RocaSec

RocaSec infers co-evolutionary sectors from protein multiple sequence alignments (MSAs) to characterize mutational correlations and relate them to biochemical domains.

Key Features:

• RoCA-based inference: Implements the Robust Co-Evolutionary Analysis (RoCA) statistical inference method to identify co-evolutionary sectors.
• Input format: Operates on protein multiple sequence alignments (MSAs) as the primary input for analysis.
• Sector prediction: Identifies co-evolutionary sectors that reflect mutational correlations and functional or structural constraints.
• Domain association: Computes statistical associations between inferred sectors and biochemical domains when domain annotations are provided.
• Error control: Incorporates procedures to control statistical errors arising from limited data in the inference.

Scientific Applications:

• Protein evolution: Identifying mutational correlations that reveal evolutionary pressures on proteins.
• Structure–function relationships: Mapping co-evolutionary sectors to functional or structural elements to infer structure–function links.
• Biochemical domain validation: Correlating inferred sectors with biochemical domains to validate or refine domain annotations and functional hypotheses.
• Protein function and interactions: Providing insights into protein functionality, interactions, and stability through sector-based constraints.

Methodology:

RocaSec applies the Robust Co-Evolutionary Analysis (RoCA) statistical inference method to analyze patterns of mutational correlations in protein MSAs, infer co-evolutionary sectors, compute statistical associations between inferred sectors and biochemical domains, and control for statistical errors due to limited data.