Repurposing Drugs Based on Evolutionary Relationships Between Targets of Approved Drugs and Proteins of Interest

Methods Mol Biol. 2019;1903:45-59. doi: 10.1007/978-1-4939-8955-3_3.

Abstract

Drug repurposing has garnered much interest as an effective method for drug development among biopharmaceutical companies. The availability of information on complete sequences of genomes and their associated biological data, genotype-phenotype-disease relationships, and properties of small molecules offers opportunities to explore the repurpose-able potential of existing pharmacopoeia. This method gains further importance, especially, in the context of development of drugs against infectious diseases, some of which pose serious complications due to emergence of drug-resistant pathogens. In this article, we describe computational means to achieve potential repurpose-able drug candidates that may be used against infectious diseases by exploring evolutionary relationships between established targets of FDA-approved drugs and proteins of pathogen of interest.

Keywords: Computational approach; Drug repurposing; Hidden Markov model; Infectious diseases; Protein evolution.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biological Evolution
  • Communicable Diseases / drug therapy
  • Communicable Diseases / etiology
  • Communicable Diseases / metabolism
  • Computational Biology* / methods
  • Databases, Pharmaceutical
  • Drug Repositioning* / methods
  • Humans
  • Ligands*
  • Markov Chains
  • Proteins / chemistry*
  • Proteins / genetics
  • Proteins / metabolism
  • Quantitative Structure-Activity Relationship*
  • Software
  • Workflow

Substances

  • Ligands
  • Proteins