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Evolving Concept of Activity Cliffs.

Dagmar Stumpfe1, Huabin Hu1, Jürgen Bajorath1

  • 1Department of Life Science Informatics, b-it, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, D-53115 Bonn, Germany.

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Activity cliffs (ACs) are pairs of similar molecules with large potency differences, crucial for understanding structure-activity relationships (SAR). This review explores ACs, their computational identification, and SAR knowledge extraction.

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Area of Science:

  • Medicinal Chemistry
  • Computational Chemistry
  • Drug Discovery

Background:

  • Activity cliffs (ACs) represent structurally similar compounds with significant potency variations against the same target.
  • ACs highlight critical chemical modifications influencing biological activity, making them vital for SAR analysis.
  • Understanding ACs is essential for effective compound optimization in drug discovery.

Purpose of the Study:

  • To review the evolution and refinement of the activity cliffs concept.
  • To emphasize novel analysis schemes and findings for better AC understanding.
  • To explore systematic computational identification and SAR knowledge extraction from ACs.

Main Methods:

  • Defining molecular similarity and potency difference criteria for AC assessment.
  • Examining case-by-case and systematic approaches to AC identification.
  • Reviewing advancements in computational representation and analysis of ACs.

Main Results:

  • ACs provide deep insights into structure-activity relationships (SAR).
  • Systematic computational methods enhance AC identification and analysis.
  • Refined AC concepts and analysis schemes facilitate SAR knowledge extraction.

Conclusions:

  • Activity cliffs are fundamental to understanding SAR and guiding drug optimization.
  • Advanced computational strategies are key to systematic AC identification and analysis.
  • Further research into ACs promises to unlock significant SAR knowledge for drug discovery.