ArticleInternational journal of molecular sciences2021
Predicting Potential SARS-COV-2 Drugs-In Depth Drug Database Screening Using Deep Neural Network Framework SSnet, Classical Virtual Screening and Docking.
Article in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Emerging role of artificial intelligence in therapeutics for COVID-19: a systematic review.Journal of biomolecular structure & dynamics · 2022Pooled it
- Possible Therapeutic Effects of Adjuvant Quercetin Supplementation Against Early-Stage COVID-19 Infection: A Prospective, Randomized, Controlled, and Open-Label Study.International journal of general medicine · 2021Trial
- Advancing Antiviral Design: Integrating Natural Products, Computation and Targeted Delivery.Chemical biology & drug design · 2026Review
- Lessons learnt from broad-spectrum coronavirus antiviral drug discovery.Expert opinion on drug discovery · 2024Review
- Tribulations and future opportunities for artificial intelligence in precision medicine.Journal of translational medicine · 2024Review
- The Potential Applications and Challenges of ChatGPT in the Medical Field.International journal of general medicine · 2024Review
- The Role of AI in Drug Discovery: Challenges, Opportunities, and Strategies.Pharmaceuticals (Basel, Switzerland) · 2023Review
- Machine learning and protein allostery.Trends in biochemical sciences · 2023Review
- Artificial Intelligence, Machine Learning, and Big Data for Ebola Virus Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2023Article
- Virtual screening and molecular dynamics simulations provide insight into repurposing drugs against SARS-CoV-2 variants Spike protein/ACE2 interface.Scientific reports · 2023Article
- Innovative applications of artificial intelligence in zoonotic disease management.Science in One Health · 2023Review
- A review of SARS-CoV-2 drug repurposing: databases and machine learning models.Frontiers in pharmacology · 2023Review
- Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2.Chemical reviews · 2022Review
- A multilevel approach for screening natural compounds as an antiviral agent for COVID-19.Computational biology and chemistry · 2022Article
- Machine learning prediction of 3CLComputational biology and chemistry · 2022Article
- Allosteric control of ACE2 peptidase domain dynamics.Organic & biomolecular chemistry · 2022Article
- Artificial Intelligence Technologies for COVID-19 De Novo Drug Design.International journal of molecular sciences · 2022Review
- Deep learning-based molecular dynamics simulation for structure-based drug design against SARS-CoV-2.Computational and structural biotechnology journal · 2022Review
- Inhibition Ability of Natural Compounds on Receptor-Binding Domain of SARS-CoV2: An In Silico Approach.Pharmaceuticals (Basel, Switzerland) · 2021Article
- Screening S protein - ACE2 blockers from natural products: Strategies and advances in the discovery of potential inhibitors of COVID-19.European journal of medicinal chemistry · 2021Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Severe Acute Respiratory Syndrome Corona Virus 2 has altered life on a global scale. A concerted effort from research labs around the world resulted in the identification of potential pharmaceutical treatments for CoVID-19 using existing drugs, as well as the discovery of multiple vaccines. During an urgent crisis, rapidly identifying potential new treatments requires global and cross-discipline cooperation, together with an enhanced open-access research model to distribute new ideas and leads. Herein, we introduce an application of a deep neural network based drug screening method, validating it using a docking algorithm on approved drugs for drug repurposing efforts, and extending the screen to a large library of 750,000 compounds for de novo drug discovery effort. The results of large library screens are incorporated into an open-access web interface to allow researchers from diverse fields to target molecules of interest. Our combined approach allows for both the identification of existing drugs that may be able to be repurposed and de novo design of ACE2-regulatory compounds. Through these efforts we demonstrate the utility of a new machine learning algorithm for drug discovery, SSnet, that can function as a tool to triage large molecular libraries to identify classes of molecules with possible efficacy.
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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.