Conformational Rigidity Classification in Intrinsically Disordered Proteins via Integrated NMR and MD Simulations

Intrinsically disordered proteins (IDPs) challenge the structure-function paradigm, yet comprehensive frameworks for characterizing their conformational diversity remain limited. Here, we present a novel approach for classifying IDPs based on backbone rigidity and intramolecular contacts through our automated Quality Evaluation Based Simulation Selection (QEBSS) protocol. This method selects experimentally consistent molecular dynamics ensembles by evaluating simulated NMR spin relaxation data against experimental measurements. Application to four functionally diverse IDPs—ChiZ1-64, KRS1-72, Alpha-synuclein, and ICL2—reveals a progressive increase in backbone rigidity and contact formation, extending beyond the conventional random coil model. ChiZ1-64 approximates a random coil with a persistence length of 0.76 nm, while KRS1-72 exhibits electrostatic-driven hairpin-like conformations. Alpha-Synuclein displays complex intrachain interactions that may regulate its aggregation propensity, and ICL2 adopts relatively ordered structures despite its classification as an IDP. Cross-validation with SAXS and PRE data confirms that QEBSS- selected ensembles capture relevant conformational features. Notably, we demonstrate that force field selection exerts stronger influence on conformational predictions than sequence variations, underscoring the necessity of experimental validation. This rigidity based classification approach provides deeper insight into sequence-dependent IDP properties and creates a foundation for developing improved computational models with implications for both fundamental biochemistry and biotechnological applications.