Molecular docking and molecular mechanics simulations are important approaches to gain a rational drug design or a chemical process modeling. It is very convenient, reducing the consumption of chemical reagents, preclinical, clinical trials, and time.
Molecular Mechanics (MM) force fields are the methods of choice for protein simulations, which are essential in the study of conformational flexibility. Given the importance of protein flexibility in drug binding, MM is involved in most if not all Computational Structure-Based Drug Discovery (CSBDD) projects.
Molecular docking and molecular mechanics simulations go to deep molecular insights as structures and mechanisms helping researchers to characterize various conformations and molecular interactions in terms of energy and binding affinities, giving the possibility to search among dozens, hundreds of real or imaginary compounds, the most suitable for a precise, well-defined purpose. The biochemical purpose derives from the chosen macromolecular target, protein, or enzyme. Starting from a known substance with a known mechanism of action and biological activity, we can imagine other related compounds as drug candidates with better efficacy and fewer side effects. These in silico methods help us to identify and select among large compound libraries the most suitable therapeutic agent before even starting its chemical synthesis. That can be called virtual chemistry before the reaction tube. It is very convenient, reducing the consumption of chemical reagents, preclinical, clinical trials, and time.
Molecular dynamics simulations explore extrinsic surface and bulk properties of certain forms of pharmaceutically active molecules to help the selection of a successful candidate. It involves accurate evaluation of binding pathways, kinetics, and thermodynamics of ligands in different solvents.
Computer-aided drug design (CADD) methods lead to ligand identification and optimization, favoring rapid development of pharmaceutical compounds.
Molecular docking techniques help to predict the best matching binding mode of a ligand to a macromolecular partner (here just proteins are considered). It consists in the generation of a number of possible conformations/orientations, i.e., poses, of the ligand within the protein binding site. For this reason, the availability of the three-dimensional structure of the molecular target is a necessary condition; it can be an experimentally solved structure (such as by X-ray crystallography or NMR) or a structure obtained by computational techniques (such as homology modeling).
Molecular docking is composed mainly by two stages:
- An engine for conformations/orientations sampling
- A scoring function, which associates a score to each predicted pose
The sampling process should effectively search the conformational space described by the free energy landscape, where energy, in docking, is approximated by the scoring function. The scoring function should be able to associate the native bound-conformation to the global minimum of the energy hypersurface.
Computational methods, used at the early stages of the drug design process, use current technology to provide valuable insights into the understanding of chemical systems in a virtual manner, complementing experimental analysis. Molecular docking is an in silico method used to foresee binding modes of small compounds or macromolecules in contact with a receptor and to predict their molecular interactions.