Objective assessment of cancer genes for drug discovery

Mishal N Patel1, Mark D Halling-Brown, Joseph E Tym

  • 1Cancer Research UK Cancer Therapeutics Unit, The Institute of Cancer Research, London, UK.

Insights

This study presents a computational method to systematically prioritize therapeutic targets from large gene sets, aiding drug discovery. It identifies druggable cancer proteins and suggests drug repurposing opportunities.

Area of Science:

  • Computational biology
  • Drug discovery
  • Genomics

Background:

  • Selecting effective therapeutic targets is crucial for drug discovery, especially with large gene sets from multi-omics initiatives in oncology.
  • Prioritizing these targets requires systematic, efficient, and objective computational approaches.

Approach:

  • Developed a multifaceted computational assessment framework to evaluate biological and chemical space for target prioritization.
  • Applied the approach to a set of 479 cancer-associated genes to demonstrate its utility.

Key Points:

  • Revealed the inherent conflict between biological significance and chemical tractability in target selection.
  • Highlighted significant knowledge gaps hindering objective decision-making in drug development.
  • Identified potential drug repurposing opportunities for existing therapeutics.

Conclusions:

  • The computational method provides an objective framework for prioritizing therapeutic targets.
  • Identified poorly explored, yet druggable, cancer-associated proteins for small-molecule drug development.
  • Aimed to facilitate more informed and efficient drug discovery and development processes.

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