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Article

Evaluation of the Lipophilicity of New Anticancer 1,2,3-Triazole-Dipyridothiazine Hybrids Using RP TLC and Different Computational Methods

by
Beata Morak-Młodawska
*,
Krystian Pluta
and
Małgorzata Jeleń
Faculty of Pharmaceutical Sciences in Sosnowiec, Department of Organic Chemistry, the Medical University of Silesia, Jagiellońska 4, 41-200 Sosnowiec, Poland
*
Author to whom correspondence should be addressed.
Processes 2020, 8(7), 858; https://doi.org/10.3390/pr8070858
Submission received: 2 June 2020 / Revised: 14 July 2020 / Accepted: 15 July 2020 / Published: 17 July 2020

Abstract

:
Two new anticancer-active 1,2,3-triazole-dipyridothiazine hybrids were evaluated for their lipophilicity using thin-layer chromatography (TLC) and computational methods. The experimental lipophilicity was evaluated with mobile phases (mixtures of TRIS buffer and acetone), exploiting a linear correlation between the retention parameter (RM) and the volume of acetone. The relative lipophilicity parameter (RM0) was obtained by extrapolation to 0% acetone concentration. This parameter was intercorrelated with a specific hydrophobic surface area (b) revealing two congeneric subgroups: hybrids of 1,2,3-triazole-2,7-diazaphenothiazines and 1,2,3-triazole-3,6-diazaphenothiazines. The parameter RM0 was converted into the absolute lipophilicity parameter logPTLC using a calibration curve prepared on the basis of compounds of known logP values. Triazole–dipyridothiazine hybrids turned out to be medium lipophilic with logPTLC values of 1.232–2.979. The chromatographically established parameter logPTLC was compared to the calculated lipophilic parameter logPcalcd obtained with various algorithms. The lipophilicity was correlated with molecular descriptors and ADME properties. The new triazole–dipyridothiazine hybrids followed Lipinski’s rule of five. The lipophilicity of these hybrids was dependent on the substituents attached to the triazole ring and the location of the azine nitrogen atoms.

Graphical Abstract

1. Introduction

Lipophilicity is one of the most crucial physicochemical properties. It plays a fundamental role in determining absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties, and, therefore, in determining the general appropriateness of drug candidates. There is increasing evidence suggesting that controlling molecular properties, such as lipophilicity, in an optimal range, can improve a drug’s quality and its therapeutic success [1]. Lipophilicity is an important parameter because it constitutes the single most informative and successful physicochemical property in medicinal chemistry [2,3,4]. Lipophilicity contributes to the ADMET characteristics of drugs by contributing to their solubility, permeability through membranes, potency, selectivity, and promiscuity, impacting upon their metabolism and pharmacokinetics, and also affecting their pharmacodynamic and toxicological profile [5,6].
Furthermore, the quantitative structure–activity relationship (QSAR) demonstrated that lipophilicity, evaluated with varied experimental methods, correlates well with other molecular properties (for example, polarity and the dissociation constant) and topological indices, and performs an essential role in predicting a drug’s behavior in a biological system (for example, in tissues and biological membranes) [7,8,9,10,11].
Lipophilicity also belongs to one of the five factors determining the bioavailability of a drug in Lipinski’s rule of five criteria. According to this rule, an orally active drug should not violate more than one of the following criterion: no more than 5 hydrogen bond donors, no more than 10 hydrogen bond acceptors, no more than 10 rotatable bonds, a molecular mass less than 500 Da, a lipophilicity parameter (logP) not greater than 5, and a polar molar surface area less than 140 Å [1,12,13] (Figure 1). Therefore, the lipophilicity property is recognized to be one of the most significant elements in the rationalization of drug design and discovery.
Dipyridothiazines (modified phenothiazines where the central thiazine ring is fused with two pyridine rings instead of two benzene rings) have turned out to be attractive scaffolds for new drug candidates, possessing anticancer activity and an improved safety profile. Structurally, dipyridothiazines differ in the tricyclic ring system (the pyridine nitrogen atoms in positions 1,6, 1,8, 1,9, 2,7, and 3,6) and the substituents at the central nitrogen atom (alkyl, dialkylaminoalkyl, cycloalkylaminoalkynyl, amidoalkyl, sulfonamidoalkyl, aryl, heteroaryl, and “half-mustard” groups). Some dipyridothiazines exhibited not only very promising anticancer activity, but also anti-inflammatory, antioxidant, and immunosuppressant activities, with a low toxicity [14,15,16,17,18,19,20,21,22,23]. Our previous research showed the relationship between biological properties and the lipophilicity of modified azaphenothiazines [24,25,26,27].
Recently, we synthesized a new group of 1,2,3-triazole-dipyridothiazine hybrids, which are derivatives of 2,7- and 3,6-diazaphenothiazines, possessing in vitro anticancer activity against cancer cell lines (breast cancer MDA-MB231, colorectal carcinoma Caco-2, glioblastoma SNB-19, and lung cancer A549) [28].
The main goal of this work was the evaluation of the lipophilicity of two new series of 1,2,3-triazole-2,7-diazaphenothiazine (1–5) and 1,2,3-triazole-3,6-diazaphenothiazine (6–10) hybrids, performed experimentally by reversed-phase thin-layer chromatography (RP TLC), and theoretically using computer programs. Furthermore, it was interesting to find correlations between experimental and theoretically predicted lipophilicity, and relationships between experimental lipophilicity and physicochemical and ADME properties. This study was performed with the hope of providing a deeper insight into the compounds’ properties and their biological activities. The structures of the investigated 1,2,3-triazole-2,7-diazaphenothiazine (1–5) and 1,2,3-triazole-3,6-diazaphenothiazine (6–10) hybrids are presented in Figure 2.

