Application of machine learning on understanding biomolecule interactions in cellular machinery

Artificial intelligence (AI) and machine learning (ML) applications have become ubiquitous in all fields of research including protein science and engineering. AI and ML are being used to not only predict the structures of the proteins but to edit the protein sequence to give them desired properties and enhance their functions. Thus, there is a need to study how these proteins are interacting with other components in the experimental setup or the human body. With the increasing interest in the above-mentioned research gaps, scientists are working on several wet-lab techniques and adding to the knowledge pool. However, this information is scattered and enormous. Hence, AI and ML come to the rescue. It can handle bulk data and organize and produce models that can make sense of the information. Therefore, the involvement of AI and ML is inevitable, and this review highlights these points.