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Nano-Differential Scanning Fluorimetry for Screening in Fragment-based Lead Discovery
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Fragment-to-lead tailored in silico design.

Moira Rachman1, Serena Piticchio2, Maciej Majewski3

  • 1Facultat de Farmàcia and Institut de Biomedicina, Universitat de Barcelona, Av. Joan XXIII, 27-31, 08028 Barcelona, Spain; Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA, USA.

Drug Discovery Today. Technologies
|December 17, 2021
PubMed
Summary

Fragment-based drug discovery (FBDD) transforms small fragments into drugs. Integrating computational (in silico) methods accelerates optimizing fragment hits into viable drug leads, overcoming key challenges in FBDD.

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Last Updated: Oct 9, 2025

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Area of Science:

  • Medicinal Chemistry
  • Computational Drug Discovery
  • Pharmacology

Background:

  • Fragment-based drug discovery (FBDD) is an established, cost-effective approach validated by approved drugs.
  • A major challenge in FBDD is the resource-intensive optimization of initial fragment hits into viable drug leads (F2L).

Purpose of the Study:

  • To critically review current in silico strategies for fragment-to-lead (F2L) optimization.
  • To highlight the impact of computational approaches in accelerating FBDD.

Main Methods:

  • Overview of existing in silico tools and methodologies applied to F2L optimization.
  • Analysis of the strengths and limitations of current computational strategies.

Main Results:

  • In silico strategies significantly aid in exploring chemical space and prioritizing potential drug candidates.
  • Current computational solutions are often specific to particular targets or fragments.
  • Integrated in silico approaches demonstrate remarkable impact on F2L optimization.

Conclusions:

  • Fully integrated, systematic in silico strategies can overcome F2L limitations.
  • Automated exploration of chemical space by computational methods can accelerate the development of fragment-originated drugs.