2. Materials and Methods

2.1. Materials

1,2,3-Triazole-dipyridothiazine hybrids (1–10) were synthesized as described recently [28]. Prothipendyl (11) (AWD Pharma, Dresden, Germany) was used (as a free base, 10-dimethylaminopropyl-1-azaphenothiazine) as the reference phenothiazine [24].

2.2. Chromatographic Procedure

TLC was carried out on 10 cm × 10 cm RP 18F254S plates precoated with silica gel (Merck, Warsaw, Poland) by the ascending technique at room temperature. The mobile phase was a mixture of acetone (POCh, Gliwice, Poland) and aqueous TRIS buffer (Fluka, Loughborough, England, pH 7.4, ionic strength 0.2 M) to satisfy physiological conditions with a concentration of acetone of 40–70% (v/v) in 5% increments. The investigated compounds (1–10), the reference compound (11), and the standards (I–V) of known lipophilicity (acetanilide, acetophenone, 4-bromoacetophenone, benzophenone, and anthracene [29,30]) were dissolved in ethanol (POCh, Gliwice, Poland, 2.0 mg/mL) and 2 μL of these solutions were spotted on the plates. The chromatograms were observed under UV light at μ = 254 nm. At least three experiments were carried out for each solution, and RF values were averaged.

2.3. Computational Programs

Eleven computational programs were employed to calculate the parameter logPcalcd using the internet databases VCCLAB [31] and SwissADME [32]. Molecular descriptors (topological polar surface area, molar mass, and refractivity) were calculated using CS Chem 3D Ultra 7.0 [33]. PreAdmet was used for the prediction of biological activities, such as human intestinal absorption (HIA), plasma protein binding (PB), blood–brain barrier (BBB) penetration, cell permeability MDCK, skin permeability (SP), and Caco-2 penetration [34].

3. Results

The lipophilicity of the tested 1,2,3-triazole-dipyridothiazine hybrids (1–10) was first evaluated using eleven of the most popular computer programs that are available on the online platforms VCCLAB and SwissADME [31,32]. The computational programs use diverse theoretical approaches, such as atomic, atomic–fragmental, fragmental, topological (relying on a linear relationship with molecular descriptors), hybrid (relying on fragments and topological descriptors), and neural networks (Alogps, AC_Logp, ALOGP, MLOGP, XLOGP2, XLOGP3, ILopP, XlogP, WlogP, MlogP, and SILICOS-IT). These programs are based on advanced mathematical models that are the basis of computational chemistry [31a,b; 32a,b]. The obtained logPcalcd values for hybrids 1–10 were totally distinct, depending on the engaged program (logPcalcd = 1.26–4.88, Table 1).
The experimental RP TLC method provided the retention parameter RM (calculated from the RF values) using the following equation:
RM = log(1/RF − 1).
The RM values decreased linearly, with an increasing concentration of acetone in the mobile phase (r = 0.9744–0.9950). These values extrapolated to 0% acetone gave the relative lipophilicity parameter (RM0) values, which characterize the partitioning between the non-polar stationary and polar mobile phases, using the equation:
RM = RM0 + bC,
where C is the concentration of acetone. The RM0 values are found within the range of 1.150–2.823 (Table 2).
The linear relationship between the relative lipophilicity parameter (RM0) and the slope (b), representing a specific hydrophobic surface area (RM0 = Bb + a), enabled us to find congeneric compound subclasses in the set of investigated compounds [35]. In addition, 1,2,3-Triazole-dipyridothiazine hybrids (1–10) belong to two groups of isomeric dipyridothiazines, with the structure of 2,7- and 3,6-diazaphenothiazines. They do not differ significantly in molecular descriptors, but differ in ADME activities (Table 3 and Table 4). The range of molar mass (372–406) and molar refractivity (108–116) could indicate the substituent diversity in the tested compounds. All tested derivatives meet the requirements of Lipinski’s rule of five.
The drugs selected to assess the intestinal absorption of drug candidates needed to use in vitro methods. Among them, the Caco-2 cell [36,37] and the MDCK cell models [38] are approved as reliable models in predicting oral drug absorption. The in silico HIA (human intestinal absorption) model and the skin permeability (SP) model are able to predict and identify drug candidates for oral and transdermal deliveries. Blood–brain barrier (BBB) penetration can provide information on a therapeutic drug in the central nervous system (CNS) and the plasma protein binding (PPB) model on its disposition and efficacy [34,36,37,38]. The compounds possess high indexes of HIA and PPB, although the indexes of BBB and MDCK (of selected compounds) are low in comparison with prothipendyl. Skin permeability (SP) and penetration of Caco-2 are comparable with the reference compound prothipendyl. The RM0 values were correlated with molecular descriptors and ADME activities (Table 5).
In order to transform the relative lipophilicity (RM0) values of hybrids 1–10 into the logPTLC values, the calibration curve was formed under the same chromatographic conditions using a set of standards (I–V), and by having the known literature values of logPlit. within the range of 1.21–4.45 (Table 6).
The logPTLC values for all 10 hybrids are presented in Table 7.

