Computational Modeling of Biomolecular Interactions

Methods and Applications

Yinglong Miao

• Publisher: Wiley
• Year: 2026
• Print ISBN:
  9781394316601
• eBook ISBN:
  9781394316618
• Edition: 1
• Topic: Physical Sciences
• Subtopic: Pharmacology

Comprehensive simulation methods for studying biomolecular interactions and drug design

Understanding how proteins interact with ligands, peptides, and nucleic acids requires sophisticated computational approaches. Computational Modeling of Biomolecular Interactions: Methods and Applications delivers authoritative coverage of simulation techniques for characterizing interaction structures, energetics, kinetics, pathways, and mechanisms. Expert contributors provide both theoretical foundations and practical applications for researchers investigating molecular recognition and drug binding.

The book covers quantum mechanics/molecular mechanics (QM/MM), molecular docking, Brownian dynamics, molecular dynamics (MD), and enhanced sampling methods including supervised MD, dissipation-corrected targeted MD, weighted ensemble, replica exchange, metadynamics, Gaussian accelerated MD, and more. Detailed chapters address binding free energy calculations, drug binding kinetics, and machine learning and deep learning applications. Application studies examine protein-ligand, protein-peptide, protein-protein, and protein-DNA/RNA interactions, plus conformational changes, allostery, and structure-based drug design.

Readers will also find:

• Step-by-step guidance on implementing accelerated MD and enhanced sampling methods for overcoming timescale limitations in biomolecular simulations
• Practical protocols for calculating binding free energies and characterizing drug binding kinetics essential for rational drug design workflows
• Integration of machine learning and deep learning approaches with traditional simulation methods for improved prediction accuracy and efficiency
• Application case studies demonstrating computational analysis of conformational changes, allosteric networks, and interaction mechanisms
• Coverage spanning fundamental simulation theory through advanced applications relevant to biochemistry, pharmacology, and computational chemistry research

Researchers in biochemistry, computational chemistry, pharmacology, biophysics, and chemical biology will find this volume an authoritative resource for computational studies of biomolecular interactions. The combination of methodological depth and practical applications makes it valuable for both method development and applied drug discovery research.

Table of contents

• Cover
• Table of Contents
• Title Page
• Copyright
• List of Contributors
• Preface
• Acknowledgments
• Chapter 1: Atomistic Force Fields for Molecular Simulations with Emphasis on the CHARMM Additive and Drude Polarizable Models
• Chapter 2: Treating Noncovalent Interactions in Biomolecules with QM and QM/MM Models
• Chapter 3: QM/MM Simulations on Catalytic Mechanisms of Metalloenzymes
• Chapter 4: Integrative Multiscale Modeling of Biomolecular Interactions: From Mechanistic Understanding to Design
• Chapter 5: Methodological Advances in Computational Biomodeling: End-point Free Energy Approaches
• Chapter 6: Computational Modeling of Protein–Protein/Peptide/RNA Interactions
• Chapter 7: Modeling Peptide–Protein Interactions with MELD: A Physics-based Framework for Structure, Affinity, and Design
• Chapter 8: Transforming Drug Binding with AI-enhanced Computational Modeling
• Chapter 9: Molecular Simulations-based Predictions of Drug’s Residence Times in the Exascale Era: Current Status and Recent Advances
• Chapter 10: Binding Thermodynamics and Kinetics of Host–Guest Systems Determined from Long-timescale Molecular Dynamics Simulations
• Chapter 11: Supervised Molecular Dynamics Approaches to Protein–Ligand (Un)binding
• Chapter 12: Dissipation-corrected Targeted Molecular Dynamics
• Chapter 13: Hybrid Gaussian Accelerated Molecular Dynamics and the Weighted Ensemble Methods for Biomolecular Simulations
• Chapter 14: Replica Exchange Gaussian Accelerated Molecular Dynamics for Enhanced Sampling and Free Energy Calculations of Biomolecular Interactions
• Chapter 15: Enhanced Sampling of Biomolecular Interactions with Gaussian Accelerated Molecular Dynamics
• Chapter 16: Contact Dynamics-based Perturbation Analysis: Revealing Allosteric Communication Pathways in Proteins
• Chapter 17: Biophysical Methods for Studying the Adamantyl Amine–Lipid–Influenza A M2 Protein Channel System
• Chapter 18: Prediction of Biomolecule Kinetics Using Physics-based Brownian Dynamics to Data-driven Machine Learning Methods
• Index
• End User License Agreement