Cited by 82Computational Drug Discovery MethodsChemical Synthesis and AnalysisProtein Degradation and Inhibitors

Fragment Informatics and Computational Fragment‐Based Drug Design: An Overview and Update

Sheng, Chunquan, Zhang, Wannian·2013·Medicinal Research Reviews

Abstract

Fragment‐based drug design (FBDD) is a promising approach for the discovery and optimization of lead compounds. Despite its successes, FBDD also faces some internal limitations and challenges. FBDD requires a high quality of target protein and good solubility of fragments. Biophysical techniques for fragment screening necessitate expensive detection equipment and the strategies for evolving fragment hits to leads remain to be improved. Regardless, FBDD is necessary for investigating larger chemical space and can be applied to challenging biological targets. In this scenario, cheminformatics and computational chemistry can be used as alternative approaches that can significantly improve the efficiency and success rate of lead discovery and optimization. Cheminformatics and computational tools assist FBDD in a very flexible manner. Computational FBDD can be used independently or in parallel with experimental FBDD for efficiently generating and optimizing leads. Computational FBDD can also be integrated into each step of experimental FBDD and help to play a synergistic role by maximizing its performance. This review will provide critical analysis of the complementarity between computational and experimental FBDD and highlight recent advances in new algorithms and successful examples of their applications. In particular, fragment‐based cheminformatics tools, high‐throughput fragment docking, and fragment‐based de novo drug design will provide the focus of this review. We will also discuss the advantages and limitations of different methods and the trends in new developments that should inspire future research.

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Registry

Crossref · 10.1002/med.21255

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  • By employing structure-based virtual screening, they identified a quinazolinone fragment, hit 4 (Kd = 467 ± 65 nM), with two optical isomers that acted on different "hot spots" of PDEδ.

    “By employing structure-based virtual screening, they identified a quinazolinone fragment, hit 4 (Kd = 467 ± 65 nM), with two optical isomers that acted on different “hot spots” of PDEδ.349–352”

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Authors
Sheng, C., & Zhang, W.
Affiliations
Second Military Medical University (CN)
Corresponding author
Sheng, Chunquan
Venue
Medicinal Research Reviews
Publisher
Wiley
Published
2012-03-19
Volume
33
Issue
3
Pages
554-598
ISSN
  • 0198-6325 (ISSN-L)
  • 1098-1128
OpenAlex
W1531916394
Cited by
80
References
261
Citations by year
2026: 3 · 2025: 6 · 2024: 11 · 2023: 11 · 2022: 5 · 2021: 4 · 2020: 5 · 2019: 3 · 2018: 5 · 2017: 3 · 2016: 4 · 2015: 6 · 2014: 6 · 2013: 5 · 2012: 3
FWCI
0.74
Type
journal article
Language
en
Open access
closed
Locations
  • Medicinal Research Reviews (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chemical Synthesis and Analysis
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Degradation and Inhibitors
Keywords
fragment-based drug discovery, cheminformatics, fragment-based docking, lead compound identification, computer-aided drug design, fragment screening
MeSH terms
Drug Evaluation, Preclinical, Ligands, Receptors, Drug, Software, Structure-Activity Relationship, Drug Design, Computational Biology, Catalytic Domain, Cyclophilin A, Nitric Oxide Synthase Type I, Serotonin 5-HT1 Receptor Antagonists, 14-alpha Demethylase Inhibitors, Molecular Docking Simulation

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