4. Discussion

This report deals with the lipophilicity evaluation of new anticancer-active 1,2,3-triazole-dipyridothiazine hybrids (1–10). Both series of dipyridothiazines (2,7- and 3,6-diazaphenothiazines) contain in their structure a ring of 1,2,3-triazole, with various benzyl substituents and a phenylthiomethyl substituent (Figure 2). These compounds possess promising anticancer activities in vitro against cancer cell lines (glioblastoma SNB-19, colorectal carcinoma Caco-2, lung cancer A549, and breast cancer MDA-MB231) and low cytotoxicity towards normal human fibroblasts (NHDF). The results of some additional experiments, such as analysis of the gene expression (H3, TP53, CDKN1A, BCL-2, and BAX), indicated the induction of mitochondrial apoptosis in cancer cell lines. The most active triazole–dipyridothiazine hybrids were found to be compound 1 against cancer lines Caco-2, A549, and MB231, 5 against A549 and MB231, and 7 against Caco-2 and A549, with IC50 values less than 1 μM [28].
The used computer software provided different logPcalcd values depending on the compound’s structure (the ring system and substituents) and the engaged program. The most lipophilic compound was derivative 5 (logPcalcd = 4.88), but slightly less lipophilic was isomeric compound 10 (logPcalcd = 4.79), both with the phenylthiomethyl group attached to the triazole ring. The least lipophilic compound was hybrid 4 (logPcalcd = 1.26), whereas its isomer 9 was more lipophilic (logPcalcd = 1.73). The graphical visualization of the calculated logP values are presented in Figure 3 and Figure 4. For each compound, large differences were observed, reaching close to 3 units. This makes it impossible to select the adequate values to describe the lipophilic property of new 1,2,3-triazole-dipyridothiazine hybrids.
The most relative lipophilicity RM0 value was shown for the compound 8 (with the p-chlorobenzyl substituent in the 1,2,3-triazole ring in 3,6-diazaphenothiazine). In contrast, the 2,7-diazaphenothiazine isomer 4 was among the least lipophilic. The least lipophilic character was exhibited by hybrid 2 (with the p-fluorobenzyl substituent) in the series of 2,7-diazaphenothiazines and hybrid 9 (with the p-cyanobenzyl substituent) in the series of 3,6-diazaphenothiazines.
The intercorrelation between the relative lipophilicity parameter (RM0) and the specific hydrophobic surface area (b) for all compounds (1–10) is given by the equation:
RM0 = −58.95b − 0.1293 (r = 0.9915).
This relationship indicated the existence of the anticipated congeneric subgroups:
  • the 2,7-diazaphenothiazine derivatives 1–5 RM0 = −57.811b − 0.0821 (r = 0.9936)
  • the 3,6-diazaphenothiazine derivatives 6–10 RM0 = −63.632b − 0.327 (r = 0.9949)
and was dependent on the places of the azine nitrogen atoms in the diazaphenothiazine structures (positions 2,7 and 3,6).
The values of RM0 for diazaphenothiazines (1–10) were correlated with molecular descriptors such as molar mass (M), topological polar molar surface area (TPSA), and molar refractivity (MR), giving moderate values of the correlation, which could be a consequence of the non-planar spatial arrangements of the dipyridothiazine ring system, placement of the azine nitrogen atoms, and complex substituents.
Next, the RM0 values were correlated with predicted ADME properties, such as blood–brain barrier (BBB) permeability, Caco-2 and MDCK cell base permeability, human intestinal absorption (HIA), plasma protein binding (PPB), and skin permeability (SP). The best correlations were found for the plasma protein binding (PPB) (r = 0.9145) and the blood–brain barrier (BBB) penetration (r = 0.8769). The correlations of the RM0 values with the other ADME parameters were moderate (r = 0.4144–0.6545). This fact suggests that the lipophilic property is one of the elements affecting biological activities and behavior during transport through biological tissues.
Comparison of the ADME properties of the tested derivatives (1–10) with the reference compound prothipendyl (11) (neuroleptic phenothiazine with the pyridobenzothiazine structure) provided valuable information. The tested compounds had substantially lower BBB penetration parameters, which may indicate that they were not be active in the central nervous system. All hybrids showed similar cell permeability (Caco-2) to prothipendyl (with the exception of compounds 3 and 8), but lower values of skin permeability (SP). The derivatives showed a slightly higher HIA compared with prothipendyl. In contrast, the parameters of PPB and MDCK were very diverse, depending largely on the type of substituent in the 1,2,3-triazole system and the type of dipyridothiazine.
The experimental RM0 values, showing relative lipophilic properties, of compounds 1–10 were transformed into absolute lipophilic properties as logPTLC values. For this purpose, the calibration equation was prepared with the same chromatographic procedure using standards I–V (Table 6) of known logPlit. values:
logPTLC = 0.9862RM0 + 0.1957   (r = 0.9949, s = 0.2246, F = 359.97, p = 0.0002).
The logPTLC values for all 10 hybrids were within the range of 1.232–2.979 (Table 7). The most lipophililic compound was hybrid 8 (logPTLC = 2.979), but the least lipophilic character was found for hybrid 9 (logPTLC = 1.509) in the series of 3,6-diazaphenothiazines. In the series of isomeric 2,7-diazaphenothiazines, the most lipophilic nature was showed by hybrid 5 (logPTLC = 2.569), but the least lipophilic compound was hybrid 2 (logPTLC = 1.330). The experimental logPTLC values were lower than the calculated logPcalcd values. In some cases, the differences between the logPTLC and logPcalcd values reached over 2 units. Figure 3 and Figure 4 show a visual comparison of the logPTLC and logPcalcd values.
The investigated 1,2,3-triazole-dipyridothiazine hybrids (1–10) turned out to be medium lipophilic. An effort to correlate the lipophilicity of these compounds with their anticancer activity (represented by the IC50 values) failed. In the most active compound (1) (against three cancer cell lines), there was found the same lipophilicity as compounds 2–4, which were 5–100 times less active.
The lipophilicity of the new 1,2,3-triazole-dipyridothiazine hybrids (1–10) was compared to the lipophilicity of the reference neuroleptic phenothiazine (11) of the pyridobenzothiazine structure. Prothipendyl (11) (logPTLC = 2.1767 (24)) turned out to be significantly more lipophilic than the 1,2,3-triazole-dipyridothiazine hybrids (1–4) and 9, but hybrids 5,6,8, and 10 possessed higher lipophilicity.
Analyzing the five factors determining the bioavailability of the drugs in Lipinski’s rule of five (hydrogen bond donors and acceptors, rotatable bonds, molecular mass, lipophilicity, and polar molar surface area), it can be stated that the tested hybrids (1–10) meet the rule of five and may become anticancer drug candidates in the future.

