Ab initio protein modelling reveals novel human MIT domains

Area of Science:

• Bioinformatics
• Structural Biology
• Molecular Biology

Background:

• Standard database searches may miss homologous sequences, especially for short or diverse protein families.
• Microtubule interacting and transport (MIT) domains are crucial for cellular processes.

Purpose of the Study:

• To develop and apply a novel computational approach for detecting true homologous sequences missed by conventional database searches.
• To identify novel MIT domains within protein families exhibiting high sequence diversity.

Main Methods:

• Utilized profile-profile matching combined with ab initio structure modeling.
• Applied the method to identify homologous sequences in the borderline significant zone of database searches.
• Focused on microtubule interacting and transport (MIT) domains as a model system.

Main Results:

• Successfully identified novel MIT domains in USP54, KATNAL1, and an uncharacterized protein with a VPS9 domain.
• USP54 was found to contain an apparently inactive ubiquitin carboxyl-terminal hydrolase domain alongside the novel MIT domain.
• Confirmed the MIT domain annotation for USP54 through in vitro binding assays with CHMP proteins.

Conclusions:

• The combined profile-profile matching and ab initio modeling approach enhances the detection of homologous sequences, particularly for challenging protein families.
• This method expands the known repertoire of proteins containing MIT domains, including those in USP54, KATNAL1, and VPS9-domain containing proteins.
• The findings provide a validated strategy for improving sequence homology detection in bioinformatics.