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      General overview on structure prediction of twilight-zone proteins

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      , , ,
      Theoretical Biology & Medical Modelling
      BioMed Central

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          Abstract

          Protein structure prediction from amino acid sequence has been one of the most challenging aspects in computational structural biology despite significant progress in recent years showed by critical assessment of protein structure prediction (CASP) experiments. When experimentally determined structures are unavailable, the predictive structures may serve as starting points to study a protein. If the target protein consists of homologous region, high-resolution (typically <1.5 Å) model can be built via comparative modelling. However, when confronted with low sequence similarity of the target protein (also known as twilight-zone protein, sequence identity with available templates is less than 30 %), the protein structure prediction has to be initiated from scratch. Traditionally, twilight-zone proteins can be predicted via threading or ab initio method. Based on the current trend, combination of different methods brings an improved success in the prediction of twilight-zone proteins. In this mini review, the methods, progresses and challenges for the prediction of twilight-zone proteins were discussed.

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          Most cited references71

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          Principles that govern the folding of protein chains.

          C ANFINSEN (1973)
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            Protein structure prediction using Rosetta.

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              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.
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                Author and article information

                Contributors
                kbyin89@gmail.com
                geejun@usm.my
                theamsoon@usm.my
                yeesiew@usm.my
                Journal
                Theor Biol Med Model
                Theor Biol Med Model
                Theoretical Biology & Medical Modelling
                BioMed Central (London )
                1742-4682
                4 September 2015
                4 September 2015
                2015
                : 12
                : 15
                Affiliations
                Institute for Research in Molecular Medicine, Universiti Sains Malaysia, 11800 Minden, Penang Malaysia
                Article
                14
                10.1186/s12976-015-0014-1
                4559291
                26338054
                e28d9dbf-ff77-4e6e-b8f8-3178c4ea8cf3
                © Khor et al. 2015

                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
                : 8 June 2015
                : 27 August 2015
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                © The Author(s) 2015

                Quantitative & Systems biology
                Quantitative & Systems biology

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