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Titlebook: Computer-Aided Antibody Design; Kouhei Tsumoto,Daisuke Kuroda Book 2023 Springer Science+Business Media, LLC, part of Springer Nature 2023

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书目名称Computer-Aided Antibody Design
编辑Kouhei Tsumoto,Daisuke Kuroda
视频videohttp://file.papertrans.cn/235/234419/234419.mp4
概述Includes cutting-edge methods and protocols.Provides step-by-step detail essential for reproducible results.Contains key notes and implementation advice from the experts
丛书名称Methods in Molecular Biology
图书封面Titlebook: Computer-Aided Antibody Design; Kouhei Tsumoto,Daisuke Kuroda Book 2023 Springer Science+Business Media, LLC, part of Springer Nature 2023
描述.This volume details state-of-the- art methods on computer-aided antibody design. Chapters guide readers through information on antibody sequences and structures,  modeling antibody structures and dynamics, prediction and optimization of biological and biophysical properties of antibodies, prediction of antibody-antigen interactions, and computer-aided antibody affinity maturation and beyond. Written in the format of the highly successful .Methods in Molecular Biology .series, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols...Authoritative and cutting-edge, .Computer-Aided Antibody Design .aims to be a useful and practical guide to new researchers and experts looking to expand their knowledge. .Chapter 2 is available open access under a Creative Commons Attribution 4.0 InternationalLicense via link.springer.com..
出版日期Book 2023
关键词Antibodies; Drug discovery; Computational methods; Protein engineering; Biotechnology
版次1
doihttps://doi.org/10.1007/978-1-0716-2609-2
isbn_softcover978-1-0716-2611-5
isbn_ebook978-1-0716-2609-2Series ISSN 1064-3745 Series E-ISSN 1940-6029
issn_series 1064-3745
copyrightSpringer Science+Business Media, LLC, part of Springer Nature 2023
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Probing Conformational Dynamics of Antibodies with Geometric Simulationsmetric simulations method FRODAN, which is a low computational complexity alternative to molecular dynamics (MD) simulations that can rapidly explore flexible motions in protein structures. FRODAN is highly suited for conformational dynamics analysis of large proteins, complexes, intrinsically disor
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PITHA: A Webtool to Predict Immunogenicity for Humanized and Fully Human Therapeutic Antibodiesic antibodies and their antibodies, one can see that anti-idiotypic antibodies usually bind the complementarity-determining regions (CDR) of idiotypic antibodies. Sequence and structural features, such as cavity volume at the CDR region and hydrophobicity of CDR-H3 loop region, were identified for d
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In Silico Prediction Method for Protein Asparagine Deamidationm on structural level with machine learning. Our structure-based method is more accurate than the sequence-based method which is still widely used in protein engineering process. In addition, molecular dynamics simulation was applied to study the time occupancy of nucleophilic attack distance, which
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Structure-Based Optimization of Antibody-Based Biotherapeutics for Improved Developability: A Practibiotherapeutic drug development. Predictive computational strategies, used in the early stages of antibody discovery and development, to mitigate the risk of late-stage failure of antibody candidates, are highly valuable. Various structure-based methods exist for accurately predicting properties cri
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