Performance of molecular dynamics simulation for predicting of solvation free energy of neutral solutes in methanol
-
Mohammad Emamian
,
Hojatollah Moradi
Abstract
In this study, molecular dynamics simulation was applied for calculating solvation free energy of 16 solute molecules in methanol solvent. The thermodynamic integration method was used because it was possible to calculate the difference in free energy in any thermodynamic path. After comparing results for solvation free energy in different force fields, COMPASS force field was selected since it had the lowest error compared to experimental result. Group-based summation method was used to compute electrostatic and van der Waals forces at 298.15 K and 1 atm. The results of solvation free energy were obtained from molecular dynamics simulation and were compared to the results from Solvation Model Density (SMD) and Universal Continuum Solvation Model (denoted as SM8), which were obtained from other research works. Average square-root-error for molecular dynamics simulation, SMD and SM8 models were 0.096091, 0.595798, and 0.70649. Furthermore, the coefficient of determination (R2) for molecular dynamics simulation was 0.9618, which shows higher accuracy of MD simulation for calculating solvation free energy comparing to two other models.
-
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
-
Research funding: None declared.
-
Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
References
1. Ben-Naim, A. Molecular theory of solutions. New York: Oxford University Press; 2006.10.1093/oso/9780199299690.001.0001Search in Google Scholar
2. Truhlar, DG, Pliego, JRJr. 7.3. Transition state theory and chemical reaction dynamics in solution. Weinheim: Wiley-VCH GmbH; 2006.Search in Google Scholar
3. Soteras, I, Blanco, D, Huertas, O, Bidon-Chanal, A, Luque, FJ. 3.2 Solvent effects in chemical equilibria. Continuum solvation models in chemical physics: from theory to applications. West Sussex: John Wiley & Sons; 2008:323 p.Search in Google Scholar
4. Matos, IQ and CR Abreu. Evaluation of the SAFT-γ Mie force field with solvation free energy calculations. Fluid Phase Equil 2019;484:88–97. https://doi.org/10.1016/j.fluid.2018.11.018.Search in Google Scholar
5. Shirts, MR, Pitera, JW, Swope, WC, Pande, VS. Extremely precise free energy calculations of amino acid side chain analogs: comparison of common molecular mechanics force fields for proteins. J Chem Phys 2003;119:5740–61. https://doi.org/10.1063/1.1587119.Search in Google Scholar
6. Zanith, CC and JR Pliego. Performance of the SMD and SM8 models for predicting solvation free energy of neutral solutes in methanol, dimethyl sulfoxide and acetonitrile. J Comput Aided Mol Des 2015;29:217–24. https://doi.org/10.1007/s10822-014-9814-3.Search in Google Scholar
7. Lyubartsev, A, Martsinovski, AA, Shevkunov, SV, Vorontsov-Velvaminov, PN. New approach to Monte Carlo calculation of the free energy: method of expanded ensembles. J Chem Phys 1992;96:1776–83. https://doi.org/10.1063/1.462133.Search in Google Scholar
8. Kirkwood, JG and EM Boggs. The radial distribution function in liquids. J Chem Phys 1942;10:394–402. https://doi.org/10.1063/1.1723737.Search in Google Scholar
9. Zwanzig, RW. Erratum: high‐temperature equation of state by a perturbation method. I. Nonpolar gases. J Chem Phys 1954;22:2099. https://doi.org/10.1063/1.1740022.Search in Google Scholar
10. Bennett, CH. Efficient estimation of free energy differences from Monte Carlo data. J Comput Phys 1976;22:245–68. https://doi.org/10.1016/0021-9991(76)90078-4.Search in Google Scholar
11. Shirts, MR and JD Chodera. Statistically optimal analysis of samples from multiple equilibrium states. J Chem Phys 2008;129:124105. https://doi.org/10.1063/1.2978177.Search in Google Scholar
