AlloSigMA

AlloSigMA quantifies residue-level allosteric signaling and predicts the effects of ligand binding and mutations on protein activity using a structure-based statistical mechanical model.

Key Features:

• Allosteric effects analysis: Quantifies allosteric impacts of mutations and ligand binding and identifies potential cancer drivers and pathogenic non-synonymous single nucleotide polymorphisms (nsSNPs) at residue resolution.
• Latent allosteric site detection: Detects latent allosteric sites within protein structures that may act as regulatory or druggable regions.
• Computational design of allosteric effectors: Supports design and evaluation of allosteric effectors with specified agonist or antagonist activities.
• Structure-Based Statistical Mechanical Model (SBSMMA): Implements SBSMMA to evaluate allosteric free-energy changes resulting from perturbations at per-residue resolution.
• Allosteric Signaling Map (ASM): Produces residue-by-residue maps of allosteric control over protein activity.
• Allosteric Probing Map (APM): Performs fragment-based-like computational probing to identify lead compounds for potential allosteric effectors.

Scientific Applications:

• Elucidation of allosteric mechanisms: Provides quantitative residue-level insight into how ligand binding and mutations alter protein function.
• Identification of disease drivers: Highlights mutations and nsSNPs with significant allosteric effects that may act as cancer drivers or pathogenic variants.
• Drug design and discovery: Enables identification and computational evaluation of allosteric modulators and lead fragments for therapeutic development.

Methodology:

Uses the Structure-Based Statistical Mechanical Model (SBSMMA) to compute per-residue allosteric free-energy changes from ligand- and mutation-induced perturbations, generates Allosteric Signaling Maps (ASM) for residue-by-residue control, and applies Allosteric Probing Maps (APM) as fragment-based-like computational experiments to identify lead compounds.