Artificial intelligence approaches to human-microbiome protein–protein interactions |
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| Institution: | 1. Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD, 21702, USA;2. Graduate School of Sciences and Engineering, Koç University, Istanbul, 34450, Turkey;3. Department of Chemical and Biological Engineering, Koç University, Istanbul, 34450, Turkey;4. Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, 69978, Israel;5. Department of Computer Engineering, Koç University, Istanbul, 34450, Turkey |
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| Abstract: | Host-microbiome interactions play significant roles in human health and disease. Artificial intelligence approaches have been developed to better understand and predict the molecular interplay between the host and its microbiome. Here, we review recent advancements in computational methods to predict microbial effects on human cells with a special focus on protein–protein interactions. We categorize recent methods from traditional ones to more recent deep learning methods, followed by several challenges and potential solutions in structure-based approaches. This review serves as a brief guide to the current status and future directions in the field. |
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