HHomp

HHomp predicts and classifies beta-barrel outer membrane proteins (OMPs) from Gram-negative bacteria, mitochondria, and plastids by constructing profile hidden Markov models (HMMs) from query sequences and comparing them to a curated OMP HMM database with integration of PROFtmb predictions.

Key Features:

• Homology-Based Prediction: Detects beta-barrel OMPs by exploiting their shared ancestry and homologous relationships to known sequences.
• Profile HMM Construction: Builds a profile hidden Markov model tailored to each input protein sequence for sensitive sequence modeling.
• Pairwise HMM Comparison: Performs pairwise comparisons between the query-derived HMM and database HMMs to assign predictions and classifications.
• Extensive OMP Database: Uses a database of over 20,000 putative OMP sequences represented as profile HMMs, compiled using the HHsenser method starting from 23 representative OMPs from the Protein Data Bank (PDB).
• Integration with PROFtmb: Integrates PROFtmb beta-barrel predictions to support and refine OMP identification.
• Benchmark Performance: On TransportDB, detected 63.5% of true positives before any false positives and, in Escherichia coli, identified 57 of 59 known OMPs and assigned them to functional subgroups; reported comparative improvements versus PROFtmb, BOMP, and TMB-Hunt as stated in the original benchmarks.

Scientific Applications:

• Microbial genomics and proteomics: Identification and cataloging of OMPs in bacterial genomes and proteomes.
• Bacterial physiology and pathogenicity studies: Analysis of OMPs relevant to membrane function, virulence, and host interaction.
• Antimicrobial strategy development: Prioritization of OMPs as targets for antimicrobial research and intervention.
• Functional subgroup assignment: Classification of OMPs into functional subgroups to support studies of protein function and membrane interactions.

Methodology:

Input protein sequences are used to construct profile HMMs, which are compared pairwise against a database of OMP profile HMMs (the database compiled with HHsenser from 23 PDB OMPs into over 20,000 HMMs), and results are integrated with PROFtmb predictions for final prediction and classification.