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Computational optimization of DEK1 calpain domain solubility through integrated structural modelling and targeted mutagenesis

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Dabiri, Mohammad, Levarski, Zdenko, Struharnanska, Eva, Demko, Viktor, Benes, Vladimir, Turna, Jan, Stuchlík, Stanislav·2025·Scientific Reports
DOI 10.21203/rs.3.rs-7559073/v1PMC PMC12948991

Preprint — published as 10.1038/s41598-026-38805-z · Paper page

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Abstract

The DEFECTIVE KERNEL 1 (DEK1) protein plays essential functions throughout plant development. DEK1 is a multidomain 250 kDa protein with yet unsolved 3D structure. To facilitate structural and functional studies of DEK1, here we investigate its calpain protease core domain (CysPc) from Physcomitrium patens . Using integrated structural modelling we propose targeted mutagenesis of CysPc to enhance its solubility during recombinant protein production. We created a pipeline to predict the topology of the CysPc domain with improved precision, providing a robust framework for further exploration. We evaluated the native and mutant structures by MD simulations, concentrating on several solubility-related parameters. Following these features, we implemented specific single, double, and triple amino acid mutagenesis to select variants with improved solubility. Our method preserves overall structural integrity while reducing aggregation-prone traits. We advocate for the utilization of reinforcement learning method that can effectively traverse the extensive combinatorial space and prioritize mutation sets with the greatest potential for enhancing solubility. This framework provides a logical, data-driven approach to improving protein solubility, particularly beneficial in situations lacking high-resolution structural data.

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Figures

Fig. 1 Process related to the finding best reference sequence and integrated homology modelling of CysPc domain and library preparation.
Fig. 1 Process related to the finding best reference sequence and integrated homology modelling of CysPc domain and library preparation.CC BY-NC-ND · PubMed Central
Fig. 2 (A) consensus-based integrated modelling approach. (B) single-model prediction. These analyses highlight the improved stereochemical quality and model confidence achieved with the consensus-based approach.
Fig. 2 (A) consensus-based integrated modelling approach. (B) single-model prediction. These analyses highlight the improved stereochemical quality and model confidence achieved with the consensus-based approach.CC BY-NC-ND · PubMed Central
Fig. 3 Workflow for multi-point mutation protein optimization using MD features and iterative training. This diagram illustrates a stepwise approach for optimizing protein solubility (or other properties) via single, double, and triple mutants, guided by MD simulation features and iterative learning.
Fig. 3 Workflow for multi-point mutation protein optimization using MD features and iterative training. This diagram illustrates a stepwise approach for optimizing protein solubility (or other properties) via single, double, and triple mutants, guided by MD simulation features and iterative learning.CC BY-NC-ND · PubMed Central
Fig. 4 (A) MD simulation RMSF plot per residue for the wild-type (green) and mutant (red) proteins. Most residues show comparable fluctuation patterns in both profiles, indicating local flexibility. Both variants have slightly greater RMSF values at the C-terminal region, with the wild-type showing slightly more flexibility. Some loop areas of the mutated protein have much less variation, which suggests that changes to the surface made the protein more stable in those areas. (B) RMSD of backbone atoms over time (ns) for proteins that are normally formed (green) and proteins that have been changed (red). The RMSD of the changed structure stays lower than that of the wild-type structure after it is stabilized quickly. The smaller RMSD of the changed protein supports the idea that certain surface changes make structures more compact and less likely to change. (C) Rg analysis between natural-type and mutated structures reveals better compactness and integrity all over trajectory.
Fig. 4 (A) MD simulation RMSF plot per residue for the wild-type (green) and mutant (red) proteins. Most residues show comparable fluctuation patterns in both profiles, indicating local flexibility. Both variants have slightly greater RMSF values at the C-terminal region, with the wild-type showing slightly more flexibility. Some loop areas of the mutated protein have much less variation, which suggests that changes to the surface made the protein more stable in those areas. (B) RMSD of backbone atoms over time (ns) for proteins that are normally formed (green) and proteins that have been changed (red). The RMSD of the changed structure stays lower than that of the wild-type structure after it is stabilized quickly. The smaller RMSD of the changed protein supports the idea that certain surface changes make structures more compact and less likely to change. (C) Rg analysis between natural-type and mutated structures reveals better compactness and integrity all over trajectory.CC BY-NC-ND · PubMed Central
Fig. 5 Comparison of the global folded structures and secondary structures of the native protein and the triple-mutant variant. (A) Structure alignment of natural type (green) and triple-mutated (red) type and superimposed structure (middle) of CysPc domain with RMSD of 1.174 Å. (B) mdmat analyses of wild-type and MUT347 in residue-residue level. (C) Time resolved DSSP secondary structures of natural and triple-mutated type in 200 ns time-laps. (D) Quantitative analysis of secondary structure composition over blocks of 50 ps; block averaging with SE ± 0.05. Colour coded as follows: coil (white), β-sheet (red), β-bridge (black), bend (green), turn (yellow), α-helix (blue) 310-helix (dark gray), chain separator (light gray); Natural type (patterned bars), mutated type (solid bars).
Fig. 5 Comparison of the global folded structures and secondary structures of the native protein and the triple-mutant variant. (A) Structure alignment of natural type (green) and triple-mutated (red) type and superimposed structure (middle) of CysPc domain with RMSD of 1.174 Å. (B) mdmat analyses of wild-type and MUT347 in residue-residue level. (C) Time resolved DSSP secondary structures of natural and triple-mutated type in 200 ns time-laps. (D) Quantitative analysis of secondary structure composition over blocks of 50 ps; block averaging with SE ± 0.05. Colour coded as follows: coil (white), β-sheet (red), β-bridge (black), bend (green), turn (yellow), α-helix (blue) 310-helix (dark gray), chain separator (light gray); Natural type (patterned bars), mutated type (solid bars).CC BY-NC-ND · PubMed Central
Fig. 6 Structural comparison and surface study relates to solubility of the wild-type and mutant protein. (A) Surface and water molecules distribution representations illustrate mutation-induced structural alterations (represent in yellow), with the mutant variant displaying enhanced intra-molecular hydrogen bonding, as assessed in the accompanying bar chart. (B) SASA mapping by residue and area indicates that the mutant has a higher static surface exposure (21108 Ų) than the wild-type (17821 Ų). Dynamic SASA analysis, however, reveals that the mutant sustains a slightly more compact conformation but better stability in finals steps. Free energy surface (FES) calculated using RMSD-SASA as reaction coordinates for wild-type and mutant 347.
Fig. 6 Structural comparison and surface study relates to solubility of the wild-type and mutant protein. (A) Surface and water molecules distribution representations illustrate mutation-induced structural alterations (represent in yellow), with the mutant variant displaying enhanced intra-molecular hydrogen bonding, as assessed in the accompanying bar chart. (B) SASA mapping by residue and area indicates that the mutant has a higher static surface exposure (21108 Ų) than the wild-type (17821 Ų). Dynamic SASA analysis, however, reveals that the mutant sustains a slightly more compact conformation but better stability in finals steps. Free energy surface (FES) calculated using RMSD-SASA as reaction coordinates for wild-type and mutant 347.CC BY-NC-ND · PubMed Central
Fig. 7 Effect of pH and ionic strength on backbone flexibility of the wild-type protein and the mutant variant. (A) pH series. Per-residue Cα RMSF profiles for wild-type (left) and mutant (right) across four pH conditions spanning acidic to basic. Line colours follow the top colour bar (blue to red = low high pH). Residue index is on the x-axis; RMSF (Å) is on the y-axis. (B) NaCl series. RMSF profiles at increasing NaCl concentrations (0.2–1.2 M). Line colours map to the middle colour bar (black to green = low to high salt). Both variants show broadly similar shapes, with only modest salt-dependent dampening of fluctuations in solvent-exposed regions. C: (NH4)2SO4 series. RMSF profiles at increasing (NH4)2SO4 concentrations (0.2–1.2 M). Colores follow the bottom colour bar (black to green).
Fig. 7 Effect of pH and ionic strength on backbone flexibility of the wild-type protein and the mutant variant. (A) pH series. Per-residue Cα RMSF profiles for wild-type (left) and mutant (right) across four pH conditions spanning acidic to basic. Line colours follow the top colour bar (blue to red = low high pH). Residue index is on the x-axis; RMSF (Å) is on the y-axis. (B) NaCl series. RMSF profiles at increasing NaCl concentrations (0.2–1.2 M). Line colours map to the middle colour bar (black to green = low to high salt). Both variants show broadly similar shapes, with only modest salt-dependent dampening of fluctuations in solvent-exposed regions. C: (NH4)2SO4 series. RMSF profiles at increasing (NH4)2SO4 concentrations (0.2–1.2 M). Colores follow the bottom colour bar (black to green).CC BY-NC-ND · PubMed Central

