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.
