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008			220317s2022 xxua o |||| 0|eng d
020			_a9781071618554
024	7		_a10.1007/978-1-0716-1855-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQP552 .P4 _b2022 EB
245	0	0	_aComputational Peptide Science : _bMethods and Protocols _cedited by Thomas Simonson
250			_a1st edition 2022
264		1	_aNew York, NY _bSpringer International Publising _c2022
300			_a1 recurso en línea (XIII, 427 páginas) _b93 ilustraciones, 83 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aMethods in Molecular Biology _x1940-6029 _v2405
505	0		_aMachine Learning Prediction of Antimicrobial Peptides -- Tools for Characterizing Proteins: Circular Variance, Mutual Proximity, Chameleon Sequences and Subsequence Propensities -- Exploring the Peptide Potential Of Genomes -- Computational Identification and Design of Complementary β-strand Sequences -- Dynamics of Amyloid Formation from Simplified Representation to Atomistic Simulations -- Predicting Membrane-Active Peptide Dynamics in Fluidic Lipid Membranes -- Coarse-grain simulations of membrane-adsorbed helical peptides -- Peptide dynamics and metadynamics: leveraging enhanced sampling molecular dynamics to robustly model long-timescale transitions -- Metadynamics Simulations to Study the Structural Ensembles and Binding Processes of Intrinsically Disordered Proteins -- Computational and Experimental Protocols to Study Cyclo-Dihistidine Self- and Co-Assembly: Minimalistic Bio-assemblies with Enhanced Fluorescence and Drug Encapsulation Properties -- Computational Tools and Strategies to Develop Peptide-Based Inhibitors of Protein-Protein Interactions -- Rapid Rational Design of Cyclic Peptides Mimicking Protein-Protein Interfaces -- Structural prediction of peptide-MHC binding modes -- Molecular Simulation of Stapled Peptides -- Free Energy-Based Computational Methods for the Study of Protein-Peptide Binding Equilibria -- Computational Evolution Protocol for Peptide Design.-Computational design of miniprotein binders -- Computational Design of LD Motif-Peptides with Improved Recognition of the Focal Adhesion Kinase FAT Domain -- Knowledge-based unfolded state model for protein design.
520			_aThis volume details current and new computational methodologies to study peptides. Chapters guide readers through antimicrobial peptides, foldability, amyloid sheet formation, membrane-active peptides, organized peptide assemblies, protein-peptide interfaces, prediction of peptide-MHC complexes, advanced free energy simulations for peptide binding, and methods for high throughput peptide or miniprotein design. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials, software, and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols. Authoritative and cutting-edge, Computational Peptides Science: Methods and Protocols aims to provide concepts, methods, and guidelines to help both novices and experienced workers benefit from today's new opportunities and challenges.
988			_aSpringer_Protocols_2022
650		7	_2embne _9146243 _aPéptidos
650		7	_2embne _9160489 _aBioinformática
776	0	8	_iPrinted edition: _z9781071618547
776	0	8	_iPrinted edition: _z9781071618561
776	0	8	_iPrinted edition: _z9781071618578
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-1-0716-1855-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b07/2023 _dz _eb _zSI