PolypharmDB, a deep learning-based resource, quickly identifies repurposed drug candidates for COVID-19

Redka, Dar′ya S.; Kurji, Naheed; Shahani, Vijay; Windemuth, Andreas; Mackinnon, Stephen; Landon, Melissa R.

doi:10.1021/scimeetings.0c06821

Cited by 4 publications

(4 citation statements)

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“… Author Study keywords Targets No. of drugs Reference Ke, Y. Y Deep neural network FIP 80 Ke et al (2020) Ge, Y Knowledge Graph, deep learning SARS-CoV-2 64 Ge et al (2020) Beck, B. R Hybrid CNN and RNN model called MT-DTI 3CLpro, RdRp, helicase, 3′-to-5′ exonuclease, endoRNAse, and 2′-O-ribose methyltransferase 3410 Beck et al (2020) Zeng, X Deep learning-based knowledge graph (CoV-KGE), SARS-CoV-2 41 Zeng et al (2020) Gao, K 2-D fingerprint, GBDT model, Recurrent Neural Network (RNN) 3CLpro 40 Gao et al (2020) Hofmarcher, M Deep neural network, ChemAI 3CLpro, PLP 20 Hofmarcher et al (2020) Ton, A. T deep learning platform – Deep Docking (DD) Mpro 1000 Ton et al (2020) Hu, F Deep learning-based multi-task models, Classification and Regression 3CLpro 10 Hu and Jiang (2020) Gysi, D.M Graph Neural Network SARS-CoV-2 77 Gysi et al (2020) Huang, K Deep Purpose, Python toolkit, CNN 3CLpro 13 Huang et al (2020b) Batra, R Random forest (RF) regression algorithm, ensemble docking S, S-ACE2 complex 187 Batra et al (2020) Redka, D.S Deep learning, Ligand Design, MatchMaker, PolypharmDB 3CLpro, Spike; ACE2, TMPRSS2, Cathepsin B 30 Redka...…”

Section: Resultsmentioning

confidence: 99%

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Artificial intelligence-driven drug repurposing and structural biology for SARS-CoV-2

Prasad

Kumar

2021

Current Research in Pharmacology and Drug Discovery

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It has been said that COVID-19 is a generational challenge in many ways. But, at the same time, it becomes a catalyst for collective action, innovation, and discovery. Realizing the full potential of artificial intelligence (AI) for structure determination of unknown proteins and drug discovery are some of these innovations. Potential applications of AI include predicting the structure of the infectious proteins, identifying drugs that may be effective in targeting these proteins, and proposing new chemical compounds for further testing as potential drugs. AI and machine learning (ML) allow for rapid drug development including repurposing existing drugs. Algorithms were used to search for novel or approved antiviral drugs capable of inhibiting SARS-CoV-2. This paper presents a survey of AI and ML methods being used in various biochemistry of SARS-CoV-2, from structure to drug development, in the fight against the deadly COVID-19 pandemic. It is envisioned that this study will provide AI/ML researchers and the wider community an overview of the current status of AI applications particularly in structural biology, drug repurposing, and development, and motivate researchers in harnessing AI potentials in the fight against COVID-19.

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Section: Resultsmentioning

confidence: 99%

“… Redka et al (2020) utilized DL platform, Ligand Design to identify the FDA-approved drugs and experimental medicines that have the potential to inhibit SARS-CoV-2 infection. They developed a resource, PoylpharmDB that contains over 10,224 drugs along with the computed list of ∼8700 proteins predicted to interact with them.…”

Section: Resultsmentioning

confidence: 99%

Artificial intelligence-driven drug repurposing and structural biology for SARS-CoV-2

Prasad

Kumar

2021

Current Research in Pharmacology and Drug Discovery

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“…Similarly, multiple deep learning techniques have also been used to identify the repurposable drug candidates for Covid-19. One of the deep learning-based studies, is done in [205] where deep learning-based drug screening was performed followed by a study done in [206] where a resource based on deep learning is created to enable the fast repurposing of the drug candidates for Covid-19. Finally, in the light of the examples tabulated in Table 8 , it can be concluded that the drug repurposing methods are quite helpful and quick to response in case Covid-19 and related emergent situations.…”

Section: Benefits Of Drug Repurposing Methods In Clinical Practicementioning

confidence: 99%

A comprehensive review of artificial intelligence and network based approaches to drug repurposing in Covid-19

Ahmed

Soomro

Salih

et al. 2022

Biomedicine & Pharmacotherapy

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“…Baricitinib was identified as a potential drug against COVID‐19 by using ML methods developed by BenevolentAI, 26,27 Several other molecules targeted against COVID‐19 have also been studied by Insilico Medicine 28 . Other AI‐based projects like IDentif.AI (identifying infectious disease combination therapy with artificial intelligence) 29 and PolypharmDB 30 have also contributed to discovering effective candidates against COVID‐19. Ong et al predicted possible vaccine candidates for COVID‐19 using the Vaxign reverse vaccinology‐ML platform 31 .…”

Section: Ai and Covid‐19 In Context Of Dermatology Clinical Practicementioning

confidence: 99%

COVID‐19 and artificial intelligence: Experts and dermatologists perspective

Goldust

Sameem

Mearaj³

et al. 2022

J of Cosmetic Dermatology

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Introduction Artificial intelligence (AI) has an important role to play in future healthcare offerings. Machine learning and artificial neural networks are subsets of AI that refer to the incorporation of human intelligence into computers to think and behave like humans. Objective The objective of this review article is to discuss perspectives on the AI in relation to Coronavirus disease (COVID‐19). Methods Google Scholar and PubMed databases were searched to retrieve articles related to COVID‐19 and AI. The current evidence is analysed and perspectives on the usefulness of AI in COVID‐19 is discussed. Results The coronavirus pandemic has rendered the entire world immobile, crashing economies, industries, and health care. Telemedicine or tele‐dermatology for dermatologists has become one of the most common solutions to tackle this crisis while adhering to social distancing for consultations. While it has not yet achieved its full potential, AI is being used to combat coronavirus disease on multiple fronts. AI has made its impact in predicting disease onset by issuing early warnings and alerts, monitoring, forecasting the spread of disease and supporting therapy. In addition, AI has helped us to build a model of a virtual protein structure and has played a role in teaching as well as social control. Conclusion Full potential of AI is yet to be realized. Expert data collection, analysis, and implementation are needed to improve this advancement.

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PolypharmDB, a deep learning-based resource, quickly identifies repurposed drug candidates for COVID-19

Cited by 4 publications

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Artificial intelligence-driven drug repurposing and structural biology for SARS-CoV-2

Artificial intelligence-driven drug repurposing and structural biology for SARS-CoV-2

A comprehensive review of artificial intelligence and network based approaches to drug repurposing in Covid-19

COVID‐19 and artificial intelligence: Experts and dermatologists perspective

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