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.

Includes cutting-edge techniques Provides step-by-step details for ease of use Contains key implementation advice from the experts

Inhalt
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 ProteinProtein Binding Affinities from Unbound Protein Structures.- Parameter Optimization for Ion Channel Models: Integrating New Data with Known Channel Properties.