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Artificial intelligence-driven drug repurposing and structural biology for SARS-CoV-2.
Prasad, Kartikay; Kumar, Vijay.
  • Prasad K; Amity Institute of Neuropsychology & Neurosciences, Amity University, Noida, UP, 201303, India.
  • Kumar V; Amity Institute of Neuropsychology & Neurosciences, Amity University, Noida, UP, 201303, India.
Curr Res Pharmacol Drug Discov ; 2: 100042, 2021.
Article in English | MEDLINE | ID: covidwho-1555960
ABSTRACT
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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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Journal: Curr Res Pharmacol Drug Discov Year: 2021 Document Type: Article Affiliation country: J.crphar.2021.100042

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study / Prognostic study Language: English Journal: Curr Res Pharmacol Drug Discov Year: 2021 Document Type: Article Affiliation country: J.crphar.2021.100042