Performing an In Silico Repurposing of Existing Drugs by Combining Virtual Screening and Molecular Dynamics Simulation

Methods Mol Biol. 2019:1903:23-43. doi: 10.1007/978-1-4939-8955-3_2.

Abstract

Drug repurposing has become one of the most widely used methods that can make drug discovery more efficient and less expensive. Additionally, computational methods such as structure-based drug designing can be utilized to make drug discovery more efficient and more accurate. Now imagine what can be achieved by combining drug repurposing and computational methods together in drug discovery, "in silico repurposing." In this chapter, we tried to describe a method that combines structure-based virtual screening and molecular dynamics simulation which can find effective compounds among existing drugs that may affect on a specific molecular target. By using molecular docking as a tool for the screening process and then by calculating ligand binding in an active receptor site using scoring functions and inspecting the proper orientation of pharmacophores in the binding site, the potential compounds will be chosen. After that, in order to test the potential compounds in a realistic environment, molecular dynamics simulation and related analysis have to be carried out for separating the false positives and the true positives from each other and finally identifying true "Hit" compounds. It's good to emphasize that if any of these identified potential compounds turn out to have the efficacy to affect that specific molecular target, it can be taken to the phase 2 clinical trials straightaway.

Keywords: Binding free energy; Drug repurposing; Molecular docking; Molecular dynamics simulation; Structure-based virtual screening.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Binding Sites
  • Computational Biology / methods
  • Data Interpretation, Statistical
  • Drug Discovery
  • Drug Repositioning* / methods
  • High-Throughput Screening Assays
  • Ligands
  • Molecular Docking Simulation*
  • Molecular Dynamics Simulation*
  • Protein Binding
  • Quantitative Structure-Activity Relationship

Substances

  • Ligands