IDENTIFICATION OF PHARMACOLOGICAL TARGETS COMBINING DOCKING AND MOLECULAR DYNAMICS SIMULATIONS

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 b