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      Platinum: a database of experimentally measured effects of mutations on structurally defined protein–ligand complexes

      * , , *

      Nucleic Acids Research

      Oxford University Press

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          Abstract

          Drug resistance is a major challenge for the treatment of many diseases and a significant concern throughout the drug development process. The ability to understand and predict the effects of mutations on protein–ligand affinities and their roles in the emergence of resistance would significantly aid treatment and drug design strategies. In order to study and understand the impacts of missense mutations on the interaction of ligands with the proteome, we have developed Platinum ( http://structure.bioc.cam.ac.uk/platinum). This manually curated, literature-derived database, comprising over 1000 mutations, associates for the first time experimental information on changes in affinity with three-dimensional structures of protein–ligand complexes. To minimize differences arising from experimental techniques and to directly compare binding affinities, Platinum considers only changes measured by the same group and with the same amino-acid sequence used for structure determination, providing a direct link between protein structure, how a ligand binds and how mutations alter the affinity of the ligand of the protein. We believe Platinum will be an invaluable resource for understanding the effects of mutations that give rise to drug resistance, a major problem emerging in pandemics including those caused by the influenza virus, in infectious diseases such as tuberculosis, in cancer and in many other life-threatening illnesses.

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          Most cited references 24

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          DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach

          Cancer genome and other sequencing initiatives are generating extensive data on non-synonymous single nucleotide polymorphisms (nsSNPs) in human and other genomes. In order to understand the impacts of nsSNPs on the structure and function of the proteome, as well as to guide protein engineering, accurate in silicomethodologies are required to study and predict their effects on protein stability. Despite the diversity of available computational methods in the literature, none has proven accurate and dependable on its own under all scenarios where mutation analysis is required. Here we present DUET, a web server for an integrated computational approach to study missense mutations in proteins. DUET consolidates two complementary approaches (mCSM and SDM) in a consensus prediction, obtained by combining the results of the separate methods in an optimized predictor using Support Vector Machines (SVM). We demonstrate that the proposed method improves overall accuracy of the predictions in comparison with either method individually and performs as well as or better than similar methods. The DUET web server is freely and openly available at http://structure.bioc.cam.ac.uk/duet.
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            The RCSB Protein Data Bank: new resources for research and education

            The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) develops tools and resources that provide a structural view of biology for research and education. The RCSB PDB web site (http://www.rcsb.org) uses the curated 3D macromolecular data contained in the PDB archive to offer unique methods to access, report and visualize data. Recent activities have focused on improving methods for simple and complex searches of PDB data, creating specialized access to chemical component data and providing domain-based structural alignments. New educational resources are offered at the PDB-101 educational view of the main web site such as Author Profiles that display a researcher’s PDB entries in a timeline. To promote different kinds of access to the RCSB PDB, Web Services have been expanded, and an RCSB PDB Mobile application for the iPhone/iPad has been released. These improvements enable new opportunities for analyzing and understanding structure data.
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              Epidemiology of drug resistance: implications for a post-antimicrobial era.

               Lewis Cohen (1992)
              In the last several years, the frequency and spectrum of antimicrobial-resistant infections have increased in both the hospital and the community. Certain infections that are essentially untreatable have begun to occur as epidemics both in the developing world and in institutional settings in the United States. The increasing frequency of drug resistance has been attributed to combinations of microbial characteristics, selective pressures of antimicrobial use, and societal and technologic changes that enhance the transmission of drug-resistant organisms. Antimicrobial resistance is resulting in increased morbidity, mortality, and health-care costs. Prevention and control of these infections will require new antimicrobial agents, prudent use of existing agents, new vaccines, and enhanced public health efforts to reduce transmission.
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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
                28 January 2015
                16 October 2014
                16 October 2014
                : 43
                : Database issue , Database issue
                : D387-D391
                Affiliations
                Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +44 1223766033; Fax: +44 1223766002; Email: dascher@ 123456svi.edu.au
                Correspondence may also be addressed to Douglas E.V. Pires. Tel: +44 1223766033; Fax: +44 1223766002; Email: dpires@ 123456dcc.ufmg.br
                Article
                10.1093/nar/gku966
                4384026
                25324307
                © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                Page count
                Pages: 5
                Product
                Categories
                Database Issue
                Custom metadata
                28 January 2015

                Genetics

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