5. Conclusions

In summary, the lipophilicity of 10 new anticancer 1,2,3-triazole-dipyridothiazine hybrids was evaluated theoretically and experimentally using 11 computing programs and reversed-phase thin-layer chromatography. The experimental RP TLC method found these compounds to be medium lipophilic. None of the computing programs provided logPcalcd values that were all similar to the logPTLC values, which can be ascribed to their specific non-planar dipyridothiazine ring system and complex substituents with the triazole and benzene rings. These triazole–dipyridothiazine hybrids followed Lipinski’s rule. The lipophilicity of these hybrids was dependent on the substituents attached to the triazole ring and the location of the pyridine nitrogen atoms.
Finally, to search for relationships between physicochemical and pharmacological properties of the tested hybrids, preliminary QSAR examinations were undertaken. Some correlations between molecular descriptors (M, TPSA, and MR) and ADME activities (BBB, Caco-2, HIA, MDCK, PPB, and SP) and lipophilicity were noted. Further in vitro, in vivo, and in silico investigations are necessary to evaluate the potential pharmacological use of the new 1,2,3-triazole-dipyridothiazine hybrids in anticancer therapy.

Author Contributions

B.M.-M. and K.P. developed the concept of the work. B.M.-M. carried out the synthetic work, interpreted the results, and prepared the original draft. M.J. contributed to the synthesis and purification of selected compounds. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Medical University of Silesia in Katowice, grant KNW-1-055/K/9/O.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Arnott, J.A.; Planey, S.L. The influence of lipophilicity in drug discovery and design. Expert Opin. Drug Discov. 2012, 7, 863–875. [Google Scholar] [CrossRef] [PubMed]
  2. Tsopelas, F.; Giaginis, C.; Tsantili, A. Lipophilicity and biomimetic properties to support drug discovery. Expert Opin. Drug Discov. 2017, 12, 885–896. [Google Scholar] [CrossRef]
  3. Waring, M.J. Lipophilicity in drug discovery. Expert Opin. Drug Discov. 2010, 5, 235–238. [Google Scholar] [CrossRef] [PubMed]
  4. Lobo, S. Is there enough focus on lipophilicity in drug discovery? Expert Opin. Drug Discov. 2020, 15, 261–263. [Google Scholar] [CrossRef] [PubMed]
  5. Dąbrowska, M.; Komsta, Ł; Krzek, J.; Kokoszka, K. Lipophilicity study of eight cephalosporins by reversed-phase thin-layer chromatographic method. Biomed. Chromatogr. 2015, 29, 1759–1768. [Google Scholar] [CrossRef]
  6. Kulig, K.; Malawska, B. Estimation of the lipophilicity of antiarrhythmic and antihypertensive active 1-substituted pyrrolidin-2-one and pyrrolidine derivatives. Biomed. Chromatogr. 2003, 17, 318–324. [Google Scholar] [CrossRef]
  7. Dołowy, M.; Pyka, A. Evaluation of lipophilic properties of betamethasoneand related compounds. Acta Poloniae Pharm. Drug Res. 2015, 72, 671–681. [Google Scholar]
  8. Bajda, M.; Boryczka, S.; Wietrzyk, J.; Malawska, B. Investigation of the lipophilicity of anticancer-active tioquinoline derivatives. Biomed. Chromatogr. 2007, 21, 123–127. [Google Scholar] [CrossRef]
  9. Kadela-Tomanek, M.; Bober, K.; Bębenek, E.; Chrobak, E.; Boryczka, S. Application of thin-layer chromatography to evaluate the lipophilicity of 5,8-quinolinedione compounds. J. Planar Chromatogr. 2017, 30, 219–224. [Google Scholar] [CrossRef]
  10. Jeleń, M.; Pluta, K.; Morak-Młodawska, B. Lipophilicity estimation of anti-proliferative and anti-inflammatory 6-substituted 9-fluoroquino[3,2-b]benzo[1,4]thiazines. J. Liq. Chromatogr. Relat. Technol. 2019, 42, 563–569. [Google Scholar] [CrossRef]
  11. Bober, K.; Bębenek, E.; Boryczka, S. Application of TLC for Evaluation of the Lipophilicity of Newly Synthetized Esters: Betulin Derivatives. J. Anal. Methods Chem. 2019, 2019, 1–7. [Google Scholar] [CrossRef] [Green Version]
