HHpred

HHpred detects remote protein homology and predicts three-dimensional protein structure by performing pairwise comparisons of profile hidden Markov models (HMMs).

Key Features:

• Input Flexibility: Accepts a single protein sequence or a multiple sequence alignment (MSA) as input.
• Pairwise HMM Comparison: Performs pairwise comparisons of profile hidden Markov models (HMMs) for sensitive detection of distant homologues.
• Database Search Capability: Searches across PDB (Protein Data Bank), SCOP, Pfam, SMART, COGs, and CDD databases.
• Alignment Methods: Supports local and global alignment modes for HMM–HMM comparisons.
• Secondary Structure Scoring: Incorporates secondary structure scoring to augment sequence-based similarity detection.
• Output Options: Produces pairwise query–template alignments, multiple alignments with selected templates, and generates 3D structural models using MODELLER, with outputs analogous to PSI-BLAST reports.
• Server-based Execution: Implements server-based HMM–HMM comparisons for rapid searches.

Scientific Applications:

• Protein structure prediction: Identifying structural templates and producing MODELLER-based 3D models from sequence data.
• Remote homology detection: Detecting distant evolutionary relationships among proteins via HMM–HMM comparison.
• Functional annotation: Assigning putative functions and conserved domains by matching queries to Pfam, SMART, CDD, and COGs entries.
• Structure–function inference: Informing analyses of protein function and interaction networks through template-based models and alignments.

Methodology:

Performs pairwise comparisons of profile HMMs (using local or global alignment and optional secondary structure scoring), searches HMMs against PDB, SCOP, Pfam, SMART, COGs, and CDD, accepts sequence or MSA input, and generates 3D models with MODELLER.