Chromatographic and Computational Studies of Molecular Lipophilicity and Drug-likeness for few 2-Thioxo-1,3-Thiazolidin-4-one Derivatives and their Analogs

Chromatographic and Computational Studies of Molecular Lipophilicity and Drug-likeness for few... Abstract Hydrophobicity of the eight 2-thioxo-1,3-thiazolidin-4-one derivatives was determined experimentally by thin-layer chromatography and predicted by means of commercially available programmers. RM values were determined by reversed-phase thin-layer chromatography with using acetonitrile–water, methanol–water, acetone–water, propan-2-ol–water or 1,4-dioxane–water and compared with logP values calculated by using computer programs: HyperChem 8.0.10, Virtual Chemical Calculation Laboratory, ACD/LogP. The drug-likeness has been calculated using Molinspiration. All the heterocycles were found to obey Lipinski’s rule of 5 for an orally active drug. Introduction A very important molecular descriptor that often links well with the bioactivity of chemicals is a lipophilicity (1). The wide-ranging application of lipophilicity to drug design elucidates the requirement for fast procedures to quantify molecular lipophilicity, particularly at the screening level. Octanol–water partition coefficients (logP) is the most common lipophilicity parameter. It can be determined by directly by liquid-liquid extraction method (2) with appropriate analytical methods such as (ultraviolet–visible) UV/Vis spectroscopy (3) or high-performance liquid chromatography (HPLC) (4). The methods are poor reproducibility and time consuming as well as requires high purity of analytes. Reversed-phase (RP)-HPLC (4) or reversed-phase thin-layer chromatography (RP-TLC) (5) techniques are very well-known indirect alternative method in logP evaluation since they have the advantage of the high-throughput and small amount of solutes needed and less strict purity requirement since the impurities are separated during the chromatographic process. These methods characterize relatively simple, rapid, low cost and easy perform. Relying on the nature of the compounds and under appropriate conditions, one to one correlation may be established logP and logkw/RMw values (6). Despite experimental method determination of lipophilicity, various methods for logP computation have been proposed based on the different mathematic algorithms (7, 8). The lipophilicity data obtained experimentally are usually compared with the calculated lipophilicity indices e.g., logPHyperChem, milogP, clogP, ALOGPs, AClogP, AlogP, MLOGP, KOWWIN, XLOGP2 and XLOGP3 (9, 10). The main goal of the studies was to apply RP-TLC to indirect determination lipophilicity descriptor (RMW) of 2-thioxo-1,3-thiazolidin-4-one derivatives (Figure 1) with using acetonitrile–water, methanol–water, acetone–water, propan-2-ol–water or 1,4-dioxane–water mixtures. The second stage was evaluated of other lipophilicity parameters in silico method (AlogPs, AClogP, AlogP, MlogP, XlogP2, XlogP3, logPHyperChem and LogPACD). The next stage was comparison and assessment of all obtained results. The last stage was evaluate of bioactivity by means of online data server Molinspiration. Figure 1. View largeDownload slide Scheme of Knoevenagel condensation of rhodamine. Figure 1. View largeDownload slide Scheme of Knoevenagel condensation of rhodamine. Experimental part Synthesis of model compounds Synthesis of the studied series of 5-cinnamylidenerhodanines (2a–f) and 5-cynamylidine-2-thioimidazolidin-4-one (5-cynamylidene-2-thiohydantoin) (2h) derivatives was carried out by Knoevenagel condensation of rhodanine by means of the corresponding 3-alkylrhodanine and 1-acetyl-2-thio-imidazolidin-4-one (1-acetyl-2-tiohydantoin) with the cinnamic aldehyde (Figure 1). The condensation reaction between the cinnamic aldehyde of rhodanine, and 3-alkylrhodanine was carried out in acetic anhydride by the procedure described previously (11). Condensation of 1-acetyl-2-thio-imidazolidin-4-one with cinnamic aldehyde was carried out in isopropanol in the presence of triethylamine as a catalyst. Under the applied conditions, the reaction is followed by separation of the acetyl group of the N-1 in the ring of 1-acetyl-2-thiohydantoine and condensation of cinnamic aldehyde in C-5 position. 