Molecular docking is a widely used computer simulation procedure to predict the conformation of a receptor-ligand complex, where the receptor is usually a protein or a nucleic acid molecule and the ligand is either a small molecule or another protein.
Protein-ligand interactions are a necessary prerequisite for signal transduction, immunoreaction, and gene regulation. Protein-ligand interaction studies are important for understanding the mechanisms of biological regulation, and they provide a theoretical basis for the design and discovery of new drug targets. In this study, it has been analyzed the molecular interactions of protein-ligand which was docked by AutoDock 4.2 software. In AutoDock 4.2 software, a new search algorithm is used, hybrid algorithm of random drift particle swarm optimization and local search (LRDPSO), and the classical Lamarckian genetic algorithm (LGA) as energy optimization algorithms. The best conformations of each docking algorithm were subjected to molecular dynamic (MD) simulations to further analyze the molecular mechanisms of protein-ligand interactions. Here, we analyze the binding energy between protein receptors and ligands, the interactions of salt bridges and hydrogen bonds in the docking region, and the structural changes during complex unfolding. Our comparison of these complexes highlights differences in the protein-ligand interactions between the two docking methods. It also shows that salt bridge and hydrogen bond interactions play a crucial role in protein-ligand stability. The present work focuses on extracting the deterministic characteristics of docking interactions from their dynamic properties, which is important for understanding biological functions and determining which amino acid residues are crucial to docking interactions.
The protein-ligand docking procedure can be typically divided into two parts: rigid body docking and flexible docking.
Rigid Docking: This approximation treats both the ligand and the receptor as rigid and explores only six degrees of translational and rotational freedom, hence excluding any kind of flexibility. Most of the docking suites employ rigid body docking procedure as a first step.
Flexible Docking: A more common approach is to model the ligand flexibility while assuming having a rigid protein receptor, considering thereby only the conformational space of the ligand. Ideally, however, protein flexibility should also be taken into account, and some approaches in this regard have been developed. There are three general categories of algorithms to treat ligand flexibility: systematic methods, random or stochastic methods, and simulation methods. Due to the large size of proteins and their multiple degrees of freedom, their flexibility may be the most challenging issue in molecular docking. The methods to address the flexibility of proteins can be grouped into: soft docking, side-chain flexibility, molecular relaxation and protein ensemble docking.
The goal of protein–ligand docking is to predict the position and orientation of a ligand (a small molecule) when it is bound to a protein receptor or enzyme. Pharmaceutical research employs docking techniques for a variety of purposes, most notably in the virtual screening of large databases of available chemicals in order to select likely drug candidates.
Many protein–ligand docking software applications that calculate the site, geometry and energy of small molecules or peptides interacting with proteins are available, such as;
AutoDock
AutoDock Vina
rDock
FlexAID
Molecular Operating Environment
Glide
