ReviewFrontiers in chemistry2024
Fragment-based drug discovery for disorders of the central nervous system: designing better drugs piece by piece.
Review in Frontiers in chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Developments and challenges in hit progression within fragment-based drug discovery.Nature communications · 2026Review
- Therapeutic Approaches Interfering with Nuclear Localization Signals: An Emerging Strategy for CNS-Related Diseases.Current neuropharmacology · 2026Review
- Molecular Basis of GABA Aminotransferase Inhibition in Epilepsy: Structure, Mechanisms, and Drug Development.Current issues in molecular biology · 2025Review
- Design, Synthesis and Anticancer Activity of 6-Substituted-1-(3,4,5-trimethoxyphenyl)-Molecules (Basel, Switzerland) · 2025Article
- High-throughput screening identifies novel chemical scaffolds targeting Leishmania donovani parasites.World journal of microbiology & biotechnology · 2025Article
- Enzyme inhibitory activity of marine alkaloid aaptamines for neurodegenerative diseases: anRoyal Society open science · 2025Article
- Design, Synthesis, and Biological Evaluations of a Novel Resveratrol-Type Analogue Against VEGF.Molecules (Basel, Switzerland) · 2025Article
- Current perspectives in drug targeting intrinsically disordered proteins and biomolecular condensates.BMC biology · 2025Review
- Recent Advances in Omics, Computational Models, and Advanced Screening Methods for Drug Safety and Efficacy.Toxics · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fragment-based drug discovery (FBDD) has emerged as a powerful strategy to confront the challenges faced by conventional drug development approaches, particularly in the context of central nervous system (CNS) disorders. FBDD involves the screening of libraries that comprise thousands of small molecular fragments, each no greater than 300 Da in size. Unlike the generally larger molecules from high-throughput screening that limit customisation, fragments offer a more strategic starting point. These fragments are inherently compact, providing a strong foundation with good binding affinity for the development of drug candidates. The minimal elaboration required to transition the hit into a drug-like molecule is not only accelerated, but also it allows for precise modifications to enhance both their activity and pharmacokinetic properties. This shift towards a fragment-centric approach has seen commercial success and holds considerable promise in the continued streamlining of the drug discovery and development process. In this review, we highlight how FBDD can be integrated into the CNS drug discovery process to enhance the exploration of a target. Furthermore, we provide recent examples where FBDD has been an integral component in CNS drug discovery programs, enabling the improvement of pharmacokinetic properties that have previously proven challenging. The FBDD optimisation process provides a systematic approach to explore this vast chemical space, facilitating the discovery and design of compounds piece by piece that are capable of modulating crucial CNS targets.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.