A molecular dynamic modeling and in silico analysis approach to three-dimensional structure of glutelin type-B 5-like proteins from proso millet: effects of temperature and electric field

Abstract

Aim: Protein structure-function relationship understanding is very important to the study of protein chemistry. In this study, we determined the 3D structure of glutelin type-B 5-like (GTB) protein from proso millet and investigated the effects of simulated temperature and static electric field on GTB protein’s secondary structures, solvent accessibility surface area (SASA), the radius of gyration (Rg), root mean square deviation (RMSD), and total dipole moment with the view to elucidate its structural behavior under different simulated processing stresses. Methods: This study leveraged homology modeling to determine the 3D structure of the GTB protein from proso millet. We further explored in silico modeling using molecular dynamic modeling tools to study the behavior of the GTB protein structure under simulated temperatures and static electric field processing stresses. Results: The 3D protein structure of GTB is majorly a protomer that comprises three monomers with one jelly-like β-barrel and two extended helix domains, and the remaining 35% as coils. From the molecular dynamic simulation, the secondary structure of the protein was not disrupted at temperatures between 300–400 K and static electric fields between 0.1–3 V/nm, albeit with the loss of a few amino acid residues. The RMSD increased significantly with temperature, static electric field, and simulation time increase. However, the Rg and SASA decreased for the same conditions, suggesting that the protein structure is compacting during thermal and electrical treatment. Conclusions: We concluded that low levels of simulated temperature and low levels of the electric field may cause a temporary reversible conformational change of GTB protein, not enough to cause a major disruption as may be expected during empirical processing of protein. To achieve greater disruption that would mimic protein denaturation, there is a need for in silico study of protein molecules under more aggressive simulated stressors for a longer time, and consideration given to protein structure development from AlphaFold3.

Keywords

Comparative homology modeling / molecular dynamic modeling / proso millet / glutelin proteins / structure-function relationship / three-dimensional structure

References

[1] Singh A, Orsat V, Raghavan V. Soybean Hydrophobic Protein Response to External Electric Field: A Molecular Modeling Approach. Biomolecules. 2013; 3: 168-79.

[2] Tandang—Silvas MR, Cabanos CS, Carrazco Peña LD, De la Rosa AP, Osuna—Castro JA, Utsumi S, et al. Crystal structure of a major seed storage protein, 11S proglobulin, from Amaranthus hypochondriacus: Insight into its physico—chemical properties . Food Chem. 2012; 135: 819-26.

[3] Pantoja—Uceda D, Shewry PR, Bruix M, Tatham AS, Santoro J, Rico M. Solution Structure of a Methionine—Rich 2S Albumin from Sunflower Seeds: Relationship to Its Allergenic and Emulsifying Properties. Biochemistry. 2004; 43: 6976-86.

[4] Fukuda T, Maruyama N, Salleh MRM, Mikami B, Utsumi S. Characterization and Crystallography of Recombinant 7S Globulins of Adzuki Bean and Structure−Function Relationships with 7S Globulins of Various Crops. J Agric Food Chem. 2008; 56: 4145-53.

[5] Vagadia BH, Vanga SK, Singh A, Raghavan V. Effects of thermal and electric fields on soybean trypsin inhibitor protein: A molecular modelling study. Innov Food Sci Emerg Technol. 2016; 35: 9-20.

[6] Marracino P, Apollonio F, Liberti M, d’Inzeo G, Amadei A. Effect of High Exogenous Electric Pulses on Protein Conformation: Myoglobin as a Case Study. J Phys Chem B. 2013; 117: 2273—9.

[7] Wang X, Li Y, He X, Chen S, Zhang JZH. Effect of Strong Electric Field on the Conformational Integrity of Insulin. J Phys Chem A. 2014; 118: 8942—52.

[8] Akharume F, Santra D, Adedeji A. Physicochemical and functional properties of proso millet storage protein fractions. Food Hydrocolloid. 2019; 108: 105497.

