ArticleComputers in biology and medicine2021
Identification of novel compounds against three targets of SARS CoV-2 coronavirus by combined virtual screening and supervised machine learning.
Article in Computers in biology and medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 86 papers, 2 of them syntheses that pooled it.
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Who cites it
86 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Combating COVID-19 Crisis using Artificial Intelligence (AI) Based Approach: Systematic Review.Current topics in medicinal chemistry · 2024Pooled it
- Emerging role of artificial intelligence in therapeutics for COVID-19: a systematic review.Journal of biomolecular structure & dynamics · 2022Pooled it
- Discovery of HAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Developments in the Management Strategies for Allergy: Advances in Artificial Intelligence and Future Perspectives.Anti-inflammatory & anti-allergy agents in medicinal chemistry · 2026Review
- Structure based drug design and machine learning approaches for identifying natural inhibitors against the human αβIII tubulin isotype.Scientific reports · 2025Article
- A parallel texture-based region-growing algorithm implemented in OpenMP.Scientific reports · 2025Article
- In silico drug repurposing of potential antiviral inhibitors targeting methyltransferase (2'-O-MTase) domain of Marburg virus.In silico pharmacology · 2025Article
- Screening inhibitors against the Ef-Tu of Fusobacterium nucleatum: a docking, ADMET and PBPK assessment study.Molecular diversity · 2024Article
- Cheminformatics approach to identify andrographolide derivatives as dual inhibitors of methyltransferases (nsp14 and nsp16) of SARS-CoV-2.Scientific reports · 2024Article
- Potential Inhibitors of Lumpy Skin Disease's Viral Protein (DNA Polymerase): A Combination of Bioinformatics Approaches.Animals : an open access journal from MDPI · 2024Article
- The Three-Dimensional Reference Interaction Site Model Approach as a Promising Tool for Studying Hydrated Viruses and Their Complexes with Ligands.International journal of molecular sciences · 2024Review
- Staying Ahead of the Game: How SARS-CoV-2 has Accelerated the Application of Machine Learning in Pandemic Management.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2023Review
- Strictinin: A Key Ingredient of Tea.Molecules (Basel, Switzerland) · 2023Review
- Bioinformatics-based investigation on the genetic influence between SARS-CoV-2 infections and idiopathic pulmonary fibrosis (IPF) diseases, and drug repurposing.Scientific reports · 2023Article
- Identification of host genomic biomarkers from multiple transcriptomics datasets for diagnosis and therapies of SARS-CoV-2 infections.PloS one · 2023Article
- Innovative applications of artificial intelligence in zoonotic disease management.Science in One Health · 2023Review
- A review onExploration of targeted anti-tumor therapy · 2023Review
- In Silico Identification of Anti-SARS-CoV-2 Medicinal Plants Using Cheminformatics and Machine Learning.Molecules (Basel, Switzerland) · 2022Article
- Supervised Machine Learning Models to Identify Early-Stage Symptoms of SARS-CoV-2.Sensors (Basel, Switzerland) · 2022Article
- Antiviral activity of amiodarone in SARS-CoV-2 disease.Physiological research · 2022Article
26 more citing papers are in PubMed but not listed here.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Coronavirus disease 2019 (COVID-19) is a major threat worldwide due to its fast spreading. As yet, there are no established drugs available. Speeding up drug discovery is urgently required. We applied a workflow of combined in silico methods (virtual drug screening, molecular docking and supervised machine learning algorithms) to identify novel drug candidates against COVID-19. We constructed chemical libraries consisting of FDA-approved drugs for drug repositioning and of natural compound datasets from literature mining and the ZINC database to select compounds interacting with SARS-CoV-2 target proteins (spike protein, nucleocapsid protein, and 2'-o-ribose methyltransferase). Supported by the supercomputer MOGON, candidate compounds were predicted as presumable SARS-CoV-2 inhibitors. Interestingly, several approved drugs against hepatitis C virus (HCV), another enveloped (-) ssRNA virus (paritaprevir, simeprevir and velpatasvir) as well as drugs against transmissible diseases, against cancer, or other diseases were identified as candidates against SARS-CoV-2. This result is supported by reports that anti-HCV compounds are also active against Middle East Respiratory Virus Syndrome (MERS) coronavirus. The candidate compounds identified by us may help to speed up the drug development against SARS-CoV-2.
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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.