5-Cynnamylidene-2-thiohydantoin was obtained. Cynnamylidene-5-thiazolidine-2,4-dione (2g) was prepared from 5-cynnamylidenorhodanine (2a) subjecting it to hydrolysis in a hydrochloric acid conditions (12). Rhodanine and 3-alkylrhodanine were prepared according to the procedures described previously in order to carry out the necessary condensation. Unsubstituted rhodanine was obtained by the reaction of ammonium thiocyanate with chloroacetic acid according to the method developed by Nencki (13). 3-Alkylrhodanines used in the condensation were obtained with primary aliphatic amines in accordance with the procedure proposed by Holmberg (14). 1-Acetyl-2-thio-imidazolidine-4-one (1-acetyl-2-tiohydantoine) was obtained according to the procedure proposed by Burgess (15). Glycine, acetic anhydride and ammonium thiocyanate were employed in the reaction. The synthesis was carried out in water, heating the reaction mixture to 100°C for 30 min. Evaluation of lipophilicity by RP-TLC Five chromatographic systems were applied to determine RM values with the used of silica gel RP18 F254 plates (Merck, Darmstadt, Germany) as a stationary phase, mobile phase—water and organic modifier (methanol, acetonitrile, acetone, propan-2-ol, 1,4-dioxane) which content varied from 40% to 100% (v/v) in 10% increments. Studied compounds were dissolved in the solvent used as a modifier of mobile phase (2 mg/mL) and 1 μL were applied on the plate with an interval 1 cm between circular spots using micropipette (Brand, Wertheim, Germany). The starting line was 0.5 cm from the lower edge of the plate. The plates were developed over a path of 4 cm in a chamber 5 × 5 cm (Desaga, Sarstedt, Germany) at room temperature, previously equilibrated for 2h. After development, the plates were dried in a gentle stream of air and the spots were visualized in λ = 254 nm UV light by means of a Merck UV lamp. An arithmetic average was calculated from four independent TLC measurements. Calculation of lipophilicity (logP) Three computer softwares: HyperChem 8.0.10 (HyperCube Inc., Gainesville, USA; http://www.hyper.com/), Virtual Chemical Calculation Laboratory (http://www.vcclab.org) and ACD/LogP (Advanced Chemistry Development Inc., Toronto, Kanada; http://www.acdlabs.com/) based on different calculation methods for computing logP have been compared in this studies. Rule of five and bioactivity score The physicochemical parameters including octanol partition coefficients (miLogP), molecular mass (MW), number of hydrogen bonds donors (NHBD), number of hydrogen bond acceptors (NHBA), total polar surface (TPSA), molecular volume (V), number of rotatable bonds (NORB) and number of violation (NV) were calculated. The bioactivity score for studied compounds was assessed with the combination of G protein–coupled receptors (GPCR) ligands, kinase inhibitors, ion channel modulators, enzymes and nuclear receptors. Calculations were accomplished with Molinspiration Software using molinspiration server (http://www.molinspiration.com/cgi-bin/properties). Results Determination of lipophilicity parameters In the relation between the structure and activity, lipophilic character logP appears to be the most important among physicochemical parameter. The aim of the studies is to determine the lipophilicity of eight 2-thioxo-1,3-thiazolidin-4-one derivatives. Lipophilicity parameters RM0 in RP-TLC were established by means of Equation (16): RM=RM0+Aϕ, (1) where RM=log(1Rf−1) (17) and ϕ is the volume fraction of the organic solvent (methanol, acetonitrile, acetone, propan-2-ol, 1,4-dioxane) in the mobile phase. RM0 as an intercept is the extrapolated value corresponding to ϕ as 0% of the volume fraction of the organic solvent. A is the slope of the linear relationship of Equation (1). The obtained data are shown in Table I. Table I. Parameters of the Relationship Between the Retention Factor (RM) and Volume Fraction (v/v) of Organic Component in the