[9] Wouters AGB, Delcour JA. Cereal protein—based nanoparticles as agents stabilizing air—water and oil—water interfaces in food systems. Curr Opin Food Sci. 2019; 25: 19-27.

[10] Akharume FU, Korotkov KK, Adedeji AA. Characterization of Recombinant Glutelin type—B 5—like Protein from Proso Millet. 2020 ASABE Annual International Virtual Meeting; 2020 July 13—15. Michigan: American Society of Agricultural and Biological Engineers; 2020. pp. 2000272.

[11] Akharume F, Adedeji A. Molecular dynamic (in silico) modeling of structure—function of glutelin type—B 5—like from proso millet storage protein: effects of temperature and pressure . J Food Sci Technol. 2023; 60: 114-22.

[12] Kuroda Y, Suenaga A, Sato Y, Kosuda S, Taiji M. All—atom molecular dynamics analysis of multi—peptide systems reproduces peptide solubility in line with experimental observations. Sci Rep. 2016; 6: 19479.

[13] Shi J, Ma X, Zhang J, Zhou Y, Liu M, Huang L, et al. Chromosome conformation capture resolved near complete genome assembly of broomcorn millet. Nat Commun. 2019; 10: 464.

[14] Waterhouse A, Bertoni M, Bienert S, Studer G, Tauriello G, Gumienny R, et al. SWISS—MODEL: homology modelling of protein structures and complexes. Nucleic Acids Res. 2018; 46: W296-303.

[15] Guex N, Peitsch MC, Schwede T. Automated comparative protein structure modeling with SWISS—MODEL and Swiss—PdbViewer: A historical perspective. Electrophoresis. 2009; 30: S162-73.

[16] Song Y, DiMaio F, Wang RY, Kim D, Miles C, Brunette T, et al. High—Resolution Comparative Modeling with RosettaCM. Structure. 2013; 21: 1735-42.

[17] Kim DE, Chivian D, Baker D. Protein structure prediction and analysis using the Robetta server. Nucleic Acids Res. 2004; 32: W526—31.

[18] Ko J, Park H, Heo L, Seok C. GalaxyWEB server for protein structure prediction and refinement. Nucleic Acids Res. 2012; 40: W294—7.

[19] Shin WH, Lee GR, Heo L, Lee H, Seok C. Prediction of Protein Structure and Interaction by GALAXY Protein Modeling Programs. Bio Design. 2014; 2: 1-11. Korean.

[20] Li Z, Natarajan P, Ye Y, Hrabe T, Godzik A. POSA: a user—driven, interactive multiple protein structure alignment server. Nucleic Acids Res. 2014; 42: W240-5.

[21] Liebschner D, Afonine PV, Baker ML, Bunkóczi G, Chen VB, Croll TI, et al. Macromolecular structure determination using X—rays, neutrons and electrons: recent developments in Phenix . Acta Crystallogr D Struct Biol. 2019; 75: 861—77.

[22] Laskowski RA, MacArthur MW, Moss DS, Thornton JM. Procheck: a program to check the stereochemical quality of protein structures . J Appl Crystallogry. 1993; 26: 283—91.

[23] Wiederstein M, Sippl MJ. ProSA—web: interactive web service for the recognition of errors in three—dimensional structures of proteins. Nucleic Acids Res. 2007; 35: W407—10.

[24] Sippl MJ. Recognition of errors in three—dimensional structures of proteins. Proteins. 1993; 17: 355-62.

[25] Studer G, Rempfer C, Waterhouse AM, Gumienny R, Haas J, Schwede T. QMEANDisCo—distance constraints applied on model quality estimation. Bioinformatics. 2020; 36: 1765—71.

[26] Van Der Spoel D, Lindahl E, Hess B, Groenhof G, Mark AE, Berendsen HJC. GROMACS: Fast, flexible, and free. J Comput Chem. 2005; 26: 1701—18.

