Engineering and Applied Sciences Journal

DynaMune: An Integrated Ensemble-Based Framework for Comparative Protein Dynamics Using Elastic Network Models

Abstract

Amirtesh Raghuram

Normal mode analysis (NMA) and elastic network models (ENMs) provide a rapid and efficient route to probe collective protein motions, but existing tools are fragmented, require heterogeneous parameter choices, and lack a unified framework for ensemble generation, apo–complex comparison, and interface persistence analysis. Here, DynaMune is introduced as an integrated, parameter-aware platform that standardizes ENM/NMA-based dynamics within a reproducible, ensemble-driven workflow. Built on ProDy as its computational backbone, DynaMune automates normal mode and principal component analysis, Gaussian and anisotropic network modeling, perturbation response scanning, domain and hinge decomposition, pocket accessibility profiling, conformational deformation mapping, and systematic quantification of interface contact stability and persistence. An optional immuno informatics extension supports early-stage epitope selection and multi-epitope construct evaluation using dynamicsinformed ensemble modeling. The tool was benchmarked on two mechanistically distinct systems: adenylate kinase (ADK), a canonical model of large-scale conformational transitions, and the ACE2–SARS-CoV-2 Spike complex, a structurally constrained protein–protein interface. DynaMune recovered the canonical CORE–LID–NMP transitions, hinge sites, and cracking behavior of ADK, and reproduced the ACE2–Spike interaction hotspot, multimode deformation mechanism, and persistent interfacial contact network reported in crystallographic, cryo-EM, and molecular dynamics studies. These results show that DynaMune reliably captures both intra-protein allostery and ligand-induced interface remodeling. The tool provides a unified, scalable framework for ENM/NMA-based structural dynamics, enabling routine mechanistic interpretation, consistent parameter usage, and publication-ready reporting without external simulations or specialized scripting expertise.

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