Investigation of Solid Formation Enthalpy and Molecular Mechanics Energies of Amino Acids via Force Field Approach

Abstract

Accurate determination of the thermodynamic and molecular mechanical properties of amino acids will contribute to a better understanding of their folding mechanisms. In this study, the enthalpy values and molecular mechanics parameters of 17 amino acids were investigated by the classical molecular dynamics method. All calculations were performed using the force-field potential approach. As a result, the calculated solid formation enthalpy for ALA, ASN, ASP, CYS, LYS, and PHE are in good agreement with the experimental data. In addition, molecular mechanics parameters such as Coulomb, bond, angle, dihedral, and Van der Waals were calculated for all amino acids. It is seen that the Coulomb energy is quite low compared to the rest of the molecular mechanical energies. The molecular mechanical energies obtained from the study will contribute to protein-lipid modification studies for electronic interaction, ligand binding to the cell surface, and correct protein localization.

Keywords

• Solid formation enthalpy
• Molecular Mechanics Energies
• Amino Acids
• Molecular Dynamics Simulation

Supporting Institution

Management Unit of Scientific Research projects of Firat University (FÜBAP)

Project Number

FF.16.28

References

1. [1] M. AlQuraishi, “End-to-End Differentiable Learning of Protein Structure,” Cell Syst., vol. 8, no. 4, pp. 292-301.e3, 2019, doi: 10.1016/j.cels.2019.03.006.
2. [2] A. V. Yakubovich, Theory of Phase Transitions in Polypeptides and Proteins, no. July. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011.
3. [3] A. V. Finkelstein and O. V. Galzitskaya, “Physics of protein folding,” Phys. Life Rev., vol. 1, no. 1, pp. 23–56, 2004, doi: 10.1016/j.plrev.2004.03.001.
4. [4] S. A. Shirdel and K. Khalifeh, “Thermodynamics of protein folding: methodology, data analysis and interpretation of data,” Eur. Biophys. J., no. 0123456789, 2019, doi: 10.1007/s00249-019-01362-7.
5. [5] T. Schlick, Molecular Modeling and Simulation: An Interdisciplinary Guide (Interdisciplinary Applied Mathematics, Volume 21), 2nd Edition. 2010.
6. [6] P. Singh, D. Kumar, S. Pal, K. Kumari, and I. Bahadur, “L-amino-acids as immunity booster against COVID-19: DFT, molecular docking and MD simulations,” J. Mol. Struct., vol. 1250, p. 131924, 2022, doi: 10.1016/j.molstruc.2021.131924.
7. [7] M. Eisenstein, “Artificial intelligence powers protein-folding predictions,” Nature, vol. 599, no. 7886, pp. 706–708, 2021, doi: 10.1038/d41586-021-03499-y.
8. [8] J. O. Hutchens, A. G. Cole, and J. W. Stout, “Heat Capacities from 11 to 305° K, Entropies, Enthalpy, and Free Energy of Formation of l-Serine,” J. Biol. Chem., vol. 239, no. 12, pp. 4194–4195, Dec. 1964, doi: 10.1016/S0021-9258(18)91154-3.

