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      Inferences from structural comparison: flexibility, secondary structure wobble and sequence alignment optimization

      research-article
      1 , 1 ,
      BMC Bioinformatics
      BioMed Central
      Proceedings of the Ninth Annual MCBIOS Conference. Dealing with the Omics Data Deluge
      17-18 February 2012

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          Abstract

          Background

          Work on protein structure prediction is very useful in biological research. To evaluate their accuracy, experimental protein structures or their derived data are used as the 'gold standard'. However, as proteins are dynamic molecular machines with structural flexibility such a standard may be unreliable.

          Results

          To investigate the influence of the structure flexibility, we analysed 3,652 protein structures of 137 unique sequences from 24 protein families. The results showed that (1) the three-dimensional (3D) protein structures were not rigid: the root-mean-square deviation (RMSD) of the backbone C α of structures with identical sequences was relatively large, with the average of the maximum RMSD from each of the 137 sequences being 1.06 Å; (2) the derived data of the 3D structure was not constant, e.g. the highest ratio of the secondary structure wobble site was 60.69%, with the sequence alignments from structural comparisons of two proteins in the same family sometimes being completely different.

          Conclusion

          Proteins may have several stable conformations and the data derived from resolved structures as a 'gold standard' should be optimized before being utilized as criteria to evaluate the prediction methods, e.g. sequence alignment from structural comparison. Helix/β-sheet transition exists in normal free proteins. The coil ratio of the 3D structure could affect its resolution as determined by X-ray crystallography.

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          Most cited references24

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          Satisfying hydrogen bonding potential in proteins.

          We have analysed the frequency with which potential hydrogen bond donors and acceptors are satisfied in protein molecules. There are a small percentage of nitrogen or oxygen atoms that do not form hydrogen bonds with either solvent or protein atoms, when standard criteria are used. For high resolution structures 9.5% and 5.1% of buried main-chain nitrogen and oxygen atoms, respectively, fail to hydrogen bond under our standard criteria, representing 5.8% and 2.1% of all main-chain nitrogen and oxygen atoms. We find that as the resolution of the data improves, the percentages fall. If the hydrogen bond criteria are relaxed many of these unsatisfied atoms form weak hydrogen bonds. However, there remain some buried atoms (1.3% NH and 1.8% CO) that fail to hydrogen bond without any immediately obvious compensating interactions.
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            Protein structure prediction and structural genomics.

            Genome sequencing projects are producing linear amino acid sequences, but full understanding of the biological role of these proteins will require knowledge of their structure and function. Although experimental structure determination methods are providing high-resolution structure information about a subset of the proteins, computational structure prediction methods will provide valuable information for the large fraction of sequences whose structures will not be determined experimentally. The first class of protein structure prediction methods, including threading and comparative modeling, rely on detectable similarity spanning most of the modeled sequence and at least one known structure. The second class of methods, de novo or ab initio methods, predict the structure from sequence alone, without relying on similarity at the fold level between the modeled sequence and any of the known structures. In this Viewpoint, we begin by describing the essential features of the methods, the accuracy of the models, and their application to the prediction and understanding of protein function, both for single proteins and on the scale of whole genomes. We then discuss the important role that protein structure prediction methods play in the growing worldwide effort in structural genomics.
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              The impact of structural genomics: expectations and outcomes.

              Structural genomics (SG) projects aim to expand our structural knowledge of biological macromolecules while lowering the average costs of structure determination. We quantitatively analyzed the novelty, cost, and impact of structures solved by SG centers, and we contrast these results with traditional structural biology. The first structure identified in a protein family enables inference of the fold and of ancient relationships to other proteins; in the year ending 31 January 2005, about half of such structures were solved at a SG center rather than in a traditional laboratory. Furthermore, the cost of solving a structure at the most efficient SG center in the United States has dropped to one-quarter of the estimated cost of solving a structure by traditional methods. However, the efficiency of the top structural biology laboratories-even though they work on very challenging structures-is comparable to that of SG centers; moreover, traditional structural biology papers are cited significantly more often, suggesting greater current impact.
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                Author and article information

                Conference
                BMC Bioinformatics
                BMC Bioinformatics
                BMC Bioinformatics
                BioMed Central
                1471-2105
                2012
                11 September 2012
                : 13
                : Suppl 15
                : S12
                Affiliations
                [1 ]State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing 100094, People's Republic of China
                Article
                1471-2105-13-S15-S12
                10.1186/1471-2105-13-S15-S12
                3439719
                23046301
                3edc9bca-6164-4529-8c81-01f1ec554dd2
                Copyright ©2012 Zhang and Su; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Proceedings of the Ninth Annual MCBIOS Conference. Dealing with the Omics Data Deluge
                Oxford, MS, USA
                17-18 February 2012
                History
                Categories
                Proceedings

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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