Exploring functional insights into the human gut microbiome via the structural proteome.

Area of Science:

• Microbiology
• Structural Biology
• Bioinformatics

Background:

• The human gut microbiome's proteome is vast, with many protein functions unknown.
• Sequence-based methods struggle to identify functions due to evolutionary divergence.
• Understanding these proteins is crucial for host health.

Purpose of the Study:

• To develop a comprehensive database of predicted protein structures from the human gut microbiome.
• To leverage structural information for functional annotation and discovery.
• To enhance the understanding of microbial protein functions and their roles in host health.

Main Methods:

• Development of the Human Gut Microbial Protein Structure Database (∼2.7 million predicted structures).
• Utilizing structural analogy for protein function annotation, particularly for phage proteins.
• Employing structure-guided approaches and structural alignments for enzyme identification.
• Implementing an alignment-free method, dense enzyme retrieval, based on structure-encoded protein language models.

Main Results:

• Structural analogy significantly improves the annotation of phage proteins.
• Revealed structural diversification of phage endolysins with potential to eliminate gut pathobionts.
• Identified microbial-host isozymes and previously unrecognized bacterial enzymes in melatonin biosynthesis.
• Demonstrated ultrafast and sensitive detection of remote homologs using dense enzyme retrieval.

Conclusions:

• Computational structural genomics is valuable for functional elucidation in the gut microbiome.
• The Human Gut Microbial Protein Structure Database provides a powerful resource for exploring microbial protein functions.
• Structure-based methods offer new avenues for discovering microbial functions and potential therapeutic targets.