HHsenser

HHsenser performs sensitive iterative sequence searches using hidden Markov model (HMM) comparisons to detect near and remote protein homologs and produce multiple alignments for analysis of protein superfamilies.

Key Features:

• Exhaustive Intermediate Profile Searches: Conducts exhaustive intermediate profile searches to increase sensitivity for detecting homologous sequences.
• Iterative HMM-HMM Comparisons: Employs pairwise hidden Markov model (HMM-HMM) comparisons iteratively to expand and refine profile matches.
• Start Inputs: Accepts either a single protein sequence or a multiple sequence alignment as the initial query.
• Detection of Near and Remote Homologs: Expands queries to include numerous near and remote homologs within protein superfamilies.
• Multiple Alignment Output: Produces a multiple sequence alignment of all detected homologs for downstream analyses.
• Minimal False Positives: Designed to yield few or no false positives in detected matches.

Scientific Applications:

• Evolutionary Studies: Enables exploration of protein superfamilies to infer relationships and diversification across homologs.
• Homology-Based Structure Prediction: Provides diverse multiple sequence alignments useful for homology-based protein structure prediction.
• Function Prediction: Supports protein function inference by identifying conserved residues across homologous sequences.
• Conservation Scoring and Functional Subtyping: Facilitates conservation scoring and functional subtyping to identify functional residues and subfamily distinctions.

Methodology:

Begins with a single sequence or an alignment and iteratively expands the query by exhaustive intermediate profile searches combined with pairwise HMM-HMM comparisons to detect near and remote homologs and produce multiple alignments.