[27] Robertson MJ, Tirado—Rives J, Jorgensen WL. Improved Peptide and Protein Torsional Energetics with the OPLS—AA Force Field. J Chem Theory Comput. 2015; 11: 3499-509.

[28] Kusalik PG, Svishchev IM. The Spatial Structure in Liquid Water. Science. 1994; 265: 1219—21.

[29] Parrinello M, Rahman A. Crystal Structure and Pair Potentials: A Molecular—Dynamics Study. Phys Rev Lett. 1980; 45: 1196.

[30] Berendsen HJC, Postma JPM, van Gunsteren WF, DiNola A, Haak JR. Molecular dynamics with coupling to an external bath. J Chem Phys. 1984; 81: 3684—90.

[31] Touw WG, Baakman C, Black J, te Beek TA, Krieger E, Joosten RP, et al. A series of PDB—related databanks for everyday needs. Nucleic Acids Res. 2015; 43: D364—8.

[32] Kabsch W, Sander C. Dictionary of protein secondary structure: Pattern recognition of hydrogen—bonded and geometrical features. Biopolymers. 1983; 22: 2577-637.

[33] Humphrey W, Dalke A, Schulten K. VMD: Visual molecular dynamics. J Mol Graph. 1996; 14: 33-8.

[34] Tandang—Silvas MRG, Fukuda T, Fukuda C, Prak K, Cabanos C, Kimura A, et al. Conservation and divergence on plant seed 11S globulins based on crystal structures. Biochim Biophys Acta. 2010; 1804: 1432—42.

[35] Adachi M, Takenaka Y, Gidamis AB, Mikami B, Utsumi S. Crystal Structure of Soybean Proglycinin A1aB1b Homotrimer. J Mol Biol. 2001; 305: 291-305.

[36] Benkert P, Biasini M, Schwede T. Toward the estimation of the absolute quality of individual protein structure models. Bioinformatics. 2011; 27: 343—50.

[37] Conway P, Tyka MD, DiMaio F, Konerding DE, Baker D. Relaxation of backbone bond geometry improves protein energy landscape modeling. Protein Sci. 2014; 23: 47-55.

[38] Vanga SK, Singh A, Raghavan V. Effect of thermal and electric field treatment on the conformation of Ara h 6 peanut protein allergen. Innov Food Sci Emerg. 2015; 30: 79-88.

[39] Li Y, Zhang C, Liang Y, Wang L, Xiong W. Solubility and conformational characterization of rice glutelin after high temperature treatment. Int J Biol Macromol. 2022; 223: 1720—6.

[40] Heinig M, Frishman D. STRIDE: a web server for secondary structure assignment from known atomic coordinates of proteins. Nucleic Acids Res. 2004; 32: W500-2.

[41] Fenwick S, Vanga SK, DiNardo A, Wang J, Raghavan V, Singh A. Computational evaluation of the effect of processing on the trypsin and alpha—amylase inhibitor from Ragi (Eleusine coracana) seed . Eng Rep. 2019; 1: e12064.

[42] Gulati P, Li A, Holding D, Santra D, Zhang Y, Rose DJ. Heating Reduces Proso Millet Protein Digestibility via Formation of Hydrophobic Aggregates. J Agric Food Chem. 2017; 65: 1952—9.

[43] Chao D, Aluko RE. Modification of the structural, emulsifying, and foaming properties of an isolated pea protein by thermal pretreatment. J Food Sci. 2018; 6: 357-66.

[44] Nakai S. Structure—function relationships of food proteins: with an emphasis on the importance of protein hydrophobicity. J Agric Food Chem. 1983; 31: 676—83.

[45] Gromiha MM, Nagarajan R, Selvaraj S. Protein Structural Bioinformatics: An Overview. Encyclopedia Bioinform Comput Biol. 2019; 2: 445-9.