Mobile Phase Equation Obtained by TLC-RP Eluent Content of organic modifier in the mobile phase, % Compound RM0 SD of RM0 Aa SD of A r2 Acetonitrile 40–100 2a 2.320 0.0499 −2.817 0.0526 0.9417 50–100 2b 4.125 0.0607 −4.384 0.0661 0.9920 70–100 2c 5.561 0.4336 −5.648 0.4727 0.8908 60–100 2d 4.875 0.0460 −5.101 0.0533 0.9668 60–100 2e 4.999 0.0967 −5.087 0.0959 0.9889 60–100 2f 4.772 0.1768 −4.761 0.1627 0.9752 30–100 2g 2.616 0.0209 −3.480 0.0405 0.9217 40–100 2h 2.412 0.0535 −3.615 0.0709 0.9461 Methanol 40–100 2a 5.889 0.467 −3.402 −0.405 0.9644 70–100 2b 6.537 0.998 −5.953 −0.878 0.9519 80–100 2c 7.879 1.300 −7.704 −1.183 0.8567 70–100 2d 5.452 0.5535 −5.393 −0.4767 0.8899 80–100 2e 6.864 1.172 −6.783 −1.079 0.9114 80–100 2f 5.452 1.235 −6.386 −1.172 0.9090 40–100 2g 2.729 0.257 −3.402 −0.2054 0.9721 40–100 2h 3.058 0.237 −3.515 −0.083 0.9645 Acetone 60–100 2a 3.812 0.195 −4.587 0.182 0.9217 70–100 2b 5.975 0.250 −6.736 0.277 0.9547 70–100 2c 7.587 0.293 −8.319 0.301 0.9718 70–100 2d 6.099 0.320 −6.816 0.377 0.9515 70–100 2e 7.298 0.403 −8.035 0.438 0.9625 70–100 2f 7.599 0.769 −8.365 0.839 0.9841 60–100 2g 3.590 0.120 −4.420 0.125 0.9247 60–100 2h 4.051 0.198 −5.158 0.184 0.9043 Propan-2-ol 30–100 2a 2.583 0.023 −3.459 0.019 0.9213 60–100 2b 2.922 0.198 −3.301 0.210 0.9389 60–100 2c 4.199 0.3457 −4.547 0.377 0.9195 60–100 2d 3.027 0.125 −3.396 0.120 0.9446 60–100 2e 3.636 0.1167 −3.997 0.134 0.9217 60–100 2f 3.434 0.285 −3.742 0.293 0.9512 30–100 2g 2.146 0.110 −3.156 0.134 0.882 30–100 2h 2.296 0.112 −3.642 0.120 0.8983 1,4-Dioxane 40–100 2a 4.625 0.017 −6.113 0.015 0.9390 70–100 2b 4.921 0.224 −5.712 0.248 0.8698 70–100 2c 7.588 0.767 −8.477 0.8227 0.9733 70–100 2d 5.566 0.367 −6.3642 0.422 0.9190 70–100 2e 6.364 0.144 −7.099 0.200 0.9005 70–100 2f 6.071 0.252 −6.777 0.309 0.8950 40–100 2g 4.041 0.080 −5.650 0.149 0.9355 40–100 2h 3.705 0.175 −5.351 0.194 0.9592 Eluent Content of organic modifier in the mobile phase, % Compound RM0 SD of RM0 Aa SD of A r2 Acetonitrile 40–100 2a 2.320 0.0499 −2.817 0.0526 0.9417 50–100 2b 4.125 0.0607 −4.384 0.0661 0.9920 70–100 2c 5.561 0.4336 −5.648 0.4727 0.8908 60–100 2d 4.875 0.0460 −5.101 0.0533 0.9668 60–100 2e 4.999 0.0967 −5.087 0.0959 0.9889 60–100 2f 4.772 0.1768 −4.761 0.1627 0.9752 30–100 2g 2.616 0.0209 −3.480 0.0405 0.9217 40–100 2h 2.412 0.0535 −3.615 0.0709 0.9461 Methanol 40–100 2a 5.889 0.467 −3.402 −0.405 0.9644 70–100 2b 6.537 0.998 −5.953 −0.878 0.9519 80–100 2c 7.879 1.300 −7.704 −1.183 0.8567 70–100 2d 5.452 0.5535 −5.393 −0.4767 0.8899 80–100 2e 6.864 1.172 −6.783 −1.079 0.9114 80–100 2f 5.452 1.235 −6.386 −1.172 0.9090 40–100 2g 2.729 0.257 −3.402 −0.2054 0.9721 40–100 2h 3.058 0.237 −3.515 −0.083 0.9645 Acetone 60–100 2a 3.812 0.195 −4.587 0.182 0.9217 70–100 2b 5.975 0.250 −6.736 0.277 0.9547 70–100 2c 7.587 0.293 −8.319 0.301 0.9718 70–100 2d 6.099 0.320 −6.816 0.377 0.9515 70–100 2e 7.298 0.403 −8.035 0.438 0.9625 70–100 2f 7.599 0.769 −8.365 0.839 0.9841 60–100 2g 3.590 0.120 −4.420 0.125 0.9247 60–100 2h 4.051 0.198 −5.158 0.184 0.9043 Propan-2-ol 30–100 2a 2.583 0.023 −3.459 0.019 0.9213 60–100 2b 2.922 0.198 −3.301 0.210 0.9389 60–100 2c 4.199 0.3457 −4.547 0.377 0.9195 60–100 2d 3.027 0.125 −3.396 0.120 0.9446 60–100 2e 3.636 0.1167 −3.997 0.134 0.9217 60–100 2f 3.434 0.285 −3.742 0.293 0.9512 30–100 2g 2.146 0.110 −3.156 0.134 0.882 30–100 2h 2.296 0.112 −3.642 0.120 0.8983 1,4-Dioxane 40–100 2a 4.625 0.017 −6.113 0.015 0.9390 70–100 2b 4.921 0.224 −5.712 0.248 0.8698 70–100 2c 7.588 0.767 −8.477 0.8227 0.9733 70–100 2d 5.566 0.367 −6.3642 0.422 0.9190 70–100 2e 6.364 0.144 −7.099 0.200 0.9005 70–100 2f 6.071 0.252 −6.777 0.309 0.8950 40–100 2g 4.041 0.080 −5.650 0.149 0.9355 40–100 2h 3.705 0.175 −5.351 0.194 0.9592 aA is the slope of the linear relationship of Equation (1). Table I. Parameters of the Relationship Between the Retention Factor (RM) and Volume Fraction (v/v) of Organic Component in the Mobile Phase Equation Obtained by TLC-RP Eluent Content of organic modifier in the mobile phase, % Compound RM0 SD of RM0 Aa SD of A r2 Acetonitrile 40–100 2a 2.320 0.0499 −2.817 0.0526 0.9417 50–100 2b 4.125 0.0607 −4.384 0.0661 0.9920 70–100 2c 5.561 0.4336 −5.648 0.4727 0.8908 60–100 2d 4.875 0.0460 −5.101 0.0533 0.9668 60–100 2e 4.999 0.0967 −5.087 0.0959 0.9889 60–100 2f 4.772 0.1768 −4.761 0.1627 0.9752 30–100 2g 2.616 0.0209 −3.480 0.0405 0.9217 40–100 2h 2.412 0.0535 −3.615 0.0709 0.9461 Methanol 40–100 2a 5.889 0.467 −3.402 −0.405 0.9644 70–100 2b 6.537 0.998 −5.953 −0.878 0.9519 80–100 2c 7.879 1.300 −7.704 −1.183 0.8567 70–100 2d 5.452 0.5535 −5.393 −0.4767 0.8899 80–100 2e 6.864 1.172 −6.783 −1.079 0.9114 80–100 2f 5.452 1.235 −6.386 −1.172 0.9090 40–100 2g 2.729 0.257 −3.402 −0.2054 0.9721 40–100 2h 3.058 0.237 −3.515 −0.083 0.9645 Acetone 60–100 2a 3.812 0.195 −4.587 0.182 0.9217 70–100 2b 5.975 0.250 −6.736 0.277 0.9547 70–100 2c 7.587 0.293 −8.319 0.301 0.9718 70–100 2d 6.099 0.320 −6.816 0.377 0.9515 70–100 2e 7.298 0.403 −8.035 0.438 0.9625 70–100 2f 7.599 0.769 −8.365 0.839 0.9841 60–100 2g 3.590 0.120 −4.420 0.125 0.9247 60–100 2h 4.051 0.198 −5.158 0.184 0.9043 Propan-2-ol 30–100 2a 2.583 0.023 −3.459 0.019 0.9213 60–100 2b 2.922 0.198 −3.301 0.210 0.9389 60–100 2c 4.199 0.3457 −4.547 0.377 0.9195 60–100 2d 3.027 0.125 −3.396 0.120 0.9446 60–100 2e 3.636 0.1167 −3.997 0.134 0.9217 60–100 2f 3.434 0.285 −3.742 0.293 0.9512 30–100 2g 2.146 0.110 −3.156 0.134 0.882 30–100 2h 2.296 0.112 −3.642 0.120 0.8983 1,4-Dioxane 40–100 2a 4.625 0.017 −6.113 0.015 0.9390 70–100 2b 4.921 0.224 −5.712 0.248 0.8698 70–100 2c 7.588 0.767 −8.477 0.8227 0.9733 70–100 2d 5.566 0.367 −6.3642 0.422 0.9190 70–100 2e 6.364 0.144 −7.099 0.200 0.9005 70–100 2f 6.071 0.252 −6.777 0.309 0.8950 40–100 2g 4.041 0.080 −5.650 0.149 0.9355 40–100 2h 3.705 0.175 −5.351 0.194 0.9592 Eluent Content of organic modifier in the mobile phase, % Compound RM0 SD of RM0 Aa SD of A r2 Acetonitrile 40–100 2a 2.320 0.0499 −2.817 0.0526 0.9417 50–100 2b 4.125 0.0607 −4.384 0.0661 0.9920 70–100 2c 5.561 0.4336 −5.648 0.4727 0.8908 60–100 2d 4.875 0.0460 −5.101 0.0533 0.9668 60–100 2e 4.999 0.0967 −5.087 0.0959 0.9889 60–100 2f 4.772 0.1768 −4.761 0.1627 0.9752 30–100 2g 2.616 0.0209 −3.480 0.0405 0.9217 40–100 2h 2.412 0.0535 −3.615 0.0709 0.9461 Methanol 40–100 2a 5.889 0.467 −3.402 −0.405 0.9644 70–100 2b 6.537 0.998 −5.953 −0.878 0.9519 80–100 2c 7.879 1.300 −7.704 −1.183 0.8567 70–100 2d 5.452 0.5535 −5.393 −0.4767 0.8899 80–100 2e 6.864 1.172 −6.783 −1.079 0.9114 80–100 2f 5.452 1.235 −6.386 −1.172 0.9090 40–100 2g 2.729 0.257 −3.402 −0.2054 0.9721 40–100 2h 3.058 0.237 −3.515 −0.083 0.9645 Acetone 60–100 2a 3.812 0.195 −4.587 0.182 0.9217 70–100 2b 5.975 0.250 −6.736 0.277 0.9547 70–100 2c 7.587 0.293 −8.319 0.301 0.9718 70–100 2d 6.099 0.320 −6.816 0.377 0.9515 70–100 2e 7.298 0.403 −8.035 0.438 0.9625 70–100 2f 7.599 0.769 −8.365 0.839 0.9841 60–100 2g 3.590 0.120 −4.420 0.125 0.9247 60–100 2h 4.051 0.198 −5.158 0.184 0.9043 Propan-2-ol 30–100 2a 2.583 0.023 −3.459 0.019 0.9213 60–100 2b 2.922 0.198 −3.301 0.210 0.9389 60–100 2c 4.199 0.3457 −4.547 0.377 0.9195 60–100 2d 3.027 0.125 −3.396 0.120 0.9446 60–100 2e 3.636 0.1167 −3.997 0.134 0.9217 60–100 2f 3.434 0.285 −3.742 0.293 0.9512 30–100 2g 2.146 0.110 −3.156 0.134 0.882 30–100 2h 2.296 0.112 −3.642 0.120 0.8983 1,4-Dioxane 40–100 2a 4.625 0.017 −6.113 0.015 0.9390 70–100 2b 4.921 0.224 −5.712 0.248 0.8698 70–100 2c 7.588 0.767 −8.477 0.8227 0.9733 70–100 2d 5.566 0.367 −6.3642 0.422 0.9190 70–100 2e 6.364 0.144 −7.099 0.200 0.9005 70–100 2f 6.071 0.252 −6.777 0.309 0.8950 40–100 2g 4.041 0.080 −5.650 0.149 0.9355 40–100 2h 3.705 0.175 −5.351 0.194 0.9592 aA is the slope of the linear relationship of Equation (1). Correlation of retention constants and computer calculated logP ACD/logP, HyperChem and Virtual Chemical Calculation Laboratory that automatically generate logP from the structure were applied. The results are given in Table II. Table II. Calculated LogP Value Value 2a 2b 2c 2d 2e 2f 2g 2h Virtual Chemical Calculation Laboratory AlogPs 2.24 3.80 5.04 4.04 4.32 5.18 2.38 2.51 AClogP 3.35 4.07 5.46 4.47 4.88 5.80 2.07 2.31 AlogP 3.31 3.86 5.30 4.24 4.71 5.55 2.41 2.10 MlogP 