12. Valleau, J. Density-scaling: a new Monte Carlo technique in statistical mechanics. J Comput Phys 1991;96:193–216. https://doi.org/10.1016/0021-9991(91)90271-l.Search in Google Scholar
13. Noroozi, J, Ghotbi, C, Jahanbin Sardroodi, J, Karimi-Sabet, J, Robert, MA. Solvation free energy and solubility of acetaminophen and ibuprofen in supercritical carbon dioxide: impact of the solvent model. J Supercrit Fluids 2016;109:166–76. https://doi.org/10.1016/j.supflu.2015.11.009.Search in Google Scholar
14. Garrido, NM, Queimada, AJ, Jorge, M, Macedo, EA, Economou, IG. 1-Octanol/water partition coefficients of n-alkanes from molecular simulations of absolute solvation free energies. J Chem Theor Comput 2009;5:2436–46. https://doi.org/10.1021/ct900214y.Search in Google Scholar PubMed
15. Garrido, NM, Jorge, M, Queimada, AJ, Macedo, EA, Economou, IG. Using molecular simulation to predict solute solvation and partition coefficients in solvents of different polarity. Phys Chem Chem Phys 2011;13:9155–64. https://doi.org/10.1039/c1cp20110g.Search in Google Scholar PubMed
16. Moradi, H, Azizpour, H, Bahmanyar, H, Mohammadi, M. Molecular dynamics simulation of H2S adsorption behavior on the surface of activated carbon. Inorg Chem Commun 2020;118:108048. https://doi.org/10.1016/j.inoche.2020.108048.Search in Google Scholar
17. Jafari, L, H Moradi, and Y Tavan. A theoretical and industrial study of component co-adsorption on 3A zeolite: an industrial case. Chem Paper 2020;74:651–61. https://doi.org/10.1007/s11696-019-00910-x.Search in Google Scholar
18. Moradi, H, Azizpour, H, Bahmanyar, H, Mohammadi, M, Akbari, M. Prediction of methane diffusion coefficient in water using molecular dynamics simulation. Heliyon 2020;6:e05385. https://doi.org/10.1016/j.heliyon.2020.e05385.Search in Google Scholar PubMed PubMed Central
19. Kwak, SK, JK Singh, and J Adhikari. Molecular simulation study of vapor-liquid equilibrium of morse fluids. Chem Prod Process Model 2007;2. https://doi.org/10.2202/1934-2659.1097.Search in Google Scholar
20. Farhadian, N, Shariaty-Niassar, M, Malek, K, Maghari, A. Coarse-Grained molecular dynamics simulation of lysozyme protein crystals. Chem Prod Process Model 2011;6. https://doi.org/10.2202/1934-2659.1544.Search in Google Scholar
21. Gharibzahedi, SMR and J Karimi-Sabet. Gas separation in nanoporous graphene from molecular dynamics simulation. Chem Prod Process Model 2016;11:29–33.10.1515/cppm-2015-0059Search in Google Scholar
22. Samandari-Masouleh, L, Mostoufi, N, Khodadadi, AA, Mortazavi, Y, Maghrebi, M. Kinetic modeling of carbon nanotube production and minimization of amorphous carbon overlayer deposition in floating catalyst method. Int J Chem React Eng 2012;10. https://doi.org/10.1515/1542-6580.2972.Search in Google Scholar
23. Goncalves, PF and H Stassen. Free energy of solvation from molecular dynamics simulation applying Voronoi-Delaunay triangulation to the cavity creation. J Chem Phys 2005;123:214109. https://doi.org/10.1063/1.2132282.Search in Google Scholar PubMed
24. Marenich, AV, Kelly, CP, Thompson, JD, Hawkins, GD, Chambers, CC, Giesen, DJ, et al.. Minnesota solvation database (MNSOL) version 2012. Minneapolis: University of Minnesota; 2020.Search in Google Scholar
25. Mohamed, NA, RT Bradshaw, and JW Essex. Evaluation of solvation free energies for small molecules with the AMOEBA polarizable force field. J Comput Chem 2016;37:2749–58. https://doi.org/10.1002/jcc.24500.Search in Google Scholar PubMed PubMed Central
26. Marenich, AV, CJ Cramer, and DG Truhlar. Universal solvation model based on solute electron density and on a continuum model of the solvent defined by the bulk dielectric constant and atomic surface tensions. J Phys Chem B 2009;113:6378–96. https://doi.org/10.1021/jp810292n.Search in Google Scholar PubMed
