Identification of Pharmacological Targets Combining Docking and Molecular Dynamics Simulations

Abstract

Studies that include both experimental data and computational simulations (in silico) have increased in number because the techniques are complementary. In silico methodologies are currently an essential component of drug design; moreover, identification and optimization of the best ligand based on the structures of biomolecules are common scientific challenges. Geometric structural properties of biomolecules explain their behavior and interactions and when this information is used by a combination of algorithms, a dynamic model based on atomic details can be produced. Docking studies enable researchers to determine the best position for a ligand to bind on a macromolecule, whereas Molecular Dynamics (MD) simulations describe the relevant interactions that maintain this binding. MD simulations have the advantage of illustrating the macromolecule movements in more detail. In the case of a protein, the side chain, backbone and domain movements can explain how ligands are trapped during different conformational states. Additionally, MD simulations can depict several binding sites of ligands that can be explored by docking studies, sampling many protein conformations. Following the previously mentioned strategy, it is possible to identify each binding site that might be able to accommodate different ligands through atomic motion. Another important advantage of MD is to explore the movement of side chains of key catalytic residues, which could provide information about the formation of transition states of a protein. All this information can be used to propose ligands and their most probable site of interaction, which are daily tasks of drug design. In this review, the most frequent criteria that are considered when determining pharmacological targets are gathered, particularly when docking and MD are combined.

DESIGN OF <i>CANDIDA ANTARCTICA</i> LIPASE B THERMOSTABILITY IMPROVEMENT BY INTRODUCING EXTRA DISULFIDE BOND INTO THE ENZYME

“…Molecular dynamic simulation is an efficient method that could be utilized for constructing model on protein conformation and time repertoire (Adcock and McCammon, 2006;Ian et al, 2013;Carrillo-Vázquez et al, 2013). As we can see, molecular dynamic simulation is still the most effective way to model the structure and reactivity of an enzyme (Gabel et al, 2009;Lousa et al, 2012;Christensen and Kepp, 2013).…”