SBPKS2

SBPKS2 performs genome-guided discovery and analysis of polyketide and non-ribosomal peptide (PKS/NRPS) biosynthetic pathways to predict and compare biosynthetic intermediates and final products.

Key Features:

• Chemical Space Exploration: Searches chemical space by comparing the chemical structures of secondary metabolites against biosynthetic intermediates and final products.
• Profile-Based Domain Identification: Employs profile-based searches for catalytic domain identification that are computationally efficient and highly sensitive.
• Enhanced Domain Analysis: Includes Hidden Markov Model (HMM) profiles for additional domains and uses motif information to distinguish condensation (C), epimerization (E), and cyclization (Cy) domains within NRPS.
• Experimentally Characterized Cluster Integration: Incorporates analysis derived from 311 experimentally characterized PKS/NRPS gene clusters with known biosynthetic outcomes.

Scientific Applications:

• Genome mining of biosynthetic gene clusters: Enables identification and annotation of PKS and NRPS gene clusters from genome sequences.
• Natural product discovery and identification: Facilitates comparison of candidate metabolites to known intermediates and products to support discovery of novel polyketides and non-ribosomal peptides.
• Domain annotation and biosynthetic pathway elucidation: Provides sensitive domain detection and motif-based discrimination to aid reconstruction of secondary metabolite biosynthetic routes.

Methodology:

Profile-based searches, Hidden Markov Model (HMM) profiles for domain detection, motif-based discrimination of C/E/Cy domains, chemical-structure comparison of secondary metabolites with biosynthetic intermediates and products, integration of sequence data, structural information, and known chemical structures, and analysis derived from 311 experimentally characterized PKS/NRPS gene clusters.