Year 2025,
, 41 - 52, 05.01.2025
Suvarna Yendurı
,
Shifa K M
,
Naga Prashant Koppuravuri
References
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- [9] P. Jandera, Stationary phases for hydrophilic interaction chromatography, their characterization and implementation into multidimensional chromatography concepts, J Sep Sci 31 (2008) 1421–1437.
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- [16] P. Žuvela, M. Skoczylas, J. Jay Liu, T. Ba̧czek, R. Kaliszan, M.W. Wong, B. Buszewski, Column Characterization and Selection Systems in Reversed-Phase High-Performance Liquid Chromatography, Chem Rev 119 (2019) 3674–3729.
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- [22] N. Mardirossian, M. Head-Gordon, Thirty years of density functional theory in computational chemistry: an overview and extensive assessment of 200 density functionals, Mol Phys 115 (2017) 2315–2372.
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- [25] P. Hohenberg, W. Kohn, Inhomogeneous electron gas, Physical Review 136 (1964) B864-B871.
- [26] S.-C. Liu, X.-R. Zhu, D.-Y. Liu, D.-C. Fang, DFT calculations in solution systems: solvation energy, dispersion energy and entropy, Phys Chem Chemal Phys 25 (2023) 913–931.
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- [28] W. Tang, C. Cai, S. Zhao, H. Liu, Development of Reaction Density Functional Theory and Its Application to Glycine Tautomerization Reaction in Aqueous Solution, J Phys Chem C 122 (2018) 20745–20754.
- [29] W. Tang, J. Xuan, H. Wang, S. Zhao, H. Liu, First-principles investigation of aluminum intercalation and diffusion in TiO2 materials: Anatase versus rutile, J Power Sources 384 (2018) 249–255.
- [30] W. Tang, J. Zhao, P. Jiang, X. Xu, S. Zhao, Z. Tong, Solvent Effects on the Symmetric and Asymmetric S N 2 Reactions in the Acetonitrile Solution: A Reaction Density Functional Theory Study, J Phys Chem B 124 (2020) 3114–3122.
- [31] W. Tang, H. Yu, T. Zhao, L. Qing, X. Xu, S. Zhao, A dynamic reaction density functional theory for interfacial reaction-diffusion coupling at nanoscale, Chem Eng Sci 236 (2021) 116513.
- [32] M.A.K. Liton, Md. Nuruzzaman, S. Helen, Calculation of Gas-Phase Gibb’s free Energy Changes of Some Small Molecules with Monte Carlo, DFT (MPW1PW91), Composite (CBS-QB3), Gaussian-n (G1, G2) and Gaussian Modified (G2MP2) Methods, Oriental J Chem 35 (2019) 947–957.
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- [40] S. Yenduri, H. Sulthana, N.P. Koppuravuri, Sustainablity evaluation of existed HPLC based analytical methods for quantification of amlodipine besylate and telmisartan using RGB model: A whiteness approach, Green Anal Chem 6 (2023) 100074.
- [41] S. Yenduri, H.N. Varalakshmi, N.P. Koppuravuri, Assessment and Comparison of Greenness of UV-Spectroscopy Methods for Simultaneous Determination of Anti-Hypertensive Combination, Ind J Pharm Edu Res 58 (2024) s543–s551.
- [42] S. Yenduri, N.P. koppuravuri, V. H N, Assessment and comparison of sustainability aspects of UV-spectroscopy methods for simultaneous determination of anti-hypertensive combination, Green Anal Chem 9 (2024) 100108.
- [43] A. Gałuszka, Z.M. Migaszewski, P. Konieczka, J. Namieśnik, Analytical Eco-Scale for assessing the greenness of analytical procedures, TrAC Tr Anal Chem 37 (2012) 61–72.
- [44] H.D. Snyder, T.G. Kucukkal, Computational Chemistry Activities with Avogadro and ORCA, J Chem Educ 98 (2021) 1335–1341.
- [45] https://www.orcasoftware.de/tutorials_orca/prop/thermo.html, (n.d.).
- [46] M.D. Hanwell, D.E. Curtis, D.C. Lonie, T. Vandermeersch, E. Zurek, G.R. Hutchison, Avogadro: an advanced semantic chemical editor, visualization, and analysis platform, J Cheminform 4 (2012) 17.
- [47] M. Bourass, A.T. Benjelloun, M. Benzakour, M. Mcharfi, M. Hamidi, S.M. Bouzzine, M. Bouachrine, DFT and TD-DFT calculation of new thienopyrazine-based small molecules for organic solar cells, Chem Cent J 10 (2016) 67.
