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Ligand efficiency metrics considered harmful.

Peter W Kenny1, Andrei Leitão, Carlos A Montanari

  • 1Grupo de em Química Medicinal do IQSC/USP - NEQUIMED, Instituto de Química de São Carlos, Universidade de São Paulo, Av. Trabalhador Sancarlense, 400, São Carlos, SP, 13566-590, Brazil, pwk.pub.2008@gmail.com.

Journal of Computer-Aided Molecular Design
|June 6, 2014
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Summary
This summary is machine-generated.

Ligand efficiency metrics help drug discovery by relating binding affinity to molecular properties. This perspective examines these metrics and suggests better ways to use physicochemical properties for lead optimization.

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Area of Science:

  • Drug discovery
  • Medicinal chemistry
  • Computational chemistry

Background:

  • Ligand efficiency metrics are crucial for normalizing biological activity against physicochemical properties.
  • Understanding protein-ligand binding thermodynamics is essential for drug design.
  • Physicochemical properties like lipophilicity and molecular size influence binding affinity.

Purpose of the Study:

  • To provide a comprehensive overview of ligand efficiency metrics.
  • To critically examine different classes of ligand efficiency metrics.
  • To suggest alternative approaches for incorporating physicochemical properties in lead optimization.

Main Methods:

  • Literature review and critical analysis of existing ligand efficiency metrics.
  • Summary of key thermodynamic principles governing protein-ligand interactions.
  • Exploration of alternative methods for accounting for physicochemical properties.

Main Results:

  • Different classes of ligand efficiency metrics exhibit varying strengths and weaknesses.
  • Current metrics may not always adequately account for the impact of physicochemical properties.
  • Thermodynamic considerations provide a framework for understanding binding.

Conclusions:

  • Ligand efficiency metrics are valuable but require careful application.
  • Alternative strategies for integrating physicochemical properties can improve lead prioritization.
  • A deeper understanding of binding thermodynamics can guide the development of more effective metrics.