SINAPs

SINAPs analyzes interaction networks derived from molecular dynamics simulations and crystallographic structures to identify key interactions that distinguish alternative protein bioactive states.

Key Features:

• Interaction Network Analysis: Identifies key interactions that differentiate two protein states from molecular dynamics simulations or crystallographic structures.
• Input Data Support: Operates on interaction networks derived from molecular dynamics simulations and crystallographic structures.
• 3D Visualization (UCSF Chimera): Renders identified interactions in three-dimensional molecular representations via integration with UCSF Chimera through a plugin.
• Implementation: Implemented in Python.

Scientific Applications:

• GLUT-1: Applied to glucose transporter-1 (GLUT-1) to pinpoint experimentally observed interactions critical for bioactivity.
• A2A adenosine receptor (A2AR): Applied to A2AR to identify interactions associated with distinct bioactive states.
• P28 glutathione-S-transferase (P28GST): Used to elucidate amino acids involved in enzymatic mechanisms governing activation of an immunomodulatory drug candidate, P28GST.

Methodology:

Analysis of interaction networks derived from molecular dynamics simulations or crystallographic structures, systematic identification of interactions that distinguish protein states, and rendering of those interactions via UCSF Chimera integration.