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Determining binding free energy by computational modelling: A theoretical approach for selection of stationary phase in chromatographic studies
Year 2025,
, 41 - 52, 05.01.2025
Suvarna Yendurı
,
Shifa K M
,
Naga Prashant Koppuravuri
Abstract
HPLC is one of the most widely used analytical method for determination of pharmaceuticals in pharmaceutical industry. Because of wide range availability of columns, it is difficult to choose the column while optimization and it consume lot of time. To reduce the time and solvent consumption for optimizing the column in HPLC method the best alternative is computational approach. Computational chemistry is a subfield of chemistry that employs computer modelling as a means of assisting in the resolution of difficult chemical issues. The computation of molecular structures, interactions, and properties is accomplished by the utilization of theoretical chemistry techniques that are integrated into efficient computer programs. In the current investigation, the objective was to implement a computational strategy with the purpose of optimizing the chromatographic column for the detection of certain pharmaceuticals. For the purpose of this experiment, the Avogadro with orca software was utilized to calculate the Gibbs free energy between the stationary phase and the pharmaceutical of choice for different columns, including C8 and C18. Relative binding free energies between the analyte and column were calculated and applied for selection of column. The tool was utilized for the purpose of optimizing the column in order to minimize the amount of solvent that was utilized and time to lessen the complexity of the procedure. This strategy also contributes to sustainable development goals by minimizing solvent usage for environmental friendliness.
Supporting Institution
Sri Adichunchanagiri College of Pharmacy
Thanks
All the authors are thankful to the staff of Sri Adichunchanagiri college of pharmacy for their continuous support throughout the research work.
References
- [1] D.A. Skoog, Holler F, Stanley Crouch, Principles of Instrumental Analysis, 7th ed., 2017.
- [2] O. Coskun, Separation Techniques: Chromatography, North Clin Istanb 3 (2016) 156-160.
- [3] J.J. Kirkland, Development of some stationary phases for reversed-phase HPLC, J Chromatogr A 1060 (2004) 9–21.
- [4] M.W.F. Nielen, R.W. Frei, U.A.Th. Brinkman, Chapter 1 On-Line Sample Handling and Trace Enrichment in Liquid Chromatography. The Determination of Organic Compounds in Water Samples, in: Selective Sample Handing and Detection in High Performance Liquid Chromatography, 1988: pp. 5–80.
- [5] S. Fasoula, Ch. Zisi, P. Nikitas, A. Pappa-Louisi, Retention prediction and separation optimization of ionizable analytes in reversed-phase liquid chromatography by organic modifier gradients in different eluent pHs, J Chromatogr A 1305 (2013) 131–138.
- [6] R. Majors, Historical developments in HPLC and UHPLC column technology: The past 25 years, LC GC N Am 33 (2015) 818–840.
- [7] A. Astefanei, I. Dapic, M. Camenzuli, Different Stationary Phase Selectivities and Morphologies for Intact Protein Separations, Chromatographia 80 (2017) 665–687.
- [8] A.U. Kulikov, M.N. Galat, Comparison of C18 silica bonded phases selectivity in micellar liquid chromatography, J Sep Sci 32 (2009) 1340–1350.
- [9] P. Jandera, Stationary phases for hydrophilic interaction chromatography, their characterization and implementation into multidimensional chromatography concepts, J Sep Sci 31 (2008) 1421–1437.
- [10] S. Bocian, B. Buszewski, Phenyl‐bonded stationary phases—The influence of polar functional groups on retention and selectivity in reversed‐phase liquid chromatography, J Sep Sci 37 (2014) 3435–3442.
- [11] P. Jandera, Optimisation of gradient elution in normal-phase high-performance liquid chromatography, J Chromatogr A 797 (1998) 11–22.
- [12] E.O. Dela Cruz, M.R. Euerby, C.M. Johnson, C. Hackett, Chromatographic classification of commercially available reverse-phase HPLC columns, Chromatographia 44 (1997) 151–161.
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- [14] M.W. Dong, HPLC column standardization in pharmaceutical development: A case study, LC-GC North America 29 (2016) 589–594.
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- [17] K.A.M. Attia, N.M. El-Abasawi, A. El-Olemy, A.H. Abdelazim, M. El-Dosoky, Simultaneous Determination of Elbasvir and Grazoprevir in Their Pharmaceutical Preparation Using High-Performance Liquid Chromatographic Method, J Chromatogr Sci 56 (2018) 731–737.
- [18] E.G. Lewars, An Outline of What Computational Chemistry Is All About, in: Computational Chemistry, Springer International Publishing, Cham, 2016: pp. 1–8.
- [19] E.G. Lewars, Introduction to Quantum Mechanics in Computational Chemistry, in: Computational Chemistry, Springer Netherlands, Dordrecht, 2011. https://doi.org/10.1007/978-90-481-3862-3.
- [20] E. Sim, S. Song, S. Vuckovic, K. Burke, Improving Results by Improving Densities: Density-Corrected Density Functional Theory, J Am Chem Soc 144 (2022) 6625–6639.
- [21] Á. Nagy, Density functional. Theory and application to atoms and molecules, Phys Rep 298 (1998) 1–79.
