Thermodynamic models for determination of the solid–liquid equilibrium of oxytocin in (acetonitrile + acetone) binary solvent mixtures
Introduction
The neurohypophysial hormone oxytocin (C43H66N12O12S2, CASRN: 50-56-6, shown in Fig. 1), or OT for short, is a white crystalline powder, which is a neuropeptide produced in the hypothalamus and released by neurohypophysis into the bloodstream, for its hormonal effects. It is named after the “quick birth” (ωkνξ = quick; τοκοξ = birth) which it causes due to its uterotonic activity [1], [2]. Hypothalamic oxytocinergic neurons also project to specific central areas involved in the modulation of pain and in motivation, sense of well-being, and sexual performance. OT is the first peptide hormone to have its structure determined and the first to be chemically synthesized in biologically active form [1], [2]. The solubilities of organic compounds in different solvents play an important role for understanding the solid–liquid equilibria (SLE) or phase equilibria in the development of a crystallization process, or liquid–liquid equilibria in extraction and extractive or azeotropic distillation processes [3], [4], [5]. More particularly, knowledge of an accurate solubility is needed for the design of separation processes such as extractive crystallization and the safety of operating different processing units such as distillation columns, adsorption units, and extraction plants. The solubility of OT can also supply basic and theoretical data for industrial production. To determine proper solvents and to design an optimized production process, it is necessary to know the solubilities of OT in different solvents [3], [4], [5], [13]. To our knowledge, we find no report of the solubility of OT in (acetonitrile + acetone) binary solvent mixtures.
In this work, the solubility of OT in (acetonitrile + acetone) binary solvent mixtures was measured from 278.15 K to 328.15 K under atmosphere pressure. The modified Apelblat equation, a variant of the combined nearly ideal binary solvent/Redich–Kister (CNIBS/R–K) model and Jouyban–Acree model were applied to correlate with the experimental data. This is the first attempt at modeling the solubility of OT in (acetonitrile + acetone) binary solvent mixtures using these specific thermodynamic models. The thermodynamic properties of the dissolution process, including enthalpy, entropy and Gibbs energy, were calculated by means of van’t Hoff analysis and Gibbs equation.
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Materials
Oxytocin (98% wt) was purchased from Aladdin (China). Its purity was measured by high performance liquid chromatography (HPLC type DIONEX P680 DIONEX Technologies). Acetonitrile and acetone for dissolving were supplied by Shanghai Shenbo Chemical Co., Ltd., China. The purities of the solvents were determined in our laboratory by gas chromatography and their mass fraction purities were higher than 0.997. Meanwhile, all chemical reagents were used without further purification. The properties of
Solubility data and thermodynamic models
The solubility data of oxytocin (x) in (acetonitrile + acetone) binary solvent mixtures with the temperature ranging from 278.15 K to 328.15 K are presented in Table 2, and graphically showed in Fig. 2. We could find that oxytocin had high solubility in pure acetone. The solubility in acetone showed the strongest positive dependency on temperature. The solubility of oxytocin depends not only on the temperature but also on the structure of the solvent. Polarity follows the order: acetonitrile >
Conclusions
The solubility of oxytocin in (acetonitrile + acetone) binary solvent mixtures from 278.15 K to 328.15 K was measured. It is obvious that the solubility increases with the rise of temperature and decreases with the rise of the ratio of acetonitrile. So acetonitrile could be used as an effective anti-solvent in the crystallization process.
The solubility data, as a whole, could be correlated with modified Apelblat equation best. Because modified Apelblat equation has the lowest MD data, and all
Acknowledgements
This research work was financially supported by Jiangsu Province Agricultural Science and Technology Innovation fund projects (CX(14)2057), Jiangsu Province Science and Technology support plan (BE2014386), Agricultural Science and Technology Achievements transformation projects (2014GB2C100317) and Major projects supported by the Natural Science Foundation of the Jiangsu Higher Education Institutions (14KJA180001).
We thank the editor and the anonymous reviewers.
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