  12. Lipinski, C.; Lombardo, F.; Dominy, B.W.; Feeney, P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 2001, 46, 3–26. [Google Scholar] [CrossRef]
  13. Chagas, C.M.; Moss, S.; Alisaraie, L. Drug metabolites and their effects on the development of adverse reactions: Revisiting Lipinski’s Rule of Five. Int. J. Pharm. 2018, 549, 133–149. [Google Scholar] [CrossRef] [PubMed]
  14. Pluta, K.; Jeleń, M.; Morak-Młodawska, B.; Zimecki, M.; Artym, J.; Kocieba, M. Anticancer activity of newly synthesized azaphenothiazines from NCI’s anticancer screening bank. Pharmacol. Rep. 2010, 62, 319–332. Available online: http://www.if-pan.krakow.pl/pjp/pdf/2010/2_319.pdf (accessed on 8 February 2020). [CrossRef]
  15. Morak-Młodawska, B.; Pluta, K.; Matralis, A.N.; Kourounakis, A.P. Antioxidant Activity of Newly Synthesized 2,7-Diazaphenothiazines. Arch. Pharm. Chem. Life Sci. 2010, 343, 268–273. [Google Scholar] [CrossRef]
  16. Zimecki, M.; Artym, J.; Kocięba, M.; Pluta, K.; Morak-Młodawska, B.; Jeleń, M. Immunosupressive activities of newly synthesized azaphenothiazines in human and mouse models. Cell. Mol. Biol. Lett. 2009, 14, 622–635. [Google Scholar] [CrossRef] [PubMed]
  17. Morak-Młodawska, B.; Pluta, K.; Zimecki, M.; Jeleń, M.; Artym, J.; Kocięba, M. Synthesis and selected immunological properties of 10-substituted 1,8-diazaphenothiazines. Med. Chem. Res. 2015, 24, 1408–1418. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Morak-Młodawska, B.; Pluta, K.; Latocha, M.; Jeleń, M.; Kuśmierz, D. Synthesis, Anticancer Activity, and Apoptosis Induction of Novel 3,6-Diazaphenothiazines. Molecules 2019, 24, 267. [Google Scholar] [CrossRef] [Green Version]
  19. Morak-Młodawska, B.; Pluta, K.; Latocha, M.; Jelenń, M. Synthesis, spectroscopic characterization, and anticancer activity of new 10-substituted 1,6-diazaphenothiazines. Med. Chem. Res. 2016, 25, 2425–2433. [Google Scholar] [CrossRef] [Green Version]
  20. Morak-Młodawska, B.; Pluta, K.; Latocha, M.; Jeleń, M.; Kuśmierz, D. Synthesis and anticancer and lipophilic properties of 10-dialkylaminobutynyl derivatives of 1,8- and 2,7-diazaphenothiazines. J. Enzym. Inhib. Med. Chem. 2016, 31, 1132–1138. [Google Scholar] [CrossRef] [Green Version]
  21. Morak-Młodawska, B.; Pluta, K.; Latocha, M.; Suwińska, K.; Jeleń, M.; Kuśmierz, D. 3,6-Diazaphenothiazines as potential lead molecules–synthesis, characterization and anticancer activity. J. Enzyme Inhib. Med. Chem. 2016, 31, 1512–1519. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Zhang, J.; Chen, M.; Wenzhi, Z.; Okechukwu, P.N.; Morak-Młodawska, B.; Pluta, K.; Jeleń, M.; Md Akim, A.; Ang, K.-P.; Ooi, K.K. 10H-3,6-Diazaphenothiazines Induce G2/M Phase Cell Cycle Arrest, Caspase-dependent Apoptosis and Inhibits Cell Invasion of A2780 Ovarian Carcinoma Cells through Regulation on NF-κB and [BIRC6-XIAP] Complexes. Drug Des. Develop. Ther. 2017, 11, 3045–3063. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Morak-Młodawska, B.; Pluta, K.; Latocha, M.; Jeleń, M.; Kuśmierz, D.; Suwinska, K.; Shkurenko, A.; Czuba, Z.; Jurzak, M. 10H-1,9-diazaphenothiazine and its 10-derivatives: Synthesis, characterisation and biological evaluation as potential anticancer agents. J. Enzyme Inhib. Med. Chem. 2019, 34, 1298–1306. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Morak-Młodawska, B.; Pluta, K.; Jeleń, M. Estimation of the Lipophilicity of New Anticancer and Immunosuppressive 1,8-Diazaphenothiazine Derivatives. J. Chromatogr. Sci. 2015, 53, 462–466. [Google Scholar] [CrossRef] [Green Version]
  25. Morak-Młodawska, B.; Pluta, K.; Jeleń, M. Lipophilicity of New Anticancer 1,6- and 3,6-diazaphenothiazines by of Use RP TLC and Different Computational Methods. J. Chromatogr. Sci. 2018, 56, 376–381. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Jeleń, M.; Pluta, K.; Morak-Młodawska, B. Determination of the lipophilicity parameters of new antiproliferative 8-10-substituted quinobenzothiazines by computational methods and RP TLC. J. Liq. Chromatogr. Relat. Technol. 2014, 37, 1373–1382. [Google Scholar] [CrossRef]
