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

Area of Science:

• Biochemistry
• Computational Biology
• Drug Discovery

Background:

• COVID-19 presents a significant global health challenge, necessitating rapid innovation.
• Artificial intelligence (AI) and machine learning (ML) are emerging as powerful tools in scientific research and development.
• The pandemic has spurred advancements in applying AI/ML to understand viral structures and develop therapeutics.

Purpose of the Study:

• To survey the current applications of AI and ML in the biochemistry of SARS-CoV-2.
• To provide an overview of AI/ML methods in structural biology and drug development for COVID-19.
• To motivate researchers to leverage AI/ML for combating the COVID-19 pandemic.

Main Methods:

• Review of AI and ML algorithms used in SARS-CoV-2 research.
• Analysis of AI applications in protein structure prediction.
• Examination of ML approaches for drug repurposing and novel compound identification.

Main Results:

• AI/ML methods are being utilized for predicting the structure of SARS-CoV-2 proteins.
• Algorithms have successfully identified potential antiviral drugs, including repurposing existing ones.
• AI is instrumental in proposing new chemical entities for drug development against COVID-19.

Conclusions:

• AI and ML are crucial for accelerating the drug discovery and development pipeline for COVID-19.
• The integration of AI/ML in structural biology and drug repurposing shows significant promise.
• Continued research and application of AI/ML are vital in the ongoing fight against COVID-19.