CusProSe

CusProSe identifies and annotates proteins based on their domain composition to predict genes involved in fungal secondary metabolism.

Key Features:

• Customizability: Allows user-customized searches and annotations via configurable HMM profile construction and rule sets.
• IterHMMBuild: Iteratively constructs Hidden Markov Model (HMM) profiles from conserved domains within selected protein sequences.
• ProSeCDA: Scans target proteomes against a database of HMM profiles and annotates matching proteins using user-defined rules.
• Fungal secondary metabolism enzyme identification: Identifies genes encoding polyketide synthases (PKS), non-ribosomal peptide synthetases (NRPS), hybrid PKS-NRPS, dimethylallyl tryptophan synthases (DMATS), and terpene synthase (TS) sub-families.
• Broad applicability: Configurable to annotate protein families and predict metabolism-related genes in biological systems beyond fungal genomics.

Scientific Applications:

• Functional prediction refinement: Refines protein functional predictions through domain-based annotation.
• Novel enzyme family detection: Extends detection capabilities to novel enzyme families via iterative HMM profile building.
• Secondary metabolism gene prediction: Facilitates prediction and characterization of genes involved in secondary metabolism and related metabolic pathways.
• Cross-taxa annotation: Supports annotation workflows adaptable to organisms beyond fungi.

Methodology:

IterHMMBuild iteratively constructs HMM profiles from conserved domains in selected protein sequences; ProSeCDA scans target proteomes against the HMM profile database and annotates matching proteins using user-defined rules.