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Artificial Intelligence Technologies for COVID-19 De Novo Drug Design.
Floresta, Giuseppe; Zagni, Chiara; Gentile, Davide; Patamia, Vincenzo; Rescifina, Antonio.
  • Floresta G; Dipartimento di Scienze del Farmaco e della Salute, Università di Catania, Viale A. Doria 6, 95125 Catania, Italy.
  • Zagni C; Dipartimento di Scienze del Farmaco e della Salute, Università di Catania, Viale A. Doria 6, 95125 Catania, Italy.
  • Gentile D; Dipartimento di Scienze del Farmaco e della Salute, Università di Catania, Viale A. Doria 6, 95125 Catania, Italy.
  • Patamia V; Dipartimento di Scienze del Farmaco e della Salute, Università di Catania, Viale A. Doria 6, 95125 Catania, Italy.
  • Rescifina A; Dipartimento di Scienze del Farmaco e della Salute, Università di Catania, Viale A. Doria 6, 95125 Catania, Italy.
Int J Mol Sci ; 23(6)2022 Mar 17.
Article in English | MEDLINE | ID: covidwho-1760650
ABSTRACT
The recent covid crisis has provided important lessons for academia and industry regarding digital reorganization. Among the fascinating lessons from these times is the huge potential of data analytics and artificial intelligence. The crisis exponentially accelerated the adoption of analytics and artificial intelligence, and this momentum is predicted to continue into the 2020s and beyond. Drug development is a costly and time-consuming business, and only a minority of approved drugs generate returns exceeding the research and development costs. As a result, there is a huge drive to make drug discovery cheaper and faster. With modern algorithms and hardware, it is not too surprising that the new technologies of artificial intelligence and other computational simulation tools can help drug developers. In only two years of covid research, many novel molecules have been designed/identified using artificial intelligence methods with astonishing results in terms of time and effectiveness. This paper reviews the most significant research on artificial intelligence in de novo drug design for COVID-19 pharmaceutical research.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Artificial Intelligence / Drug Design / SARS-CoV-2 / COVID-19 / COVID-19 Drug Treatment Type of study: Prognostic study Topics: Traditional medicine Limits: Humans Language: English Year: 2022 Document Type: Article Affiliation country: Ijms23063261

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Antiviral Agents / Artificial Intelligence / Drug Design / SARS-CoV-2 / COVID-19 / COVID-19 Drug Treatment Type of study: Prognostic study Topics: Traditional medicine Limits: Humans Language: English Year: 2022 Document Type: Article Affiliation country: Ijms23063261