Artificial intelligence approaches to human-microbiome protein-protein interactions.

Journal: Current opinion in structural biology
Published Date:

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.

Authors

  • Hansaim Lim
  • Fatma Cankara
    Graduate School of Sciences and Engineering, KoƧ University, Istanbul, 34450, Turkey.
  • Chung-Jung Tsai
    Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, MD, 21702, USA.
  • Ozlem Keskin
    Department of Chemical and Biological Engineering, Koc University, Istanbul, 34450, Turkey. Electronic address: okeskin@ku.edu.tr.
  • Ruth Nussinov
    Computational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, National Cancer Institute at Frederick, Frederick, MD 21702, USA.
  • Attila Gursoy
    Department of Computer Engineering, Koc University, Istanbul, 34450, Turkey. Electronic address: agursoy@ku.edu.tr.