Quality Evaluation Based Simulation Selection (QEBSS) for analysis of conformational ensembles and dynamics of multidomain proteins

Abstract

Multidomain proteins containing both folded and intrinsically disordered regions are crucial for biological processes, but characterizing their conformational ensembles and dynamics remains challenging. We introduce the Quality Evaluation Based Simulation Selection (QEBSS) protocol, which combines MD simulations with NMR-derived protein backbone ¹⁵N T₁ and T₂ spin relaxation times and hetNOE values to interpret conformational ensembles and dynamics of multidomain proteins. We demonstrate the practical advantage of QEBSS by characterizing four flexible multidomain proteins: calmodulin, EN2, MANF, and CDNF. These biologically important proteins have been difficult to study due to their flexible nature. Our findings reveal new insights into their conformational landscapes and dynamics, providing mechanistic understanding of their biological functions. QEBSS offers quantitative quality evaluation of simulations and a systematic approach for resolving conformational ensembles of multidomain proteins with heterogeneous dynamics. Given the importance of such proteins in biology, biotechnology, and materials science, QEBSS should benefit fields from drug design to novel materials development.

Fig. 1. General characterization of simulations.

Average radius of gyration (nm) for each force field calculated from five replicas (left). Representative snapshots showing 50 overlaid structures per force field, with 10 equally spaced structures taken from each of the five replicas. For structural alignment, the entire protein was used for TonBCTD, while the N-terminal folded domains were used for calmodulin, CDNF, and MANF, and the C-terminal domain for EN2. Domain organization, sequence, and residue numbering of each protein are shown to illustrate the different domains of the multidomain proteins (right).

Fig. 2. Comparison of spin relaxation times predicted by different force fields with experiments.

Backbone ¹⁵N spin relaxation times, T₁ and T₂, and hetNOE values calculated from averages over replicas from MD simulations with different force fields compared to experimental spin relaxation data for TonBCTD, calmodulin, CDNF, MANF, and EN2. Average difference over all residues between calculated ¹⁵N spin relaxation times, T₁ and T₂, and hetNOE values from simulations and experimental values. Experimental errors are displayed with gray error bars if reported.

Fig. 3. Comparison of spin relaxation times between QEBSS ensemble and experiments.

¹⁵N spin relaxation times, T₁ and T₂, and hetNOE values calculated from averaged correlation functions from the total QEBSS ensemble resulting from the QEBSS protocol for different proteins. Experimental errors are displayed with gray error bars if reported.

Fig. 4. Characterization of overall shapes and timescale distributions of QEBSS ensembles.

Radius of gyration (R_g in nm) distributions (left), snapshots displaying 10 overlayed structures (middle), and timescales (right) from QEBSS ensembles for different proteins. Dashed vertical lines show the average R_g and the experimental value for calmodulin is marked with a black dashed line. For the snapshots, structural alignment of the entire protein was used for TonBCTD, while the N-terminal folded domains were used for calmodulin, CDNF, and MANF, and the C-terminal domain for EN2. The point sizes represent the weight of each timescale in the rotational relaxation process.

Fig. 5. Characterization of backbone correlations, contacts, and overall dynamics of QEBSS ensembles.

Protein backbone orientation correlation maps for vectors between C^α carbons of consecutive residues (left), average minimum distance between residues maps (middle), and effective correlation times calculated from QEBSS ensemble for different proteins (right).