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Introducing the metacore concept for multi-target ligand design.

Dagmar Stumpfe1, Alexander Hoch1, Jürgen Bajorath1

  • 1Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität Friedrich-Hirzebruch-Allee 6 D-53115 Bonn Germany bajorath@bit.uni-bonn.de +49 228 73 69101 +49 228 73 69100.

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Summary

We introduce metacores (MCs) to organize analog series (ASs) for multi-target (MT) drug design. This method aids in discovering new compounds active against diverse biological targets, advancing polypharmacology.

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Area of Science:

  • Medicinal Chemistry
  • Computational Drug Design
  • Pharmacology

Background:

  • Generating compounds with activity against multiple, often unrelated, targets is crucial for polypharmacology-driven drug discovery.
  • Organizing and analyzing existing analog series (ASs) is key to identifying patterns for novel ligand design.
  • Existing methods may not efficiently capture the structural relationships relevant for multi-target (MT) drug discovery.

Purpose of the Study:

  • To introduce and define the concept of metacores (MCs) for structuring analog series (ASs).
  • To develop a methodology for extracting MCs from ASs to facilitate multi-target (MT) ligand design.
  • To provide a freely accessible resource of MCs and associated target information for medicinal chemists.

Main Methods:

  • A two-stage extraction process was employed to derive structural cores, termed metacores (MCs), from analog series (ASs).
  • Systematic identification of ASs exclusively containing analogs with MT activity and determination of their target profiles.
  • Characterization and prioritization of extracted MCs based on AS, compound, and target coverage.

Main Results:

  • A diverse set of 317 MCs was extracted from identified ASs.
  • 127 of these MCs were linked to distinct target families, highlighting their potential for MT applications.
  • 260 MCs were identified as pharmaceutically relevant after rigorous characterization and prioritization.

Conclusions:

  • The developed metacore (MC) methodology offers a chemically intuitive and broadly applicable approach for organizing analog series (ASs).
  • Metacores (MCs) serve as valuable templates for generating novel structures with potential multi-target (MT) activities.
  • The freely available MCs and associated data empower medicinal chemists in drug discovery efforts.