ReviewFrontiers in microbiology2021
Deep Learning Driven Drug Discovery: Tackling Severe Acute Respiratory Syndrome Coronavirus 2.
Review in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed.
- A novel framework for the discovery of MAPK-activated protein kinase 2 (MAPKAPK2) inhibitors using a multi-feature deep learning ensemble.Journal of computer-aided molecular design · 2026Article
- Advancing Antiviral Design: Integrating Natural Products, Computation and Targeted Delivery.Chemical biology & drug design · 2026Review
- Drug repurposing against viral infections (2020-2025): clinical trials, computational strategies, and therapeutic interventions.Inflammopharmacology · 2026Review
- Advancing Drug Discovery with AI: Machine and Deep Learning Strategies for Target Identification and Precision Nanomedicine.International journal of nanomedicine · 2026Review
- Review
- Biomolecular Interaction Prediction: The Era of AI.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- MetaboGNN: predicting liver metabolic stability with graph neural networks and cross-species data.Journal of cheminformatics · 2025Article
- The physics-AI dialogue in drug design.RSC medicinal chemistry · 2025Review
- Benzoxanthenone Lignans Related to Carpanone, Polemanone, and Sauchinone: Natural Origin, Chemical Syntheses, and Pharmacological Properties.Molecules (Basel, Switzerland) · 2025Review
- Unveiling the ghost: machine learning's impact on the landscape of virology.The Journal of general virology · 2025Review
- HBCVTr: an end-to-end transformer with a deep neural network hybrid model for anti-HBV and HCV activity predictor from SMILES.Scientific reports · 2024Article
- TCRcost: a deep learning model utilizing TCR 3D structure for enhanced of TCR-peptide binding.Frontiers in genetics · 2024Article
- Small molecule-mediated targeting of microRNAs for drug discovery: Experiments, computational techniques, and disease implications.European journal of medicinal chemistry · 2023Review
- AI-Driven De Novo Design and Molecular Modeling for Discovery of Small-Molecule Compounds as Potential Drug Candidates Targeting SARS-CoV-2 Main Protease.International journal of molecular sciences · 2023Article
- Artificial Intelligence, Machine Learning, and Big Data for Ebola Virus Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2023Article
- Novel computational pipelines in antiviral structure‑based drug design (Review).Biomedical reports · 2022Review
- A comprehensive review of artificial intelligence and network based approaches to drug repurposing in Covid-19.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2022Review
- Deep learning-based molecular dynamics simulation for structure-based drug design against SARS-CoV-2.Computational and structural biotechnology journal · 2022Review
- MDGNN: Microbial Drug Prediction Based on Heterogeneous Multi-Attention Graph Neural Network.Frontiers in microbiology · 2022Article
- Artificial Intelligence and Antibiotic Discovery.Antibiotics (Basel, Switzerland) · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Deep learning significantly accelerates the drug discovery process, and contributes to global efforts to stop the spread of infectious diseases. Besides enhancing the efficiency of screening of antimicrobial compounds against a broad spectrum of pathogens, deep learning has also the potential to efficiently and reliably identify drug candidates against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Consequently, deep learning has been successfully used for the identification of a number of potential drugs against SARS-CoV-2, including Atazanavir, Remdesivir, Kaletra, Enalaprilat, Venetoclax, Posaconazole, Daclatasvir, Ombitasvir, Toremifene, Niclosamide, Dexamethasone, Indomethacin, Pralatrexate, Azithromycin, Palmatine, and Sauchinone. This mini-review discusses recent advances and future perspectives of deep learning-based SARS-CoV-2 drug discovery.
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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.