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Metadata

Authors
Dabiri, M., Levarski, Z., Struharnanska, E., Demko, V., Benes, V., Turna, J., & Stuchlík, S.
Affiliations
  • Comenius University Bratislava (SK)
  • Comenius University in Bratislava
  • Slovak Academy of Sciences (SK)
  • European Molecular Biology Laboratory (DE)
Corresponding author
  • Dabiri, Mohammad
  • Levarski, Zdenko
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2025-10-03
Volume
16
Issue
1
ISSN
2045-2322 (ISSN-L)
DOI
10.21203/rs.3.rs-7559073/v1
PMC
PMC12948991
OpenAlex
W7128355779
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0
References
1
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0.00
Type
journal article
Language
en
Open access
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  • Scientific Reports (publishedVersion, cc-by-nc-nd)
  • Research Square (acceptedVersion, cc-by)
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  • PubMed Central (publishedVersion, cc-by-nc-nd)
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Funders
  • Univerzita Komenského v Bratislave
  • Agentúra na Podporu Výskumu a Vývoja (APVV-22-0161, APVV-21-0227, APVV-22-, APVV-21-, APVV-21-0215)
  • HORIZON EUROPE Framework Programme
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein purification and stability
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
Keywords
protein solubility, targeted mutagenesis, protein aggregation, Physcomitrella patens, protein topology prediction, molecular dynamics simulation, recombinant protein expression, protein structure prediction, computational protein design
MeSH terms
Protein Domains, Calpain, Models, Molecular, Mutation, Plant Proteins, Solubility, Mutagenesis, Bryopsida, Molecular Dynamics Simulation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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