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EN
The Protein Data Bank (PDB) undergoes an exponential expansion in terms of the number of macromolecular structures deposited every year. A pivotal question is how this rapid growth of structural information improves the quality of three-dimensional models constructed by contemporary bioinformatics approaches. To address this problem, we performed a retrospective analysis of the structural coverage of a representative set of proteins using remote homology detected by COMPASS and HHpred. We show that the number of proteins whose structures can be confidently predicted increased during a 9-year period between 2005 and 2014 on account of the PDB growth alone. Nevertheless, this encouraging trend slowed down noticeably around the year 2008 and has yielded insignificant improvements ever since. At the current pace, it is unlikely that the protein structure prediction problem will be solved in the near future using existing template-based modeling techniques. Therefore, further advances in experimental structure determination, qualitatively better approaches in fold recognition, and more accurate template-free structure prediction methods are desperately needed.
EN
Template-based modeling (termed also Comparative or Homology Modeling) of a protein structure is one of ubiquitous tasks of structural bioinfor matics. The method can deliver model structures important for testing biological hypotheses, virtual docking and drug design. The performance of these methods is evaluated every two years during a Critical Assessment of Protein Structure Prediction (CASP) experiment. In this contribution we present a new automated protocol for template-base d modeling, which combines computational tools recently developed in our laboratory: the dat abase of protein domain structures (BDDB) with one dimensional and three dimensional thread ing applications. The protocol was tested during a CASP11 experiment.
EN
The article describes the results of studies on the similarity of protein structures generated by the sequences differing by only one amino acid residue. On this basis, the table of amino acid residue similarities has been determined. Similar residue sequences should generate similar protein structures – on this basis act such classification systems as SCOP and CATH. These systems detect the existence of domains of different lengths in the sequences. These domains are characteristic for proteins which exist in organisms. Synthesized proteins are not related to any other proteins and may contain domains that can not be classified by traditional methods. The solution to this problem may be to analyzing all the possible combinations of amino acid residues and observation of secondary structures generated by this sequence in exising proteins. Analyzing the structural differences in the sequences differing only by one amino acid residue gives information on the structural similarity of these amino acids. The task of analyzing all possible combinations of amino acid sequence is possible only for short stretches, because for longer stretches the same sequence cannot be found in the existing databases. So the second question is: how long the sequence should be analyzed in order to enable determining the local backbone structure. For this purpose, segments of known proteins with a length of 3 and 5 amino acid residues are analyzed.
EN
The force field and Monte Carlo sampling method of our recently developed reduced model of proteins is described. Recent applications of the models include ab initio structure prediction for small globular proteins, modeling of protein structure based on distantly homologous (or analogous) structural templates, assembly of protein structure from sparse experimental data, and computational studies of protein folding dynamics and thermodynamics. The newest application, described in this paper, enables the prediction of low-to-moderate resolution coordinates of the parts of protein structure that are missed in incomplete PDB files.
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