27. Marenich, AV, Olson, RM, Kelly, CP, Cramer, CJ, Truhlar, DG. Self-consistent reaction field model for aqueous and nonaqueous solutions based on accurate polarized partial charges. J Chem Theor Comput 2007;3:2011–33. https://doi.org/10.1021/ct7001418.Search in Google Scholar PubMed
28. Biovia, DS, Materials Studio. R2. San Diego: Dassault Systèmes BIOVIA; 2017.Search in Google Scholar
29. Bunte, SW and H Sun. Molecular modeling of energetic materials: the parameterization and validation of nitrate esters in the COMPASS force field. J Phys Chem B 2000;104:2477–89. https://doi.org/10.1021/jp991786u.Search in Google Scholar
30. Sui, J, Luo, Y, Zhai, J, Fan, F, Zhang, L, Lu, Y, et al.. Solubility measurement, model evaluation and molecular simulations of aprepitant (form I) in eight pure solvents. J Mol Liq 2020;304:112723. https://doi.org/10.1016/j.molliq.2020.112723.Search in Google Scholar
31. Yang, Y, Tang, W, Liu, S, Han, D, Liu, Y, Gong, J. Solubility of benzoin in three binary solvent mixtures and investigation of intermolecular interactions by molecular dynamic simulation. J Mol Liq 2017;243:472–83. https://doi.org/10.1016/j.molliq.2017.07.125.Search in Google Scholar
32. Jorge, M, Garrido, NM, Queimada, AJ, Economou, IG, Macedo, EA. Effect of the integration method on the accuracy and computational efficiency of free energy calculations using thermodynamic integration. J Chem Theor Comput 2010;6:1018–27. https://doi.org/10.1021/ct900661c.Search in Google Scholar
33. Steinbrecher, T, I Joung, and DA Case. Soft‐core potentials in thermodynamic integration: comparing one‐and two‐step transformations. J Comput Chem 2011;32:3253–63. https://doi.org/10.1002/jcc.21909.Search in Google Scholar PubMed PubMed Central
34. Linstrom, PJ. NIST chemistry webbook; 2005. Available from: http://webbook.nist.gov.Search in Google Scholar
© 2021 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Research Articles
- Three-phase modeling and optimization of benzene alkylation in commercial catalytic reactors
- Control of negative gain nonlinear processes using sliding mode controllers with modified Nelder-Mead tuning equations
- Novel control strategy for non-minimum-phase unstable second order systems: generalised predictor based approach
- Modelling adiabatic flame temperature for methane with an overview for advanced combustion process: flameless combustion
- Evaluation the effect of the ambient temperature on the liquid petroleum gas transportation pipeline
- Performance of molecular dynamics simulation for predicting of solvation free energy of neutral solutes in methanol
- Reviews
- Phase equilibria modeling of biorefinery-related systems: a systematic review
- On the drag force closures for multiphase flow modeling
Articles in the same Issue
- Frontmatter
- Research Articles
- Three-phase modeling and optimization of benzene alkylation in commercial catalytic reactors
- Control of negative gain nonlinear processes using sliding mode controllers with modified Nelder-Mead tuning equations
- Novel control strategy for non-minimum-phase unstable second order systems: generalised predictor based approach
- Modelling adiabatic flame temperature for methane with an overview for advanced combustion process: flameless combustion
- Evaluation the effect of the ambient temperature on the liquid petroleum gas transportation pipeline
- Performance of molecular dynamics simulation for predicting of solvation free energy of neutral solutes in methanol
- Reviews
- Phase equilibria modeling of biorefinery-related systems: a systematic review
- On the drag force closures for multiphase flow modeling