2.45 2.98 3.73 3.24 3.49 9.97 2.02 2.02 XlogP2 2.17 2.73 4.23 3.19 3.39 4.74 1.92 1.81 XLOGP3 3.44 3.99 5.41 4.42 4.95 5.67 2.84 2.32 HyperChem 8.0.10 logPHyperChem 1.15 1.1 1.55 1.1 1.1 1.25 0.5 0.54 ACD/LogP LogPACD 1.54 2.16 3.79 2.54 3.07 4.14 1.23 2.06 Value 2a 2b 2c 2d 2e 2f 2g 2h Virtual Chemical Calculation Laboratory AlogPs 2.24 3.80 5.04 4.04 4.32 5.18 2.38 2.51 AClogP 3.35 4.07 5.46 4.47 4.88 5.80 2.07 2.31 AlogP 3.31 3.86 5.30 4.24 4.71 5.55 2.41 2.10 MlogP 2.45 2.98 3.73 3.24 3.49 9.97 2.02 2.02 XlogP2 2.17 2.73 4.23 3.19 3.39 4.74 1.92 1.81 XLOGP3 3.44 3.99 5.41 4.42 4.95 5.67 2.84 2.32 HyperChem 8.0.10 logPHyperChem 1.15 1.1 1.55 1.1 1.1 1.25 0.5 0.54 ACD/LogP LogPACD 1.54 2.16 3.79 2.54 3.07 4.14 1.23 2.06 Table II. Calculated LogP Value Value 2a 2b 2c 2d 2e 2f 2g 2h Virtual Chemical Calculation Laboratory AlogPs 2.24 3.80 5.04 4.04 4.32 5.18 2.38 2.51 AClogP 3.35 4.07 5.46 4.47 4.88 5.80 2.07 2.31 AlogP 3.31 3.86 5.30 4.24 4.71 5.55 2.41 2.10 MlogP 2.45 2.98 3.73 3.24 3.49 9.97 2.02 2.02 XlogP2 2.17 2.73 4.23 3.19 3.39 4.74 1.92 1.81 XLOGP3 3.44 3.99 5.41 4.42 4.95 5.67 2.84 2.32 HyperChem 8.0.10 logPHyperChem 1.15 1.1 1.55 1.1 1.1 1.25 0.5 0.54 ACD/LogP LogPACD 1.54 2.16 3.79 2.54 3.07 4.14 1.23 2.06 Value 2a 2b 2c 2d 2e 2f 2g 2h Virtual Chemical Calculation Laboratory AlogPs 2.24 3.80 5.04 4.04 4.32 5.18 2.38 2.51 AClogP 3.35 4.07 5.46 4.47 4.88 5.80 2.07 2.31 AlogP 3.31 3.86 5.30 4.24 4.71 5.55 2.41 2.10 MlogP 2.45 2.98 3.73 3.24 3.49 9.97 2.02 2.02 XlogP2 2.17 2.73 4.23 3.19 3.39 4.74 1.92 1.81 XLOGP3 3.44 3.99 5.41 4.42 4.95 5.67 2.84 2.32 HyperChem 8.0.10 logPHyperChem 1.15 1.1 1.55 1.1 1.1 1.25 0.5 0.54 ACD/LogP LogPACD 1.54 2.16 3.79 2.54 3.07 4.14 1.23 2.06 Rule of five and bioactivity score Analysis of ADME (absorption, distribution, metabolism and elimination) property for compounds has been essential in drug development. The bioactivity and properties of studied compounds were determined by means of online data server Molinspiration (18). The octanol partition coefficient (miLogP), values and other physiochemical properties as MW, the NHBA, the NHBD, NORB, molecular volume (V) and TPSA were calculated. Molecules violating more than one of the Lipinski’s rule can have problems with bioavailability (19). The results are shown in Table IV. Discussion Determination of lipophilicity parameters The well-matched (r2 > 0.85) the linear equations of a relationship between the retention factor (RM) and φ volume fraction (v/v) of an organic component for experimental data for all compounds in organic modifier-water system was obtained (see Table I). The slope A of the regression line (Equation (1)) applied for obtaining RM0 is considered to be related to the specific hydrophobic surface area (20). Regular retention behavior was observed for each solute on TLCRP-18 plates. The RM values of the investigated compounds were decreasing with the increasing fraction volume of organic modifier in the mobile phase since the value A < 0. It was found that the RM0 values obtained from content of organic modifier in the mobile phase shown in Table I. have to be considered to extrapolate of ð‘𝑠values to a water content of 100% in the mobile phase. It has been shown in the literature that the linear correlation is usually established between the intercept RM0 and slope A of Equation (1) (21). The compounds form a congeneric class if linearity exists. The linear relationship for the RM0 and slopes A values was also found in this studied (Table I) with a correlation coefficient >0.8567. This result proves that the investigated 2-thioxo-1,3-thiazolidin-4-one derivatives may be considered as compounds belonging to the same group under the circumstances described. The lines of the dependence of the RM values versus the volume fraction of methanol in the mobile phase (φ) for the 2c and 2e, as well as 2d, 2f and 2b as well as 2a, 2h, 2g were running next to each other since the A values are similar. There are three group of lines of the dependence RM values versus the volume fraction (φ) of acetonitrile (the A values are similar within each group): 