18
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Computational analyses of protein coded by rice ( Oryza sativa japonica) cDNA (GI: 32984786) indicate lectin like Ca 2+ binding properties for Eicosapenta Peptide Repeats (EPRs)

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      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

          Eicosapenta peptide repeats (EPRs) occur exclusively in flowering plant genomes and exhibit very high amino acid residue conservation across occurrence. DNA and amino acid sequence searches yielded no indications about the function due to absence of similarity to known sequences. Tertiary structure of an EPR protein coded by rice ( Oryza sativa japonica) cDNA (GI: 32984786) was determined based on ab initio methodology in order to draw clues on functional significance of EPRs. The resultant structure comprised of seven α-helices and thirteen anti-parallel β-sheets. Surface-mapping of conserved residues onto the structure deduced that (i) regions equivalent to β α4- the primary function of EPR protein could be Ca 2+ binding, and (iii) the putative EPR Ca 2+ binding domain is structurally similar to calcium-binding domains of plant lectins. Additionally, the phylogenetic analysis showed an evolving taxa-specific distribution of EPR proteins observed in some GNA-like lectins.

          Related collections

          Most cited references11

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

          Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions.

          We explore the ability of a simple simulated annealing procedure to assemble native-like structures from fragments of unrelated protein structures with similar local sequences using Bayesian scoring functions. Environment and residue pair specific contributions to the scoring functions appear as the first two terms in a series expansion for the residue probability distributions in the protein database; the decoupling of the distance and environment dependencies of the distributions resolves the major problems with current database-derived scoring functions noted by Thomas and Dill. The simulated annealing procedure rapidly and frequently generates native-like structures for small helical proteins and better than random structures for small beta sheet containing proteins. Most of the simulated structures have native-like solvent accessibility and secondary structure patterns, and thus ensembles of these structures provide a particularly challenging set of decoys for evaluating scoring functions. We investigate the effects of multiple sequence information and different types of conformational constraints on the overall performance of the method, and the ability of a variety of recently developed scoring functions to recognize the native-like conformations in the ensembles of simulated structures.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            ConSurf: identification of functional regions in proteins by surface-mapping of phylogenetic information.

            We recently developed algorithmic tools for the identification of functionally important regions in proteins of known three dimensional structure by estimating the degree of conservation of the amino-acid sites among their close sequence homologues. Projecting the conservation grades onto the molecular surface of these proteins reveals patches of highly conserved (or occasionally highly variable) residues that are often of important biological function. We present a new web server, ConSurf, which automates these algorithmic tools. ConSurf may be used for high-throughput characterization of functional regions in proteins. The ConSurf web server is available at:http://consurf.tau.ac.il. A set of examples is available at http://consurf.tau.ac.il under 'GALLERY'.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Fast prediction and visualization of protein binding pockets with PASS.

              PASS (Putative Active Sites with Spheres) is a simple computational tool that uses geometry to characterize regions of buried volume in proteins and to identify positions likely to represent binding sites based upon the size, shape, and burial extent of these volumes. Its utility as a predictive tool for binding site identification is tested by predicting known binding sites of proteins in the PDB using both complexed macromolecules and their corresponding apoprotein structures. The results indicate that PASS can serve as a front-end to fast docking. The main utility of PASS lies in the fact that it can analyze a moderate-size protein (approximately 30 kDa) in under 20 s, which makes it suitable for interactive molecular modeling, protein database analysis, and aggressive virtual screening efforts. As a modeling tool, PASS (i) rapidly identifies favorable regions of the protein surface, (ii) simplifies visualization of residues modulating binding in these regions, and (iii) provides a means of directly visualizing buried volume, which is often inferred indirectly from curvature in a surface representation. PASS produces output in the form of standard PDB files, which are suitable for any modeling package, and provides script files to simplify visualization in Cerius2, InsightII, MOE, Quanta, RasMol, and Sybyl. PASS is freely available to all.
                Bookmark

                Author and article information

                Journal
                Bioinformation
                Bioinformation
                Bioinformation
                Bioinformation
                Biomedical Informatics
                0973-8894
                0973-2063
                2014
                19 February 2014
                : 10
                : 2
                : 63-67
                Affiliations
                [1 ]Division of Genomic Resources, National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi INDIA
                [2 ]Laboratory of Molecular Genetics, Centre for DNA Fingerprinting and Diagnostics, Hyderabad INDIA
                Author notes
                [* ]Sunil Archak: sunil.archak@ 123456gmail.com Phone: +91-11-25846074; Fax: +91-11-25842495
                Article
                97320630010063
                10.6026/97320630010063
                3937577
                24616556
                9d2e8bfe-e0ac-49f5-8de3-a0c432ceba28
                © 2014 Biomedical Informatics

                This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.

                History
                : 19 January 2014
                : 26 January 2014
                Categories
                Hypothesis

                Bioinformatics & Computational biology
                ab initio structure prediction,function prediction,repeat proteins,surface mapping,taxa-specific

                Comments

                Comment on this article