Identification of key functional sites for ATPase activity in the OBC protein complex using artificial intelligence approaches

doi:10.1088/1674-1056/ae0891

Abstract Microorganisms evolve diverse immune defense systems to protect against phage and viral invasion. The bacteriophage exclusion (BREX) system represents a common bacterial genomic defense mechanism, and preliminary studies indicate that the interaction between BrxC and OrbA proteins (forming the OBC complex) can alter the aggregation pattern of defense system components and modulate immune function. Notably, the adenosine triphosphatase (ATPase) domain of this system plays a pivotal role. This study employs optimized network screening (ONS), an artificial intelligence-based integrated analytical approach combining machine learning and deep learning, to identify critical enzymatic active sites in target macromolecular complexes and to provide crucial insights for potential drug target discovery. Through comprehensive ONS analysis of multiple sites, we identified lysine (K73) as a key residue governing the ATPase activity of this protein complex. Following plasmid construction and expression, we successfully purified the OrbA-BrxC (OBC) complex, along with newly engineered OBCK (K73A mutant of the OBC complex) and the negative control OBCE (E255A mutant of the OBC complex). ATPase activity assays demonstrated complete loss of enzymatic function in the OBCK mutant, confirming K73 as the essential catalytic site for BREX system ATPase activity. Comparative analysis revealed minimal differences between OBC and OBCE complexes, but significant divergence from OBCK. The single K73 mutation alone was sufficient to abolish critical enzymatic activity and disrupt BREX system function, achieving efficient complex engineering without requiring multiple mutations. Building on this artificial intelligence methodology, we further analyzed potential functional sites and antigenic epitopes in OBC and OBCK complexes, thereby establishing a research foundation for developing anti-drug-resistant pathogen therapeutics.

Keywords: artificial intelligence methods BREX defense system co-expression and purification ATPase activity construction of protein complexes

Received: 25 April 2025
Revised: 12 September 2025
Accepted manuscript online: 18 September 2025

PACS:	87.14.E-	(Proteins)
	87.15.hp	(Conformational changes)
	87.15.km	(Protein-protein interactions)
	87.50.sg	(Biophysical mechanisms of interaction)

Fund: This project was supported by the National Natural Science Foundation of China (Grant No. 82272308).

Corresponding Authors: Kun Shang
E-mail: puospumu@yeah.net

Cite this article:

Lei Hua(花蕾), Yuhang He(贺宇航), Peng Zhao(赵澎), Jiayao Liu(刘嘉瑶), and Kun Shang(尚坤) Identification of key functional sites for ATPase activity in the OBC protein complex using artificial intelligence approaches 2026 Chin. Phys. B 35 048702

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Identification of key functional sites for ATPase activity in the OBC protein complex using artificial intelligence approaches

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