  27. Jeleń, M.; Pluta, K.; Morak-Młodawska, B. The Lipophilicity Parameters of New Antiproliferative 6,9-Disubstituted Quinobenzothiazines Determined by Computational Methods and RP TLC. J. Liq. Chromatogr. Relat. Technol. 2015, 38, 1577–1584. [Google Scholar] [CrossRef]
  28. Morak-Młodawska, B.; Pluta, K.; Latocha, M.; Jeleń, M.; Kusmierz, D. Design, Synthesis, and Structural Characterization of Novel Diazaphenothiazines with 1,2,3-Triazole Substituents as Promising Antiproliferative Agents. Molecules 2019, 24, 4388. [Google Scholar] [CrossRef] [Green Version]
  29. Bodor, N.; Gabanyi, Z.; Wong, C.K. A new method for the estimation of partition coefficient. J. Am. Chem. Soc. 1989, 111, 3783–3786. [Google Scholar] [CrossRef]
  30. Mannhold, R.; Cruciani, G.; Dross, K.; Rekker, R. Multivariate analysis of experimental and computational descriptors of molecular lipophilicity. J. Comput. Aided Mol. Des. 1998, 12, 573–581. [Google Scholar] [CrossRef]
  31. Tetko, I.V.; Tanchuk, V.Y. Application of Associative Neural Networks for Prediction of Lipophilicity in ALOGPS 2.1 Program. J. Chem. Inf. Comput. Sci. 2002, 42, 1136–1145. Available online: http://www.vcclab.org (accessed on 9 February 2020). [CrossRef] [PubMed]
  32. Daina, A.; Michielin, O.; Zoete, V. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci. Rep. 2017, 7, 42717. Available online: http://swissadme.ch (accessed on 9 February 2020). [CrossRef] [PubMed] [Green Version]
  33. ClogP (CS Chem 3D Ultra, Molecular Modeling and Analysis, version 7.0) distributed by CambridgeSoft.
  34. Available online: http://preadmet.bmdrc.org (accessed on 9 February 2020).
  35. Biaggi, G.L.; Barbaro, A.M.; Sapone, A. Determination of the lipophilicity by means of reversed-phase. I: Basic aspects and relationship between slope and intercept of TLC equitions. J. Chromatogr. A 1994, 662, 341–361. [Google Scholar]
  36. Kulkarni, A.; Han, Y.; Hopfinger, A.J. Predicting Caco-2 Cell Permeation Coefficients of Organic Molecules Using Membrane-Interaction QSAR Analysis. J. Chem. Inf. Comput. Sci. 2002, 42, 331–342. [Google Scholar] [CrossRef]
  37. Feher, M.; Schmidt, J.M. Property Distributions: Differences Between Drugs, Natural Products, and Molecules from Combinatorial Chemistry. Chem. Inf. Comput. Sci. 2003, 34, 218–227. [Google Scholar] [CrossRef] [PubMed]
  38. Irvine, J.D.; Takahashi, L.; Lockhart, K.; Cheong, J.; Tolan, J.W.; Selick, H.E.; Grove, J.R. MDCK (Madin-Darby Canine Kidney) Cells: A Tool for Membrane Permeability Screening. J. Pharm. Sci. 1999, 88, 28–33. [Google Scholar] [CrossRef]
Figure 1. The visual interpretation of Lipinski’s rule of five criteria.
Figure 1. The visual interpretation of Lipinski’s rule of five criteria.
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Figure 2. Structure of 1,2,3-triazole-dipyridothiazine hybrids (1–10) and prothipendyl (11).
Figure 2. Structure of 1,2,3-triazole-dipyridothiazine hybrids (1–10) and prothipendyl (11).
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Figure 3. Graphical visualization of calculated logP values (using VCCLAB models) of the tested compounds with a comparison to logPTLC.
Figure 3. Graphical visualization of calculated logP values (using VCCLAB models) of the tested compounds with a comparison to logPTLC.
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Figure 4. Graphical visualization of the calculated logP values (using SwissADME models) of the tested compounds with a comparison to logPTLC.
Figure 4. Graphical visualization of the calculated logP values (using SwissADME models) of the tested compounds with a comparison to logPTLC.
