webPSN

webPSN analyzes structural communication and allosteric networks in proteins and nucleic acids by combining Protein Structure Network (PSN) analysis with Elastic Network Model-Normal Mode Analysis (ENM-NMA) to examine static and dynamic interactions and compare communication pathways across structural states.

Key Features:

• PSN-ENM integration: Implements a mixed strategy combining Protein Structure Network (PSN) analysis with Elastic Network Model-Normal Mode Analysis (ENM-NMA) to capture static and dynamic aspects of biomacromolecules.
• Protein Structure Graphs (PSGs): Computes PSGs on individual structures to provide static network representations of molecular architecture.
• ENM-NMA dynamic analysis: Incorporates ENM-NMA-derived dynamic information to assess how structural fluctuations influence communication pathways.
• Internal network-parameter database: Uses an updatable internal database of network parameters for ions and small molecules across Protein Data Bank (PDB) structures to contextualize network construction.
• Network comparison: Computes differences in nodes, links, and communication pathways between two structural states to identify state-specific changes.
• Consensus network analysis: Derives consensus networks from multiple structures and infers links, hubs, communities, and metapaths to identify recurrent structural-communication signatures.
• Support for proteins and nucleic acids: Applies analyses to both protein and nucleic acid macromolecules.
• Comparative studies of multiple structures: Enables analysis across large sets of biomacromolecular structures for comparative and evolutionary investigations.

Scientific Applications:

• Allosterism and allosteric regulation: Identification and characterization of allosteric communication pathways within proteins and nucleic acids.
• Structure-function analysis: Linking static and dynamic network features to conformational changes and biomolecular function.
• Comparative and evolutionary studies: Detecting conserved and divergent communication signatures across homologous systems or different functional states.

Methodology:

Computes Protein Structure Graphs (PSGs) on individual structures; integrates Elastic Network Model-Normal Mode Analysis (ENM-NMA) in a PSN-ENM mixed strategy to incorporate dynamics; employs an internal database of network parameters for ions and small molecules across PDB structures; computes differences in nodes, links, and communication pathways between two structural states; derives consensus networks from multiple structures and infers links, hubs, communities, and metapaths.