9. [9] S. Nguon Ngauv, R. Sabbah, and M. Laffitie, “Thermodynamique de composes azotes III. Etude Thermochimique de la glycine et de la l-α-alanine,” Thermochim. Acta, vol. 20, no. 3, pp. 371–380, 1977, doi: 10.1016/0040-6031(77)85091-0.
10. [10] O. V. Dorofeeva and O. N. Ryzhova, “Revision of standard molar enthalpies of formation of glycine and l-alanine in the gaseous phase on the basis of theoretical calculations,” J. Chem. Thermodyn., vol. 41, no. 4, pp. 433–438, 2009, doi: 10.1016/j.jct.2008.12.001.
11. [11] V. Petrauskas, E. Maximowitsch, and D. Matulis, “Thermodynamics of Ion Pair Formations Between Charged Poly(Amino Acid)s,” J. Phys. Chem. B, vol. 119, no. 37, pp. 12164–12171, 2015, doi: 10.1021/acs.jpcb.5b05767.
12. [12] A. Hossain, S. Roy, and B. K. Dolui, “Effects of thermodynamics on the solvation of amino acids in the pure and binary mixtures of solutions: A review,” J. Mol. Liq., vol. 232, pp. 332–350, 2017, doi: 10.1016/j.molliq.2017.02.080.
13. [13] S. Pandit and M. De, “Interaction of amino acids and graphene oxide: Trends in thermodynamic properties,” J. Phys. Chem. C, vol. 121, no. 1, pp. 600–608, 2017, doi: 10.1021/acs.jpcc.6b11571.
14. [14] D. Gheorghe, A. Neacşu, I. Contineanu, S. Tănăsescu, and Ş. Perişanu, “A calorimetric study of l-, d- and dl-isomers of tryptophan,” J. Therm. Anal. Calorim., vol. 130, no. 2, pp. 1145–1152, 2017, doi: 10.1007/s10973-017-6396-z.
15. [15] O. V. Dorofeeva and O. N. Ryzhova, “Gas-phase enthalpies of formation and enthalpies of sublimation of amino acids based on isodesmic reaction calculations,” J. Phys. Chem. A, vol. 118, no. 19, pp. 3490–3502, 2014, doi: 10.1021/jp501357y.
16. [16] B. Nie, R. Li, Y. Wu, X. Yuan, and W. Zhang, “Theoretical Calculation of the Thermodynamic Properties of 20 Amino Acid Ionic Liquids,” J. Phys. Chem. B, vol. 122, no. 46, pp. 10548–10557, 2018, doi: 10.1021/acs.jpcb.8b06813.
17. [17] C. I. Bayly et al., “A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules,” J. Am. Chem. Soc., vol. 117, no. 19, pp. 5179–5197, 1995, doi: 10.1021/ja00124a002.
18. [18] K. Vanommeslaeghe, E. Prabhu Raman, and A. D. MacKerell, “Automation of the CHARMM General Force Field (CGenFF) II: Assignment of Bonded Parameters and Partial Atomic Charges,” J Chem Inf Model, vol. 52, no. 12, pp. 3155–3168, 2013, doi: 10.1021/ci3003649.
19. [19] H. M. Berman, “The Protein Data Bank,” Nucleic Acids Res., vol. 28, no. 1, pp. 235–242, Jan. 2000, doi: 10.1093/nar/28.1.235.
20. [20] A. P. Thompson et al., “LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales,” Comput. Phys. Commun., vol. 271, p. 108171, 2022, doi: 10.1016/j.cpc.2021.108171.
21. [21] R. B. Best et al., “Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone φ, ψ and side-chain χ1 and χ2 Dihedral Angles,” J. Chem. Theory Comput., vol. 8, no. 9, pp. 3257–3273, 2012, doi: 10.1021/ct300400x.
22. [22] A. D. MacKerell et al., “All-atom empirical potential for molecular modeling and dynamics studies of proteins,” J. Phys. Chem. B, vol. 102, no. 18, pp. 3586–3616, 1998, doi: 10.1021/jp973084f.
23. [23] S. Jo et al., “CHARMM-GUI 10 years for biomolecular modeling and simulation,” J. Comput. Chem., vol. 38, no. 15, pp. 1114–1124, 2017, doi: 10.1002/jcc.24660.
24. [24] W. Humphrey, A. Dalke, and K. Schulten, “VMD - Visual Molecular Dynamics,” J. Molec. Graph., vol. 14, pp. 33–38, 1996.
25. [25] S. Nosé, “A unified formulation of the constant temperature molecular dynamics methods,” J. Chem. Phys., vol. 81, no. 1, pp. 511–519, 1984, doi: 10.1063/1.447334.
26. [26] W. G. Hoover, “Canonical dynamics: Equilibrium phase-space distributions,” Phys. Rev. A, vol. 31, no. 3, pp. 1695–1697, Mar. 1985, doi: 10.1103/PhysRevA.31.1695.
27. [27] M. Parrinello and A. Rahman, “Polymorphic transitions in single crystals: A new molecular dynamics method,” J. Appl. Phys., vol. 52, no. 12, pp. 7182–7190, 1981, doi: 10.1063/1.328693.
28. [28] J. O. Wrabl, S. A. Larson, and V. J. Hilser, “Thermodynamic propensities of amino acids in the native state ensemble: Implications for fold recognition,” Protein Sci., vol. 10, no. 5, pp. 1032–1045, 2001, doi: 10.1110/ps.01601.
29. [29] S. Pal, P. Pyne, N. Samanta, S. Ebbinghaus, and R. K. Mitra, “Thermal stability modulation of the native and chemically-unfolded state of bovine serum albumin by amino acids,” Phys. Chem. Chem. Phys., vol. 22, no. 1, pp. 179–188, 2019, doi: 10.1039/c9cp04887a.
30. [30] F. Peccati and G. Jiménez-Osés, “Enthalpy-Entropy Compensation in Biomolecular Recognition: A Computational Perspective,” ACS Omega, vol. 6, no. 17, pp. 11122–11130, 2021, doi: 10.1021/acsomega.1c00485.
31. [31] P. J. Linstrom and W. G. Mallard, “The NIST Chemistry WebBook: A chemical data resource on the Internet,” J. Chem. Eng. Data, vol. 46, no. 5, pp. 1059–1063, 2001, doi: 10.1021/je000236i.
32. [32] I. M. Weiss, C. Muth, R. Drumm, and H. O. K. Kirchner, “Thermal decomposition of the amino acids glycine, cysteine, aspartic acid, asparagine, glutamic acid, glutamine, arginine and histidine,” BMC Biophys., vol. 11, no. 1, pp. 1–15, 2018, doi: 10.1186/s13628-018-0042-4.
33. [33] N. M. Goldenberg and B. E. Steinberg, “Surface charge: A key determinant of protein localization and function,” Cancer Res., vol. 70, no. 4, pp. 1277–1280, 2010, doi: 10.1158/0008-5472.CAN-09-2905.
34. [34] C. Clementi and S. S. Plotkin, “The effects of nonnative interactions on protein folding rates: Theory and simulation,” Protein Sci., vol. 13, no. 7, pp. 1750–1766, 2004, doi: 10.1110/ps.03580104.
35. [35] E. G. Asmus, “Protein Structure,” Am. Biol. Teach., vol. 69, no. 1, pp. 38–40, 2007.
36. [36] V. Raicu and A. Popescu, Integrated Molecular and Cellular Biophysics, no. July. Dordrecht: Springer Netherlands, 2008.
37. [37] Q. Cui et al., “Molecular Dynamics-Solvated Interaction Energy Studies of Protein-Protein Interactions: The MP1-p14 Scaffolding Complex,” J. Mol. Biol., vol. 379, no. 4, pp. 787–802, 2008, doi: 10.1016/j.jmb.2008.04.035.