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Table 1. The calculated logPcalcd values for 1,2,3-triazole-dipyridothiazine hybrids (1–10) using the internet databases: VCCLAB [31] and SwissADME [32].
Table 1. The calculated logPcalcd values for 1,2,3-triazole-dipyridothiazine hybrids (1–10) using the internet databases: VCCLAB [31] and SwissADME [32].
NoAlogpsAC_LogpALOGPMLOGPXLOGP2XLOGP3ILogPXLogPWlogPMlogPSILICOS-IT
13.362.733.891.612.982.832.712.162.261.912.19
23.723.344.552.103.613.463.022.792.912.402.82
33.312.794.101.992.944.122.782.262.812.292.60
43.042.543.771.272.712.552.521.882.131.262.21
53.504.884.481.883.413.482.572.812.812.182.28
62.982.643.351.612.902.502.472.503.392.372.64
72.912.703.561.993.062.602.972.603.952.753.04
82.621.632.862.583.634.653.223.134.042.873.27
92.902.453.231.272.622.222.402.223.261.732.65
103.324.793.941.883.323.143.042.943.882.642.72
Table 2. The RM0, b (slope), and r values of the equation RM = RM0 + bC for compounds 1–10.
Table 2. The RM0, b (slope), and r values of the equation RM = RM0 + bC for compounds 1–10.
No−bRM0r
10.02271.2290.9897
20.01981.1500.9788
30.02151.1550.9950
40.02531.2740.9869
50.04262.4070.9831
60.04162.2170.9744
70.03411.8670.9859
80.04922.8230.9853
90.02611.3320.9899
100.04172.3880.9781
Table 3. The molecular descriptors and parameters of Lipinski’s rule for 1,2,3-triazole-dipyridothiazine hybrids (1–10) and prothipendyl (11) [32,33].
Table 3. The molecular descriptors and parameters of Lipinski’s rule for 1,2,3-triazole-dipyridothiazine hybrids (1–10) and prothipendyl (11) [32,33].
NoMolecular Mass (M)H-bond AcceptorsH-bond DonorsRotatable BondsTPSAMol Refractivity (MR)
137240485.03108
239040485.03109
340640485.03113
4397504108.8114
5404405110.3116
637240485.03108
739040485.03109
840640485.03113
9397504108.8114
10404405110.3116
1128620444.686
Table 4. The predicted ADME activities for 1,2,3-triazole-dipyridothiazine hybrids (1–10) and prothipendyl (11) [34].
Table 4. The predicted ADME activities for 1,2,3-triazole-dipyridothiazine hybrids (1–10) and prothipendyl (11) [34].
NoBBBCaco2HIAMDCKPPBSP
10.54724.76998.11094.80888.062−3.742
20.28326.14698.5583.20373.476−4.184
30.98250.73597.66334.20689.739−3.795
40.19622.38299.75230.30887.208−3.682
50.27325.46599.0264.76394.100−3.491
60.83627.47698.11074.71491.502−3.508
71.06129.80398.09912.72391.532−3.881
81.43951.40297.66333.06793.582−3.634
90.22423.54699.75225.26689.391−3.517
100.40627.03799.0264.27798.907−3.320
113.10322.68497.47618.98375.453−3.100
Table 5. The correlation of the RM0 values with the molecular descriptors and predicted ADME activities for compounds 1–10.
Table 5. The correlation of the RM0 values with the molecular descriptors and predicted ADME activities for compounds 1–10.
NoMolecular Descriptor or ADME Activities Equation r
1–5
6–10
MRM0 = 69.511M2 − 240.09M + 579.21
RM0 = 30.107M2 − 118.14M + 501.3
0.4987
0.6546
1–5
6–10
TPSARM0 = 17.351TPSA + 69.8
RM0 = −9.699TPSA + 115.45
0.6989
0.4051
1–5
6–10
MRRM0 = 4.235MR + 105.89
RM0 = 6.099M2 − 24.708M + 135.43
0.6761
0.5020
1–10BBBBBB = 8.8792RM03 − 22.208RM02 + 16.225RM0 − 0.98890.8769
1–10Caco-2Caco-2 = 0.002RM03 − 0.2097RM02 + 6.9362RM0 − 71.7290.6545
1–10HIAHIA = −1.1492RM03 + 340.02RM02 − 335.35RM0 + 0.010.5377
1–10MDCKMDCK = 0.0005RM03 + 0.0018RM02 − 0.0583RM0 + 2.18020.4144
1–10PPBPPB = −0.0012RM03 + 0.3263RM02 − 28.461RM0 + 820.960.9145
1–10SPSP = −1.5107RM03 – 15.909RM02 − 53.876RM0 − 56.380.5870
Table 6. The RM0, logPlit., b (slope), and r values of the equation RM = RM0 + bC for standards I–V.
Table 6. The RM0, logPlit., b (slope), and r values of the equation RM = RM0 + bC for standards I–V.
No−bRM0rlogPTLC
I0.0181.0010.99791.21 (29)
II0.0191.5010.99741.58 (29)
III0.0332.2310.99602.43 (30)
IV0.0342.8860.99443.18 (29)
V0.0443.4880.99644.45 (29)
Table 7. The logPTLC values of investigated compounds 1–10.
Table 7. The logPTLC values of investigated compounds 1–10.
Compound
12345678910
logPTLC1.4081.3301.3351.4522.5692.3822.0372.9791.5092.551

