SSNpipe

SSNpipe performs sequence similarity network (SSN) analysis to delineate evolutionary relationships and classify subfamilies within glycoside hydrolases.

Key Features:

• Sequence Similarity Network Analysis: Constructs and analyzes sequence similarity networks (SSNs) to resolve relationships within large and diverse protein families such as glycoside hydrolase family 16 (GH16).
• Subfamily Classification: Delineates nearly 23,000 GH16 sequences into 23 robust subfamilies supported by hidden Markov model and maximum likelihood molecular phylogenetic analyses.
• Structural Insights: Evaluates over 40 experimental three-dimensional structures to highlight tertiary structural differences, particularly in active-site loops, that influence substrate specificity across the GH16 evolutionary landscape.
• Guidance for Functional Glycogenomics: Provides a subfamily framework that informs functional glycogenomics and supports bioinformatics and experimental structure-function analyses for large glycoside hydrolase families such as GH5, GH13, and GH43.

Scientific Applications:

• Evolutionary and functional analysis: Enables systematic study of protein evolution and functional diversification within glycoside hydrolases.
• Enzyme function prediction: Aids prediction of enzyme functions and substrate specificities across ecological and taxonomic contexts.
• Target selection for experiments: Guides selection of subfamily representatives for structural and biochemical structure–function investigations in glycogenomics research.

Methodology:

Employs a highly scalable workflow that constructs and analyzes sequence similarity networks, applies hidden Markov models and maximum likelihood molecular phylogenetic analyses, and evaluates experimental three-dimensional structures.