alignment. It has long been suspected that structural information can help to improve the quality of these alignments, yet the effect of combining sequences and structures has not been evaluated systematically. We developed 3DCoffee, a novel method for combining protein sequences and structures in order to generate high-quality multiple sequence alignments. 3DCoffee is based on TCoffee version 2.00, and uses a mixture of pairwise sequence alignments and pairwise structure comparison methods to generate multiple sequence alignments. We benchmarked 3DCoffee using a subset of HOMSTRAD, the collection of reference structural alignments. We found that combining TCoffee with the threading program Fugue makes it possible to improve the accuracy of our HOMSTRAD dataset by four percentage points when using one structure only per dataset. Using two structures yields an improvement of ten percentage points. The measures carried out on HOM39, a HOMSTRAD subset composed of distantly related sequences, show a linear correlation between multiple sequence alignment accuracy and the ratio of number of provided structure to total number of sequences. Our results suggest that in the case of distantly related sequences, a single structure may not be enough for computing an accurate multiple sequence alignment.
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              STRAP: editor for STRuctural Alignments of Proteins.

              STRAP is a comfortable and extensible tool for the generation and refinement of multiple alignments of protein sequences. Various sequence ordered input file formats are supported. These are the SwissProt-,GenBank-, EMBL-, DSSP- PDB-, MSF-, and plain ASCII text format. The special feature of STRAP is the simple visualization of spatial distances C(alpha)-atoms within the alignment. Thus structural information can easily be incorporated into the sequence alignment and can guide the alignment process in cases of low sequence similarities. Further STRAP is able to manage huge alignments comprising a lot of sequences. The protein viewers and modeling programs INSIGHT, RASMOL and WEBMOL are embedded into STRAP. STRAP is written in JAVA: The well-documented source code can be adapted easily to special requirements. STRAP may become the basis for complex alignment tools in the future.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                January 2009
                January 2009
                3 November 2008
                3 November 2008
                : 37
                : Database issue , Database issue
                : D436-D442
                Affiliations
                1Department of Molecular Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037 and 2Department of Chemistry, Biophysics Program, 930 N. University Ave., University of Michigan, Ann Arbor, MI 48109, USA
                Author notes
                *To whom correspondence should be addressed. Tel: +1 858 784 8191; Fax: +1 858 784 8660; Email: reddyv@ 123456scripps.edu
                Article
                gkn840
                10.1093/nar/gkn840
                2686430
                18981051
                ba3aef6b-9449-48a2-be61-1e431729919f
                © 2008 The Author(s)

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 15 September 2008
                : 13 October 2008
                : 14 October 2008
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                Genetics
                Genetics

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