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Cited by 5Protein Structure and DynamicsAdvanced NMR Techniques and ApplicationsAdvanced Physical and Chemical Molecular Interactions

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

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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 15 N T 1 and T 2 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.

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Crossref · 10.1038/s42004-025-01623-x

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Figures

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 TonBCTD22, while the N-terminal folded domains were used for calmodulin60, CDNF28, and MANF44, and the C-terminal domain for EN245. Domain organization, sequence, and residue numbering of each protein are shown to illustrate the different domains of the multidomain proteins (right).
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 TonBCTD22, while the N-terminal folded domains were used for calmodulin60, CDNF28, and MANF44, and the C-terminal domain for EN245. Domain organization, sequence, and residue numbering of each protein are shown to illustrate the different domains of the multidomain proteins (right).CC BY · PubMed Central
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 TonBCTD43, calmodulin13, CDNF28, MANF44, and EN245. 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. 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 TonBCTD43, calmodulin13, CDNF28, MANF44, and EN245. 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.CC BY · PubMed Central
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. 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.CC BY · PubMed Central
Fig. 4 Characterization of overall shapes and timescale distributions of QEBSS ensembles. Radius of gyration (Rg 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 Rg and the experimental value for calmodulin48 is marked with a black dashed line. For the snapshots, structural alignment of the entire protein was used for TonBCTD22, while the N-terminal folded domains were used for calmodulin60, CDNF28, and MANF44, and the C-terminal domain for EN245. The point sizes represent the weight of each timescale in the rotational relaxation process.
Fig. 4 Characterization of overall shapes and timescale distributions of QEBSS ensembles. Radius of gyration (Rg 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 Rg and the experimental value for calmodulin48 is marked with a black dashed line. For the snapshots, structural alignment of the entire protein was used for TonBCTD22, while the N-terminal folded domains were used for calmodulin60, CDNF28, and MANF44, and the C-terminal domain for EN245. The point sizes represent the weight of each timescale in the rotational relaxation process.CC BY · PubMed Central
Fig. 5 Characterization of backbone correlations, contacts, and overall dynamics of QEBSS ensembles. Protein backbone orientation correlation maps for vectors between Cα carbons of consecutive residues (left), average minimum distance between residues maps (middle), and effective correlation times calculated from QEBSS ensemble for different proteins (right).
Fig. 5 Characterization of backbone correlations, contacts, and overall dynamics of QEBSS ensembles. Protein backbone orientation correlation maps for vectors between Cα carbons of consecutive residues (left), average minimum distance between residues maps (middle), and effective correlation times calculated from QEBSS ensemble for different proteins (right).CC BY · PubMed Central

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Metadata

Authors
Sandelin, A. E., Nencini, R., Yasar, E., Fudo, S., Stratoulias, V., Kajander, T., & Ollila, O. H. S.
Affiliations
University of Helsinki (FI)
Corresponding author
Ollila, O. H. Samuli
Venue
Communications Chemistry
Published
2025-08-10
Volume
8
Issue
1
Pages
241-241
ISSN
2399-3669 (ISSN-L)
OpenAlex
W4413094454
Cited by
5
References
73
Citations by year
2026: 3 · 2025: 1
FWCI
1.20
Type
journal article
Language
en
Open access
Licence
Locations
  • Communications Chemistry (publishedVersion, cc-by)
  • ChemRxiv (acceptedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Työväentutkimus Vuosikirja (submittedVersion)
Funders
Emil Aaltosen Säätiö
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Physical Sciences › Chemistry › Spectroscopy › Advanced NMR Techniques and Applications
  • Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Advanced Physical and Chemical Molecular Interactions
Keywords
multidomain proteins, intrinsically disordered regions, conformational ensembles, protein dynamics, calmodulin, EN2, MANF, CDNF, flexible proteins

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