1. Group: 2c, 2e, 2d, 2. Group: 2f, 2b and 3. Group 2a, 2h, 2g. When acetone is used as a modifier of the mobile phases there are also three group of dependences: 1. Group: 2c, 2e, 2f, 2. Group: 2d, 2b and 3. Group 2a, 2h, 2g. When 1,4-dioxane is used as modifier of the mobile phases there are two groups of dependencies: 1. Group: 2c, 2e, 2. Group: 2d, 2f, 2b, 2a, 2h, 2g. For propan-2-ol there is only one group of lines. The significant influence of used organic modifiers (methanol, acetonitrile, acetone, propan-2-ol, 1,4-dioxane) on the chromatographic lipophilicity parameters ( RM0) were observed (Table I). The values of RM0 for all studied compounds are lower for propan-2-ol–water chromatographic system. As it is well-known elution strength in RP-TLC varies increase as solvent polarity decreases: propan-2-ol < 1,4-dioxane < acetone < methanol < acetonitrile (22). Studies solvents belong to three different groups of solvents based on the Snyder’s selectivity triangle (23). The methanol and propan-2-ol are in the second group, 1,4-dioxane and acetone are in the fourth group and acetonitrile in the sixth. The proton-donor solubility parameter for methanol is high (acetonitrile does not have proton-donor properties) and the proton-acceptor solubility parameter is also higher for methanol than for acetonitrile (24). Based on obtained results stronger affinity of studies compounds to acetonitrile than to methanol were observed. Propan-2-ol and methanol belong to the same group of Snyder’s selectivity but the polarity index P-value of propan-2-ol is lower than the one of methanol. Stronger affinity of studies compounds to methanol than to propan-2-ol was also observed. Dioxane and acetone belong to the same group of Snyder’s selectivity. Their polarity index are 4.8 i 5.1, respectively. The stronger affinity to acetone are observed for analyzed compounds that there are alkane groups in their molecule (2c, 2e, 2d, 2f, 2b). Correlation of retention constants and computer calculated logP The constants RM0 for RP-TLC and the LogP is supposed to agree (25). Eight values of the theoretically calculated logP have been reflected in this research. The computational LogP values and individual constant RM0 and A value in TLC estimated in different binary systems were correlated. Linear relationships between LogP values and RM0 or A value constants (slope of the linear relationship of the Equation (1)) along with good statistical parameters are shown in Table III. The highest statistical quality was found for the relationships for acetone as a modifier of the mobile phase. Table III. Regression Coefficients (a and b, r2) for the Relationships Between Different Computational LogP Values and RM0 or A (Slope of the Linear Relationship of the Equation (1)), Respectively Computational LogP values Regression coefficients Acetonitrile Methanol Acetone Propan-2-ol 1,4-Dioxane RM0=a⋅LogP+b AlogPs a 1.0556 1.0265 1.4309 0.5336 0.9678 b 0.0660 1.6961 0.4731 1.0621 1.7901 r2 0.9043 0.4605 0.9693 0.8126 0.7812 AClogP a 0.8560 1.0384 1.1870 0.4639 0.8464 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8114 0.6431 0.9103 0.8382 0.8154 AlogP a 0.9315 1.1194 1.2800 0.5064 0.9393 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8099 0.6298 0.8921 0.8418 0.8464 MlogP a 0.2388 0.1488 0.4210 0.1226 0.2210 b 3.0676 4.9263 4.1779 2.5722 4.5341 r2 0.2235 0.0468 0.4054 0.2073 0.1969 XlogP2 a 1.0623 1.0738 1.4932 0.5707 1.0572 b 0.7493 2.2369 1.2380 1.3055 2.1646 r2 0.7551 0.4155 0.8704 0.7665 0.7688 XLOGP3 a 0.9862 1.1426 1.3464 0.5300 0.9895 b −0.1129 0.7638 0.1907 0.8416 1.2734 r2 0.8228 0.5948 0.8948 0.8358 0.8515 logPHyperChem a 2.8017 4.7249 3.7477 1.7338 3.2130 b 1.0567 0.5863 1.8678 1.2338 2.0307 r2 0.5654 0.8660 0.5902 0.7615 0.7643 LogPACD a 1.0592 1.0205 1.5453 0.5912 1.0521 b 1.2418 2.8635 1.7857 1.5133 2.6602 r2 0.6967 0.3483 0.8652 0.7633 0.7066 A=aLogP+b  AlogPs a −0.7486 −1.3538 −1.3716 −0.2425 −0.6494 b −1.6001 −0.3234 −1.4951 −2.7605 −4.0473 r2 0.8299 0.8975 0.9657 0.4110 0.5772  AClogP a −0.5655 −1.1057 −1.1256 −0.2041 −0.5729 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6462 