LSP-MD: A Fast Computational Method to Study Allostery Driven by Thermal Vibrations

Conformational entropy associated with thermal vibrations plays fundamental roles in protein function, from ligand binding and catalysis to allosteric regulation. Cooper and Dryden first proposed entropy-driven allostery as an example of these effects. However, measuring the underlying thermal motions remains technically challenging. Here, we introduce LSP-MD, a computational method that builds on the Local Spatial Pattern (LSP) alignment to track side-chain stability in molecular dynamics (MD) simulations. LSP-MD uses graph-based Protein Residue Networks (PRNs) with edge weights derived from fast, local geometric fluctuations. Applied to protein kinase A (PKA), the method captures picosecond-time scale vibrations with amplitudes in the 0-2 Å range and frequencies below 100 cm^-1─within the range implicated in entropy-mediated signaling. Centrality measures derived from LSP-MD networks remain stable across different simulation lengths, vector definitions, and force fields, confirming robustness. Importantly, LSP-MD reproduces key findings from traditional LSP analysis, while offering a clearer physical basis and greater computational efficiency. This method opens new opportunities for exploring entropy-driven allosteric behavior in diverse macromolecular systems.