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

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.

Wird KI neue Medikamente gegen Herzkrankheiten hervorbringen?

“…Dies könnte zur Identifizierung einer größeren Anzahl von potenziellen Zielproteinen beitragen. Solche Formen der Mustererkennung können auch dabei helfen, neue Anwendungen für bereits zugelassene Medikamente zu identifizieren [12].…”

Developing a SARS-CoV-2 main protease binding prediction random forest model for drug repurposing for COVID-19 treatment

“…Because of the knowledge and understanding of an existing drug’s safety, mechanisms of action, and pharmacokinetics, drug repurposing reduces the risks associated with drug development, and has shown promising results for the discovery of the main protease inhibitors, 17–19 especially when combined with the power of artificial intelligence approaches. 20…”

“…Because of the knowledge and understanding of an existing drug's safety, mechanisms of action, and pharmacokinetics, drug repurposing reduces the risks associated with drug development, and has shown promising results for the discovery of the main protease inhibitors, [17][18][19] especially when combined with the power of artificial intelligence approaches. 20 Machine learning is the approach to learn from the provided data, identify the patterns within the provided data, and make predictions on new data using what it has learned. Machine learning methods have been widely used for toxicity prediction, novel drug discovery, and drug repurposing.…”

Antiviral Potential of Plants against COVID-19 during Outbreaks—An Update

“…The majority of previous papers and studies have primarily concentrated on specific ethnobotanical drugs, such as traditional Chinese or Indian medicines [ 11 , 12 , 13 , 14 , 15 ], without regard to particular locations or ethnobotanical characteristics. In addition to core wet laboratory experiments, several modern computational methodologies have been adopted for screening and identifying natural compounds that may inhibit viral infection, and the utilization of these approaches to identify fast-acting and more potent vaccines and treatments, including drugs, for COVID-19, increased during the recent pandemic [ 16 , 17 , 18 ]. Many major scientific databases have been established to help researchers identify possible ethnomedicinal plants or herbs for use as antivirals, including for coronavirus treatments.…”