Computational Methods for Estimating the Kinetic Parameters of Biological Systems

Buch | Softcover

379 Seiten

2022 | 1st ed. 2022
Springer-Verlag New York Inc.
978-1-0716-1769-4 (ISBN)

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This detailed book provides an overview of various classes of computational techniques, including machine learning techniques, commonly used for evaluating kinetic parameters of biological systems. Focusing on three distinct situations, the volume covers the prediction of the kinetics of enzymatic reactions, the prediction of the kinetics of protein-protein or protein-ligand interactions (binding rates, dissociation rates, binding affinities), and the prediction of relatively large set of kinetic rates of reactions usually found in quantitative models of large biological networks. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of expert implementation advice that leads to successful results.
Authoritative and practical, Computational Methods for Estimating the Kinetic Parameters of Biological Systems will be of great interest for researchers working through the challenge of identifying the best type of algorithm and who would like to use or develop a computational method for the estimation of kinetic parameters.

Current Approaches of Building Mechanistic Pharmacodynamic Drug-Target Binding Models.- An Extended Model Including Target Turnover, Ligand-Target Complex Kinetics, and Binding Properties to Describe Drug-Receptor Interactions.- Beyond the Michaelis-Menten: Bayesian Inference for Enzyme Kinetic Analysis.- Multi-Objective Optimization Tuning Framework for Kinetic Parameter Selection and Estimation.- Relationship between Dimensionality and Convergence of Optimization Algorithms: A Comparison between Data-Driven Normalization and Scaling Factor-Based Methods Using PEPSSBI.- Dynamic Optimization Approach to Estimate Kinetic Parameters of Monod-Based Microalgae Growth Models.- Automatic Assembly and Calibration of Models of Enzymatic Reactions Based on Ordinary Differential Equations.- Data Processing to Probe the Cellular Hydrogen Peroxide Landscape.- Computational Methods for Structure-Based Drug Design through Systems Biology.- Model Setup and Procedures for Prediction of Enzyme Reaction Kinetics with QM-Only and QM:MM Approaches.- The Role of Ligand Rebinding and Facilitated Dissociation on the Characterization of Dissociation Rates by Surface Plasmon Resonance (SPR) and Benchmarking Performance Metrics.- Computational Tools for Accurate Binding Free Energy Prediction.- Computational Alanine Scanning Reveals Common Features of TCR/pMHC Recognition in HLA-DQ8-Associated Celiac Disease.- Umbrella Sampling-Based Method to Compute Ligand-Binding Affinity.- Creating Maps of the Ligand Binding Landscape for Kinetics-Based Drug Discovery.- Prediction of Protein–Protein Binding Affinities from Unbound Protein Structures.- Parameter Optimization for Ion Channel Models: Integrating New Data with Known Channel Properties.

Erscheinungsdatum	14.12.2022
Reihe/Serie	Methods in Molecular Biology ; 2385
Zusatzinfo	96 Illustrations, color; 9 Illustrations, black and white; XI, 379 p. 105 illus., 96 illus. in color.
Verlagsort	New York, NY
Sprache	englisch
Maße	178 x 254 mm
Themenwelt	Informatik ► Weitere Themen ► Bioinformatik
	Naturwissenschaften ► Biologie ► Genetik / Molekularbiologie
	Naturwissenschaften ► Chemie ► Physikalische Chemie
Schlagworte	Biophysics • enzymatic reactions • kinetic parameters • machine learning • Protein-Ligand Interactions • Quantitative mechanistic models
ISBN-10	1-0716-1769-9 / 1071617699
ISBN-13	978-1-0716-1769-4 / 9781071617694
Zustand	Neuware