Abstract
Protein interactions with various other macromolecules is a key biological phenomenon for the molecular recognition process leading to various physiological functions. Throughout decades, researchers have proposed various methods for the investigation of such binding mechanism, starting from static, rigid docking to flexible docking approaches. Rational drug designing approaches were improvised by introducing semi- to full-flexibility in the protein-ligand molecular recognition process, conformational dynamics, and binding kinetics and thermodynamics of conserved waters in the binding site. A better understanding of ligand-binding is quintessential to gain more quantitative and accurate information about molecular recognition for drug and therapeutic interventions. To address these issues, Ensemble docking approaches were introduced, which include protein flexibility through a different set of protein conformations either experimentally or with computational simulations i.e., molecular dynamics simulations. MD simulations enable ensemble construction which generates an array of binding site conformations for multiple docking trials of the same protein, though sometimes poorly sampled. To overcome the same, enhanced sampling was introduced. In this chapter, the theoretical background of molecular docking, classical MD simulations, MD-based enhanced sampling methods and hybrid docking-MD based methods are highlighted, demonstrating how protein flexibility has been introduced to optimize and enhance accurate protein-ligand binding predictions. Overall, the evolution of various computational strategies is discussed, from molecular docking to molecular dynamics simulations, to improve the overall drug discovery and development process.
Keywords: CADD, Enhanced Sampling, Ensemble Docking, Flexible Docking, Hybrid Docking-MD, Molecular Docking, Molecular Dynamics Simulations, Metadynamics, REMD, Steered Dynamics, Umbrella Sampling.