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      Molecular modeling and molecular dynamic simulation of the effects of variants in the TGFBR2 kinase domain as a paradigm for interpretation of variants obtained by next generation sequencing

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          Abstract

          Variants in the TGFBR2 kinase domain cause several human diseases and can increase propensity for cancer. The widespread application of next generation sequencing within the setting of Individualized Medicine (IM) is increasing the rate at which TGFBR2 kinase domain variants are being identified. However, their clinical relevance is often uncertain. Consequently, we sought to evaluate the use of molecular modeling and molecular dynamics (MD) simulations for assessing the potential impact of variants within this domain. We documented the structural differences revealed by these models across 57 variants using independent MD simulations for each. Our simulations revealed various mechanisms by which variants may lead to functional alteration; some are revealed energetically, while others structurally or dynamically. We found that the ATP binding site and activation loop dynamics may be affected by variants at positions throughout the structure. This prediction cannot be made from the linear sequence alone. We present our structure-based analyses alongside those obtained using several commonly used genomics-based predictive algorithms. We believe the further mechanistic information revealed by molecular modeling will be useful in guiding the examination of clinically observed variants throughout the exome, as well as those likely to be discovered in the near future by clinical tests leveraging next-generation sequencing through IM efforts.

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          Most cited references 33

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          T-Coffee: a web server for the multiple sequence alignment of protein and RNA sequences using structural information and homology extension

          This article introduces a new interface for T-Coffee, a consistency-based multiple sequence alignment program. This interface provides an easy and intuitive access to the most popular functionality of the package. These include the default T-Coffee mode for protein and nucleic acid sequences, the M-Coffee mode that allows combining the output of any other aligners, and template-based modes of T-Coffee that deliver high accuracy alignments while using structural or homology derived templates. These three available template modes are Expresso for the alignment of protein with a known 3D-Structure, R-Coffee to align RNA sequences with conserved secondary structures and PSI-Coffee to accurately align distantly related sequences using homology extension. The new server benefits from recent improvements of the T-Coffee algorithm and can align up to 150 sequences as long as 10 000 residues and is available from both http://www.tcoffee.org and its main mirror http://tcoffee.crg.cat.
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            DaliLite workbench for protein structure comparison.

             L. Holm,  J. Park (2000)
            DaliLite is a program for pairwise structure comparison and for structure database searching. It is a standalone version of the search engine of the popular Dali server. A web interface is provided to view the results, multiple alignments and 3D superimpositions of structures.
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              Coarse-grained normal mode analysis in structural biology.

               Ivet Bahar,  AJ Rader (2005)
              The realization that experimentally observed functional motions of proteins can be predicted by coarse-grained normal mode analysis has renewed interest in applications to structural biology. Notable applications include the prediction of biologically relevant motions of proteins and supramolecular structures driven by their structure-encoded collective dynamics; the refinement of low-resolution structures, including those determined by cryo-electron microscopy; and the identification of conserved dynamic patterns and mechanically key regions within protein families. Additionally, hybrid methods that couple atomic simulations with deformations derived from coarse-grained normal mode analysis are able to sample collective motions beyond the range of conventional molecular dynamics simulations. Such applications have provided great insight into the underlying principles linking protein structures to their dynamics and their dynamics to their functions.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                9 February 2017
                2017
                : 12
                : 2
                Affiliations
                [1 ]Department of Health Science Research, Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, United States of America
                [2 ]Laboratory of Epigenetics and Chromatin Dynamics, Gastroenterology Research Unit, Mayo Clinic, Rochester, Minnesota, United States of America
                [3 ]Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, Minnesota, United States of America
                [4 ]Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, United States of America
                [5 ]Center for Individualized Medicine, Mayo Clinic, Rochester, MN, United States of America
                [6 ]Center for Individualized Medicine, Mayo Clinic, Jacksonville, FL, United States of America
                Wake Forest University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: MTZ RU GRO EWK.

                • Data curation: MTZ RU GRO.

                • Formal analysis: MTZ.

                • Funding acquisition: RU EWK.

                • Investigation: MTZ.

                • Methodology: MTZ RU GRO EWK.

                • Software: MTZ.

                • Supervision: RU EWK.

                • Validation: MTZ GRO RU.

                • Visualization: MTZ.

                • Writing – original draft: MTZ RU.

                • Writing – review & editing: MTZ RU GRO PRB MAC NJB EWK.

                Article
                PONE-D-16-39141
                10.1371/journal.pone.0170822
                5300139
                28182693
                © 2017 Zimmermann et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 8, Tables: 1, Pages: 21
                Product
                Funding
                Funded by: Mayo Clinic Center for Individualized Medicine
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000062, National Institute of Diabetes and Digestive and Kidney Diseases;
                Award ID: R0152913
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000062, National Institute of Diabetes and Digestive and Kidney Diseases;
                Award ID: P30084567
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000062, National Institute of Diabetes and Digestive and Kidney Diseases;
                Award ID: P50CA102701
                Award Recipient :
                We thank the Mayo Clinic Center for Individualized Medicine for funding. RU was supported by Grants from NIDDK: National Institute of Diabetes and Digestive and Kidney Diseases - RO1 52913, - P30 084567 - P50CA102701 and the Mayo Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Biochemistry
                Biochemical Simulations
                Biology and Life Sciences
                Computational Biology
                Biochemical Simulations
                Biology and Life Sciences
                Biophysics
                Biophysical Simulations
                Physical Sciences
                Physics
                Biophysics
                Biophysical Simulations
                Biology and Life Sciences
                Computational Biology
                Biophysical Simulations
                Biology and Life Sciences
                Molecular Biology
                Macromolecular Structure Analysis
                Protein Structure
                Biology and Life Sciences
                Biochemistry
                Proteins
                Protein Structure
                Physical Sciences
                Chemistry
                Physical Chemistry
                Chemical Bonding
                Hydrogen Bonding
                Biology and Life Sciences
                Biochemistry
                Nucleotides
                Adenine
                Physical Sciences
                Chemistry
                Computational Chemistry
                Molecular Dynamics
                Research and Analysis Methods
                Simulation and Modeling
                Biology and life sciences
                Cell biology
                Signal transduction
                Cell signaling
                Signaling cascades
                TGF-beta signaling cascade
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

                Uncategorized

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