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      SMOG@ctbp: simplified deployment of structure-based models in GROMACS

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          Abstract

          Molecular dynamics simulations with coarse-grained and/or simplified Hamiltonians are an effective means of capturing the functionally important long-time and large-length scale motions of proteins and RNAs. Structure-based Hamiltonians, simplified models developed from the energy landscape theory of protein folding, have become a standard tool for investigating biomolecular dynamics. SMOG@ 123456ctbp is an effort to simplify the use of structure-based models. The purpose of the web server is two fold. First, the web tool simplifies the process of implementing a well-characterized structure-based model on a state-of-the-art, open source, molecular dynamics package, GROMACS. Second, the tutorial-like format helps speed the learning curve of those unfamiliar with molecular dynamics. A web tool user is able to upload any multi-chain biomolecular system consisting of standard RNA, DNA and amino acids in PDB format and receive as output all files necessary to implement the model in GROMACS. Both C α and all-atom versions of the model are available. SMOG@ 123456ctbp resides at http://smog.ucsd.edu.

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          Most cited references12

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          Topological and energetic factors: what determines the structural details of the transition state ensemble and "en-route" intermediates for protein folding? An investigation for small globular proteins.

          Recent experimental results suggest that the native fold, or topology, plays a primary role in determining the structure of the transition state ensemble, at least for small, fast-folding proteins. To investigate the extent of the topological control of the folding process, we studied the folding of simplified models of five small globular proteins constructed using a Go-like potential to retain the information about the native structures but drastically reduce the energetic frustration and energetic heterogeneity among residue-residue native interactions. By comparing the structure of the transition state ensemble (experimentally determined by Phi-values) and of the intermediates with those obtained using our models, we show that these energetically unfrustrated models can reproduce the global experimentally known features of the transition state ensembles and "en-route" intermediates, at least for the analyzed proteins. This result clearly indicates that, as long as the protein sequence is sufficiently minimally frustrated, topology plays a central role in determining the folding mechanism. Copyright 2000 Academic Press.
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            Protein folding funnels: a kinetic approach to the sequence-structure relationship.

            A lattice model of protein folding is developed to distinguish between amino acid sequences that do and do not fold into unique conformations. Although Monte Carlo simulations provide insights into the long-time processes involved in protein folding, these simulations cannot systematically chart the conformational energy surface that enables folding. By assuming that protein folding occurs after chain collapse, a kinetic map of important pathways on this surface is constructed through the use of an analytical theory of probability flow. Convergent kinetic pathways, or "folding funnels," guide folding to a unique, stable, native conformation. Solution of the probability flow equations is facilitated by limiting treatment to diffusion between geometrically similar collapsed conformers. Similarity is measured in terms of a reconfigurational distance. Two specific amino acid sequences are deemed foldable and nonfoldable because one gives rise to a single, large folding funnel leading to a native conformation and the other has multiple pathways leading to several stable conformers. Monte Carlo simulations demonstrate that folding funnel calculations accurately predict the fact of and the pathways involved in folding-specific sequences. The existence of folding funnels for specific sequences suggests that geometrically related families of stable, collapsed conformers fulfill kinetic and thermodynamic requirements of protein folding.
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              Spin glasses and the statistical mechanics of protein folding.

              The theory of spin glasses was used to study a simple model of protein folding. The phase diagram of the model was calculated, and the results of dynamics calculations are briefly reported. The relation of these results to folding experiments, the relation of these hypotheses to previous protein folding theories, and the implication of these hypotheses for protein folding prediction schemes are discussed.
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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
                1 July 2010
                4 June 2010
                4 June 2010
                : 38
                : Web Server issue
                : W657-W661
                Affiliations
                1Center for Theoretical Biological Physics and Department of Physics, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093 and 2Theoretical Biology and Biophysics, Theoretical Division, Los Alamos National Laboratory, MS K710, Los Alamos, NM 87545, USA
                Author notes
                *To whom correspondence should be addressed. Tel: +1 858 534 7067; Fax: +1 858 534 7697; Email: jonuchic@ 123456ctbp.ucsd.edu
                Article
                gkq498
                10.1093/nar/gkq498
                2896113
                20525782
                243a0fcc-2d80-4099-98d4-5ea79ad07321
                © The Author(s) 2010. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 12 February 2010
                : 14 May 2010
                : 18 May 2010
                Categories
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                Genetics
                Genetics

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