Multiply Perturbed Response: A Computational Protocol to Identify Cooperative Allosteric Residue Combinations Driving...

Protein function often depends on dynamic conformational transitions driven by external factors or molecular interactions. Understanding the allosteric mechanisms underlying these transitions is essential for mechanistic insight into protein function. Molecular dynamics (MD) simulations are widely used to study protein dynamics; however, capturing large-scale, rare transitions is computationally expensive. To address this, we previously developed Perturbation Response Scanning (PRS), based on elastic network models and linear response theory, but PRS is limited in capturing collective effects because it perturbs one residue at a time. Here, we present Multiply Perturbed Response (MPR), which extends PRS by applying simultaneous perturbations to multiple residues to identify allosteric residue combinations that drive conformational transitions. This protocol provides a workflow for structure preparation, displacement, and covariance-matrix calculations, overlap analysis, and visualization. It can be applied to static structures or trajectories from MD simulations, requiring initial and final protein structures as the main inputs and an optional MD trajectory for trajectory-based analysis. The main outputs are residue combinations that maximize overlap, O _max values, corresponding force vectors, and visualization files. These outputs help identify cooperative allosteric regions and residues for mechanistic interpretation or further experimental validation. By perturbing multiple residues simultaneously, MPR captures conformational transitions arising from combined residue effects. The method is easy to use, reproducible, and accessible through open-source tools and libraries. Key features • Facilitates the identification of multiple allosteric hotspot residues using optimized multi-residue perturbations. • Extends classical perturbation-response scanning to account for the coordinated effects of multiple simultaneous perturbations. • Enables structure-based and trajectory-based analyses within a single framework, using static structural information or MD-derived covariance information. • Provides interpretable outputs, including ranked residue combinations, overlap values, optimized force vectors, and ChimeraX-compatible visualization files.