0.8170 0.8877 0.3974 0.6130  AlogP a −0.6102 −1.2014 −1.2079 −0.2202 −0.6464 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6340 0.8129 0.8613 0.3897 0.6576  MlogP a −0.1417 −0.3090 −0.4068 −0.0419 −0.1303 b −3.8320 −4.1623 −5.0341 −3.4985 −5.9560 r2 0.1437 0.2260 0.4105 0.0592 0.1122  XlogP2 a −0.7209 −1.3648 −1.4251 −0.2659 −0.7375 b −2.1826 −1.1921 −2.2472 −2.8514 −4.2137 r2 0.6346 0.7522 0.8596 0.4074 0.6139  XLOGP3 a −0.6491 −1.2634 −1.2693 −0.2287 −0.6824 b −1.6809 −0.0993 −1.3123 −2.7105 −3.6244 r2 0.6505 0.8150 0.8623 0.3811 0.6646  logPHyperChem a −1.7369 −3.7958 −3.4884 −0.8190 −2.3442 b −2.5618 −1.3838 −2.9397 −2.8064 −4.0137 r2 0.3965 0.6263 0.5545 0.4160 0.6676  LogPACD a −0.7586 −1.4045 −1.5025 −0.3239 −0.7472 b −2.4149 −1.7130 −2.6986 −2.8237 −4.5255 r2 0.6521 0.7393 0.8869 0.5612 0.5847 Computational LogP values Regression coefficients Acetonitrile Methanol Acetone Propan-2-ol 1,4-Dioxane RM0=a⋅LogP+b AlogPs a 1.0556 1.0265 1.4309 0.5336 0.9678 b 0.0660 1.6961 0.4731 1.0621 1.7901 r2 0.9043 0.4605 0.9693 0.8126 0.7812 AClogP a 0.8560 1.0384 1.1870 0.4639 0.8464 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8114 0.6431 0.9103 0.8382 0.8154 AlogP a 0.9315 1.1194 1.2800 0.5064 0.9393 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8099 0.6298 0.8921 0.8418 0.8464 MlogP a 0.2388 0.1488 0.4210 0.1226 0.2210 b 3.0676 4.9263 4.1779 2.5722 4.5341 r2 0.2235 0.0468 0.4054 0.2073 0.1969 XlogP2 a 1.0623 1.0738 1.4932 0.5707 1.0572 b 0.7493 2.2369 1.2380 1.3055 2.1646 r2 0.7551 0.4155 0.8704 0.7665 0.7688 XLOGP3 a 0.9862 1.1426 1.3464 0.5300 0.9895 b −0.1129 0.7638 0.1907 0.8416 1.2734 r2 0.8228 0.5948 0.8948 0.8358 0.8515 logPHyperChem a 2.8017 4.7249 3.7477 1.7338 3.2130 b 1.0567 0.5863 1.8678 1.2338 2.0307 r2 0.5654 0.8660 0.5902 0.7615 0.7643 LogPACD a 1.0592 1.0205 1.5453 0.5912 1.0521 b 1.2418 2.8635 1.7857 1.5133 2.6602 r2 0.6967 0.3483 0.8652 0.7633 0.7066 A=aLogP+b  AlogPs a −0.7486 −1.3538 −1.3716 −0.2425 −0.6494 b −1.6001 −0.3234 −1.4951 −2.7605 −4.0473 r2 0.8299 0.8975 0.9657 0.4110 0.5772  AClogP a −0.5655 −1.1057 −1.1256 −0.2041 −0.5729 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6462 0.8170 0.8877 0.3974 0.6130  AlogP a −0.6102 −1.2014 −1.2079 −0.2202 −0.6464 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6340 0.8129 0.8613 0.3897 0.6576  MlogP a −0.1417 −0.3090 −0.4068 −0.0419 −0.1303 b −3.8320 −4.1623 −5.0341 −3.4985 −5.9560 r2 0.1437 0.2260 0.4105 0.0592 0.1122  XlogP2 a −0.7209 −1.3648 −1.4251 −0.2659 −0.7375 b −2.1826 −1.1921 −2.2472 −2.8514 −4.2137 r2 0.6346 0.7522 0.8596 0.4074 0.6139  XLOGP3 a −0.6491 −1.2634 −1.2693 −0.2287 −0.6824 b −1.6809 −0.0993 −1.3123 −2.7105 −3.6244 r2 0.6505 0.8150 0.8623 0.3811 0.6646  logPHyperChem a −1.7369 −3.7958 −3.4884 −0.8190 −2.3442 b −2.5618 −1.3838 −2.9397 −2.8064 −4.0137 r2 0.3965 0.6263 0.5545 0.4160 0.6676  LogPACD a −0.7586 −1.4045 −1.5025 −0.3239 −0.7472 b −2.4149 −1.7130 −2.6986 −2.8237 −4.5255 r2 0.6521 0.7393 0.8869 0.5612 0.5847 Table III. Regression Coefficients (a and b, r2) for the Relationships Between Different Computational LogP Values and RM0 or A (Slope of the Linear Relationship of the Equation (1)), Respectively Computational LogP values Regression coefficients Acetonitrile Methanol Acetone Propan-2-ol 1,4-Dioxane RM0=a⋅LogP+b AlogPs a 1.0556 1.0265 1.4309 0.5336 0.9678 b 0.0660 1.6961 0.4731 1.0621 1.7901 r2 0.9043 0.4605 0.9693 0.8126 0.7812 AClogP a 0.8560 1.0384 1.1870 0.4639 0.8464 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8114 0.6431 0.9103 0.8382 0.8154 AlogP a 0.9315 1.1194 1.2800 0.5064 0.9393 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8099 0.6298 0.8921 0.8418 0.8464 MlogP a 0.2388 0.1488 0.4210 0.1226 0.2210 b 3.0676 4.9263 4.1779 2.5722 4.5341 r2 0.2235 0.0468 0.4054 0.2073 0.1969 XlogP2 a 1.0623 1.0738 1.4932 0.5707 1.0572 b 0.7493 2.2369 1.2380 1.3055 2.1646 r2 0.7551 0.4155 0.8704 0.7665 0.7688 XLOGP3 a 0.9862 1.1426 1.3464 0.5300 0.9895 b −0.1129 0.7638 0.1907 0.8416 1.2734 r2 0.8228 0.5948 0.8948 0.8358 0.8515 logPHyperChem a 2.8017 4.7249 3.7477 1.7338 3.2130 b 1.0567 