A Kulandaisamy1, S Binny Priya1, R Sakthivel1, Svetlana Tarnovskaya2, Ilya Bizin2, Peter Hönigschmid3, Dmitrij Frishman2,3, M Michael Gromiha1,4. 1. Department of Biotechnology, Bhupat and Jyoti Mehta School of BioSciences, Indian Institute of Technology Madras, Chennai, Tamilnadu, India. 2. Department of Bioinformatics, Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russian Federation. 3. Department of Bioinformatics, Technische Universität München, WissenschaftszentrumWeihenstephan, Freising, Germany. 4. Advanced Computational Drug Discovery Unit (CADD), Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Kanagawa, Japan.
Abstract
Motivation: Existing sources of experimental mutation data do not consider the structural environment of amino acid substitutions and distinguish between soluble and membrane proteins. They also suffer from a number of further limitations, including data redundancy, lack of disease classification, incompatible information content, and ambiguous annotations (e.g. the same mutation being annotated as disease and benign). Results: We have developed a novel database, MutHTP, which contains information on 183 395 disease-associated and 17 827 neutral mutations in human transmembrane proteins. For each mutation site MutHTP provides a description of its location with respect to the membrane protein topology, structural environment (if available) and functional features. Comprehensive visualization, search, display and download options are available. Availability and implementation: The database is publicly available at http://www.iitm.ac.in/bioinfo/MutHTP/. The website is implemented using HTML, PHP and javascript and supports recent versions of all major browsers, such as Firefox, Chrome and Opera. Supplementary information: Supplementary data are available at Bioinformatics online.
Motivation: Existing sources of experimental mutation data do not consider the structural environment of amino acid substitutions and distinguish between soluble and membrane proteins. They also suffer from a number of further limitations, including data redundancy, lack of disease classification, incompatible information content, and ambiguous annotations (e.g. the same mutation being annotated as disease and benign). Results: We have developed a novel database, MutHTP, which contains information on 183 395 disease-associated and 17 827 neutral mutations in human transmembrane proteins. For each mutation site MutHTP provides a description of its location with respect to the membrane protein topology, structural environment (if available) and functional features. Comprehensive visualization, search, display and download options are available. Availability and implementation: The database is publicly available at http://www.iitm.ac.in/bioinfo/MutHTP/. The website is implemented using HTML, PHP and javascript and supports recent versions of all major browsers, such as Firefox, Chrome and Opera. Supplementary information: Supplementary data are available at Bioinformatics online.
Authors: Andrei L Lomize; Kevin A Schnitzer; Spencer C Todd; Stanislav Cherepanov; Carlos Outeiral; Charlotte M Deane; Irina D Pogozheva Journal: Protein Sci Date: 2022-05 Impact factor: 6.993
Authors: Tamás Langó; Zoltán Gergő Pataki; Lilla Turiák; András Ács; Julia Kornélia Varga; György Várady; Nóra Kucsma; László Drahos; Gábor E Tusnády Journal: Sci Rep Date: 2020-06-01 Impact factor: 4.379