PRIMoRDiA

PRIMoRDiA computes CDFT-based global and local reactivity and electrostatic descriptors from post-electronic-structure outputs of quantum mechanics packages for large biomolecules.

Key Features:

• Conceptual DFT (CDFT): Implements Conceptual Density Functional Theory to compute response-based reactivity descriptors.
• Global and local reactivity: Generates both global and local descriptors to evaluate molecular reactivity within biomolecular systems.
• Electrostatic properties: Calculates electrostatic properties alongside CDFT-derived descriptors.
• Post-electronic-structure processing: Processes molecular information extracted from outputs of popular quantum mechanics packages.
• Theoretical reactivity from resolved electronic structures: Derives theoretical reactivity descriptors from resolved electronic structures.
• Large-biomolecule focus: Targets post-electronic-structure calculations specifically for large biomolecules.
• Implementation and performance: Implemented in C++ and uses shared-memory parallel processing to handle extensive quantum-chemistry output files.

Scientific Applications:

• Enzymatic catalysis analysis: Elucidates mechanisms of catalysis in enzymes, including systems lacking structural data.
• Enzymatic system studies: Applied to enzymatic systems to analyze reactivity and catalytic mechanisms.
• SARS-CoV-2 main protease interactions: Aided depiction of interactions between the SARS-CoV-2 main protease and a potential inhibitor.
• Large-scale biomolecular studies: Supports large-scale studies of biomolecular interactions relevant to virology and related drug-discovery research.

Methodology:

Processes molecular information from outputs of quantum mechanics packages, applies Conceptual Density Functional Theory (CDFT) and computes electrostatic properties and theoretical reactivity descriptors from resolved electronic structures; implemented in C++ with shared-memory parallel processing to handle extensive post-electronic-structure output files for large biomolecules.