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Morak-Młodawska, B.; Pluta, K.; Jeleń, M. Evaluation of the Lipophilicity of New Anticancer 1,2,3-Triazole-Dipyridothiazine Hybrids Using RP TLC and Different Computational Methods. Processes 2020, 8, 858. https://doi.org/10.3390/pr8070858

AMA Style

Morak-Młodawska B, Pluta K, Jeleń M. Evaluation of the Lipophilicity of New Anticancer 1,2,3-Triazole-Dipyridothiazine Hybrids Using RP TLC and Different Computational Methods. Processes. 2020; 8(7):858. https://doi.org/10.3390/pr8070858

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Morak-Młodawska, Beata, Krystian Pluta, and Małgorzata Jeleń. 2020. "Evaluation of the Lipophilicity of New Anticancer 1,2,3-Triazole-Dipyridothiazine Hybrids Using RP TLC and Different Computational Methods" Processes 8, no. 7: 858. https://doi.org/10.3390/pr8070858

APA Style

Morak-Młodawska, B., Pluta, K., & Jeleń, M. (2020). Evaluation of the Lipophilicity of New Anticancer 1,2,3-Triazole-Dipyridothiazine Hybrids Using RP TLC and Different Computational Methods. Processes, 8(7), 858. https://doi.org/10.3390/pr8070858

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