ReviewThe AAPS journal2018
Computational Fragment-Based Drug Design: Current Trends, Strategies, and Applications.
Review in The AAPS journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
38 citing papers in PubMed.
- Artificial intelligence and ultra-high performance computing methods and experiments for drug discovery: virtual screening, deep learning, molecular dynamics simulations, ADMET modelling, and experimental validation.Molecular biomedicine · 2026Review
- From Genome Inspection to Precision Agrochemicals: A Structure-Based Antivirulence Roadmap for Sustainable Crop Protection againstJournal of agricultural and food chemistry · 2026Review
- LinkLlama: Enabling Large Language Model for Chemically Reasonable Linker Design.bioRxiv : the preprint server for biology · 2026Article
- Energy-Screened Many-Body Expansion for Protein-Ligand Interactions: Examining Convergence for Metalloenzymes Through Seven-Body Interactions.Journal of chemical theory and computation · 2026Article
- Article
- Expanding Automated Multiconformer Ligand Modeling to Macrocycles and Fragments.bioRxiv : the preprint server for biology · 2025Article
- Medicinal Chemistry behind Capivasertib Discovery: Seventh Magic Bullet of the Fragment-based Drug Design Approved for Oncology.Current medicinal chemistry · 2025Review
- The role and application of bioinformatics techniques and tools in drug discovery.Frontiers in pharmacology · 2025Review
- DigFrag as a digital fragmentation method used for artificial intelligence-based drug design.Communications chemistry · 2024Article
- In Silico Investigation against Inhibitors of Alpha-Amylase Using Structure-based Screening, Molecular Docking, and Molecular Simulations Studies.Cell biochemistry and biophysics · 2024Article
- Streamlining Computational Fragment-Based Drug Discovery through Evolutionary Optimization Informed by Ligand-Based Virtual Prescreening.Journal of chemical information and modeling · 2024Article
- Recent Deep Learning Applications to Structure-Based Drug Design.Methods in molecular biology (Clifton, N.J.) · 2024Review
- Collective and Coordinated Conformational Changes Determine Agonism or Antagonism at the Human Trace Amine-Associated Receptor 1.ACS omega · 2023Article
- Alchemical Free Energy Calculations on Membrane-Associated Proteins.Journal of chemical theory and computation · 2023Review
- SILVR: Guided Diffusion for Molecule Generation.Journal of chemical information and modeling · 2023Article
- Construction of Histone-Protein Complex Structures by Peptide Growing.International journal of molecular sciences · 2023Article
- Development and application of fragment-based de novo inhibitor design approaches against Plasmodium falciparum GST.Journal of molecular modeling · 2023Article
- DrugEx v3: scaffold-constrained drug design with graph transformer-based reinforcement learning.Journal of cheminformatics · 2023Article
- Evaluating the use of absolute binding free energy in the fragment optimisation process.Communications chemistry · 2022Article
- FastGrow: on-the-fly growing and its application to DYRK1A.Journal of computer-aided molecular design · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Fragment-based drug design (FBDD) has become an effective methodology for drug development for decades. Successful applications of this strategy brought both opportunities and challenges to the field of Pharmaceutical Science. Recent progress in the computational fragment-based drug design provide an additional approach for future research in a time- and labor-efficient manner. Combining multiple in silico methodologies, computational FBDD possesses flexibilities on fragment library selection, protein model generation, and fragments/compounds docking mode prediction. These characteristics provide computational FBDD superiority in designing novel and potential compounds for a certain target. The purpose of this review is to discuss the latest advances, ranging from commonly used strategies to novel concepts and technologies in computational fragment-based drug design. Particularly, in this review, specifications and advantages are compared between experimental and computational FBDD, and additionally, limitations and future prospective are discussed and emphasized.
Indexed as
Identifiers
What OpenQuestion holds
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.