Computational peptidology
By: edited by Peng Zhou, Center of Bioinformatics (COBI), School of Life Science and Technology, University of Electronic Science and Technology of China (UESTC), Chengdu, China, Jian Huang, Center of Bioinformatics (COBI), School of Life Science and Technology, University of Electronic Science and Technology of China (UESTC), Chengdu, China
Series: Methods in molecular biology -- 1268; Springer protocols; Methods in molecular biology (Clifton, N.J.) -- v. 1268.; Springer protocols (Series)
Publisher: Humana Press
Published: 2015
Place of publication: New York
Language: eng
Number of pages: 338
ISBN-13: 9781493922840; 9781493922857
Subjects: Peptides; Computational Biology; Computational biology; Laboratory manuals; Molecular Models; Drug Design
Description: "In this volume expert researchers detail in silico methods widely used to study peptides. These include methods and techniques covering the database, molecular docking, dynamics simulation, data mining, de novo design and structure modeling of peptides and protein fragments. Chapters focus on integration and application of technologies to analyze, model, identify, predict, and design a wide variety of bioactive peptides, peptide analogues and peptide drugs, as well as peptide-based biomaterials. Written in the highly successful "Methods in Molecular Biology" series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls.Authoritative and practical, "Computational Peptidology" seeks to aid scientists in the further study into this newly rising subfield."--
Notes: Includes bibliographical references and index.
Table of contents: title: De novo peptide structure prediction : an overview  -- Pierre Thévenet [and three others]; title: Molecular modeling of peptides  -- Krzysztof Kuczera; title: Improved methods for classification, prediction, and design of antimicrobial peptides  -- Guangshun Wang; title: Building MHC class II epitope predictor using machine learning approaches  -- Loan Ping Eng, Tin Wee Tan, and Joo Chuan Tong; title: Brownian dynamics simulation of peptides with the University of Houston Brownian Dynamics (UHBD) program  -- Tongye Shen and Chung F. Wong; title: Computational prediction of short linear motifs from protein sequences  -- Richard J. Edwards and Nicolas Palopoli; title: Peptide toxicity prediction  -- Sudheer Gupta [and five others]; title: Synthetic and structural routes for the rational conversion of peptides into small molecules  -- Pasqualina Liana Scognamiglio, Giancarlo Morelli, and Daniela Marasco; title: In silico design of antimicrobial peptides  -- Giuseppe Maccari, Mariagrazia Di Luca, and Riccardo Nifosì; title: Information-driven modeling of protein-peptide complexes  -- Mikael Trellet, Adrien S.J. Melquiond, and Alexandre M.J.J. Bonvin; title: Computational approaches to developing short cyclic peptide modulators of protein-protein interactions  -- Fergal J. Duffy, Marc Devocelle, and Denis C. Shields; title: A use of homology modeling and molecular docking methods : to explore binding mechanisms of nonylphenol and bisphenol A with antioxidant enzymes  -- Mannu Jayakanthan [and three others]; title: Computational peptide vaccinology  -- Johannes Söllner; title: Computational modeling of peptide-aptamer binding -- Kristen L. Rhinehardt, Ram V. Mohan, and Goundla Srinivas.