ReviewNature2023
Computational approaches streamlining drug discovery.
Review in Nature, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 524 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
524 citing papers in PubMed.
- From RNA design to delivery: Computational strategies for functional RNA therapeutics.Bioactive materials · 2027Review
- Artificial intelligence-driven discovery of coumarin-based therapeutics: Revolutionizing target identification and validation.Pharmaceutical science advances · 2026Review
- Integrating virtual screening and molecular dynamics simulations to identify emodin as a PYCR1 inhibitor modulating docetaxel sensitivity in prostate cancer.Journal of enzyme inhibition and medicinal chemistry · 2026Article
- Antitumor activity and structure-activity relationship of poly (ADP-ribose) polymerase (PARP)-based dual inhibitors.Journal of enzyme inhibition and medicinal chemistry · 2026Review
- Structure-guided discovery and evaluation of an EGFR L858R-targeting peptide with antiproliferative activity against ovarian cancer cells.Journal of enzyme inhibition and medicinal chemistry · 2026Article
- Drug-likeness prioritised selection identifies anti-Journal of enzyme inhibition and medicinal chemistry · 2026Article
- A comprehensive review of small molecule drugs approved by the FDA in 2025: advance and prospect.Journal of enzyme inhibition and medicinal chemistry · 2026Review
- Drug repurposing in hereditary ataxia.npj drug discovery · 2026Review
- Article
- Experimental characterization of Pleurotus tuber-regium-derived silver nanoparticles and antifungal activity against Aspergillus fumigatus, Cryptococcus neoformans, and Candida albicans.Archives of microbiology · 2026Article
- Development of Benzothiophene-Bearing Bis-oxadiazole Derivatives for Potential Anticancer Targets: Evaluation of DFT, ADME-Tox, and In Silico Docking.Chemistry & biodiversity · 2026Article
- Chemical language models for early-stage drug discovery: applications, pitfalls, and future directions.Journal of computer-aided molecular design · 2026Review
- Quantum Theoretical, Chemo-Computational, and Comparative Molecular Coupling Studies of Two Enantiomeric Naphthoquinones, Alkannin and Shikonin, and Their Corresponding Indole Derivatives.Molecules (Basel, Switzerland) · 2026Article
- Cracking ERα Y537S Resistance: Explainable Machine Learning-Guided Discovery and Molecular Dynamics Validation of Stable Candidate Ligands.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Docking-based virtual screening: Past, present, and future.Biophysical journal · 2026Review
- An extension of jamdock-suite for virtual screening from raw chemical datasets.STAR protocols · 2026Article
- AGC kinase homology requires and enables co-targeting for CNS regeneration.bioRxiv : the preprint server for biology · 2026Article
- Drug Design Studio (DDS) 2.0: A Unified Platform for Network Pharmacology Integrated with Docking and Virtual Screening Workflow for Covalent/Non-Covalent Binders.International journal of molecular sciences · 2026Article
- 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
- Pushing the boundaries of virtual screening scale of combinatorial spaces with the V-SYNTHES approach.npj drug discovery · 2026Article
464 more citing papers are in PubMed but not listed here.
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
No grant is acknowledged in the PubMed record.
Abstract
Computer-aided drug discovery has been around for decades, although the past few years have seen a tectonic shift towards embracing computational technologies in both academia and pharma. This shift is largely defined by the flood of data on ligand properties and binding to therapeutic targets and their 3D structures, abundant computing capacities and the advent of on-demand virtual libraries of drug-like small molecules in their billions. Taking full advantage of these resources requires fast computational methods for effective ligand screening. This includes structure-based virtual screening of gigascale chemical spaces, further facilitated by fast iterative screening approaches. Highly synergistic are developments in deep learning predictions of ligand properties and target activities in lieu of receptor structure. Here we review recent advances in ligand discovery technologies, their potential for reshaping the whole process of drug discovery and development, as well as the challenges they encounter. We also discuss how the rapid identification of highly diverse, potent, target-selective and drug-like ligands to protein targets can democratize the drug discovery process, presenting new opportunities for the cost-effective development of safer and more effective small-molecule treatments.
Indexed as
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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.