- [22] N. Mardirossian, M. Head-Gordon, Thirty years of density functional theory in computational chemistry: an overview and extensive assessment of 200 density functionals, Mol Phys 115 (2017) 2315–2372.
- [23] M. Altarawneh, Virtual undergraduate chemical engineering labs based on density functional theory calculations, Chem Teacher Int 6 (2024) 5–17. https://doi.org/10.1515/cti-2022-0054.
- [24] E.S. Aazam, R. Thomas, Understanding the behavior of a potential anticancer lamotrigine in explicit solvent (water and DMSO) using quantum mechanical tools and abinitio molecular dynamics, Chemical Physics Impact 8 (2024) 100404.
- [25] P. Hohenberg, W. Kohn, Inhomogeneous electron gas, Physical Review 136 (1964) B864-B871.
- [26] S.-C. Liu, X.-R. Zhu, D.-Y. Liu, D.-C. Fang, DFT calculations in solution systems: solvation energy, dispersion energy and entropy, Phys Chem Chemal Phys 25 (2023) 913–931.
- [27] H. Zhang, W. Tang, P. Xie, S. Zhao, Demystifying Solvent Effects on Diels–Alder Reactions in Pure and Mixed Solvents: A Combined Electronic DFT and QM/MM Study, Ind Eng Chem Res 62 (2023) 7721–7730.
- [28] W. Tang, C. Cai, S. Zhao, H. Liu, Development of Reaction Density Functional Theory and Its Application to Glycine Tautomerization Reaction in Aqueous Solution, J Phys Chem C 122 (2018) 20745–20754.
- [29] W. Tang, J. Xuan, H. Wang, S. Zhao, H. Liu, First-principles investigation of aluminum intercalation and diffusion in TiO2 materials: Anatase versus rutile, J Power Sources 384 (2018) 249–255.
- [30] W. Tang, J. Zhao, P. Jiang, X. Xu, S. Zhao, Z. Tong, Solvent Effects on the Symmetric and Asymmetric S N 2 Reactions in the Acetonitrile Solution: A Reaction Density Functional Theory Study, J Phys Chem B 124 (2020) 3114–3122.
- [31] W. Tang, H. Yu, T. Zhao, L. Qing, X. Xu, S. Zhao, A dynamic reaction density functional theory for interfacial reaction-diffusion coupling at nanoscale, Chem Eng Sci 236 (2021) 116513.
- [32] M.A.K. Liton, Md. Nuruzzaman, S. Helen, Calculation of Gas-Phase Gibb’s free Energy Changes of Some Small Molecules with Monte Carlo, DFT (MPW1PW91), Composite (CBS-QB3), Gaussian-n (G1, G2) and Gaussian Modified (G2MP2) Methods, Oriental J Chem 35 (2019) 947–957.
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- [39] N.P.K. Yenduri Suvarna, Recent Research Trends in Pharmaceutical Science (Volume - 2), Integrated Publications, 2023. https://doi.org/10.22271/int.book.300.
- [40] S. Yenduri, H. Sulthana, N.P. Koppuravuri, Sustainablity evaluation of existed HPLC based analytical methods for quantification of amlodipine besylate and telmisartan using RGB model: A whiteness approach, Green Anal Chem 6 (2023) 100074.
- [41] S. Yenduri, H.N. Varalakshmi, N.P. Koppuravuri, Assessment and Comparison of Greenness of UV-Spectroscopy Methods for Simultaneous Determination of Anti-Hypertensive Combination, Ind J Pharm Edu Res 58 (2024) s543–s551.
- [42] S. Yenduri, N.P. koppuravuri, V. H N, Assessment and comparison of sustainability aspects of UV-spectroscopy methods for simultaneous determination of anti-hypertensive combination, Green Anal Chem 9 (2024) 100108.
- [43] A. Gałuszka, Z.M. Migaszewski, P. Konieczka, J. Namieśnik, Analytical Eco-Scale for assessing the greenness of analytical procedures, TrAC Tr Anal Chem 37 (2012) 61–72.
- [44] H.D. Snyder, T.G. Kucukkal, Computational Chemistry Activities with Avogadro and ORCA, J Chem Educ 98 (2021) 1335–1341.
- [45] https://www.orcasoftware.de/tutorials_orca/prop/thermo.html, (n.d.).
- [46] M.D. Hanwell, D.E. Curtis, D.C. Lonie, T. Vandermeersch, E. Zurek, G.R. Hutchison, Avogadro: an advanced semantic chemical editor, visualization, and analysis platform, J Cheminform 4 (2012) 17.
- [47] M. Bourass, A.T. Benjelloun, M. Benzakour, M. Mcharfi, M. Hamidi, S.M. Bouzzine, M. Bouachrine, DFT and TD-DFT calculation of new thienopyrazine-based small molecules for organic solar cells, Chem Cent J 10 (2016) 67.
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