0.5863 1.8678 1.2338 2.0307 r2 0.5654 0.8660 0.5902 0.7615 0.7643 LogPACD a 1.0592 1.0205 1.5453 0.5912 1.0521 b 1.2418 2.8635 1.7857 1.5133 2.6602 r2 0.6967 0.3483 0.8652 0.7633 0.7066 A=aLogP+b  AlogPs a −0.7486 −1.3538 −1.3716 −0.2425 −0.6494 b −1.6001 −0.3234 −1.4951 −2.7605 −4.0473 r2 0.8299 0.8975 0.9657 0.4110 0.5772  AClogP a −0.5655 −1.1057 −1.1256 −0.2041 −0.5729 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6462 0.8170 0.8877 0.3974 0.6130  AlogP a −0.6102 −1.2014 −1.2079 −0.2202 −0.6464 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6340 0.8129 0.8613 0.3897 0.6576  MlogP a −0.1417 −0.3090 −0.4068 −0.0419 −0.1303 b −3.8320 −4.1623 −5.0341 −3.4985 −5.9560 r2 0.1437 0.2260 0.4105 0.0592 0.1122  XlogP2 a −0.7209 −1.3648 −1.4251 −0.2659 −0.7375 b −2.1826 −1.1921 −2.2472 −2.8514 −4.2137 r2 0.6346 0.7522 0.8596 0.4074 0.6139  XLOGP3 a −0.6491 −1.2634 −1.2693 −0.2287 −0.6824 b −1.6809 −0.0993 −1.3123 −2.7105 −3.6244 r2 0.6505 0.8150 0.8623 0.3811 0.6646  logPHyperChem a −1.7369 −3.7958 −3.4884 −0.8190 −2.3442 b −2.5618 −1.3838 −2.9397 −2.8064 −4.0137 r2 0.3965 0.6263 0.5545 0.4160 0.6676  LogPACD a −0.7586 −1.4045 −1.5025 −0.3239 −0.7472 b −2.4149 −1.7130 −2.6986 −2.8237 −4.5255 r2 0.6521 0.7393 0.8869 0.5612 0.5847 Computational LogP values Regression coefficients Acetonitrile Methanol Acetone Propan-2-ol 1,4-Dioxane RM0=a⋅LogP+b AlogPs a 1.0556 1.0265 1.4309 0.5336 0.9678 b 0.0660 1.6961 0.4731 1.0621 1.7901 r2 0.9043 0.4605 0.9693 0.8126 0.7812 AClogP a 0.8560 1.0384 1.1870 0.4639 0.8464 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8114 0.6431 0.9103 0.8382 0.8154 AlogP a 0.9315 1.1194 1.2800 0.5064 0.9393 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8099 0.6298 0.8921 0.8418 0.8464 MlogP a 0.2388 0.1488 0.4210 0.1226 0.2210 b 3.0676 4.9263 4.1779 2.5722 4.5341 r2 0.2235 0.0468 0.4054 0.2073 0.1969 XlogP2 a 1.0623 1.0738 1.4932 0.5707 1.0572 b 0.7493 2.2369 1.2380 1.3055 2.1646 r2 0.7551 0.4155 0.8704 0.7665 0.7688 XLOGP3 a 0.9862 1.1426 1.3464 0.5300 0.9895 b −0.1129 0.7638 0.1907 0.8416 1.2734 r2 0.8228 0.5948 0.8948 0.8358 0.8515 logPHyperChem a 2.8017 4.7249 3.7477 1.7338 3.2130 b 1.0567 0.5863 1.8678 1.2338 2.0307 r2 0.5654 0.8660 0.5902 0.7615 0.7643 LogPACD a 1.0592 1.0205 1.5453 0.5912 1.0521 b 1.2418 2.8635 1.7857 1.5133 2.6602 r2 0.6967 0.3483 0.8652 0.7633 0.7066 A=aLogP+b  AlogPs a −0.7486 −1.3538 −1.3716 −0.2425 −0.6494 b −1.6001 −0.3234 −1.4951 −2.7605 −4.0473 r2 0.8299 0.8975 0.9657 0.4110 0.5772  AClogP a −0.5655 −1.1057 −1.1256 −0.2041 −0.5729 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6462 0.8170 0.8877 0.3974 0.6130  AlogP a −0.6102 −1.2014 −1.2079 −0.2202 −0.6464 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6340 0.8129 0.8613 0.3897 0.6576  MlogP a −0.1417 −0.3090 −0.4068 −0.0419 −0.1303 b −3.8320 −4.1623 −5.0341 −3.4985 −5.9560 r2 0.1437 0.2260 0.4105 0.0592 0.1122  XlogP2 a −0.7209 −1.3648 −1.4251 −0.2659 −0.7375 b −2.1826 −1.1921 −2.2472 −2.8514 −4.2137 r2 0.6346 0.7522 0.8596 0.4074 0.6139  XLOGP3 a −0.6491 −1.2634 −1.2693 −0.2287 −0.6824 b −1.6809 −0.0993 −1.3123 −2.7105 −3.6244 r2 0.6505 0.8150 0.8623 0.3811 0.6646  logPHyperChem a −1.7369 −3.7958 −3.4884 −0.8190 −2.3442 b −2.5618 −1.3838 −2.9397 −2.8064 −4.0137 r2 0.3965 0.6263 0.5545 0.4160 0.6676  LogPACD a −0.7586 −1.4045 −1.5025 −0.3239 −0.7472 b −2.4149 −1.7130 −2.6986 −2.8237 −4.5255 r2 0.6521 0.7393 0.8869 0.5612 0.5847 Rule of five and bioactivity score The results showed (Table IV) that all tested compounds have zero violations of the rules and suggest the molecules have good bioavailability. LogP values of 2-thioxo-1,3-thiazolidin-4-one derivatives were found to be in the range of 1.841–4.59. It is clear that studied compounds fulfill the rule that calculated octanol/water partition coefficient is <5. Compound 2h is expected to have the highest hydrophilicity because its LogP value is the smallest, whereas compound 2c will be the most lipophilic. This implied that these compounds should have good permeability across the cell membrane. Table IV. In Silico Determination of Physiochemical Properties 2a 2b 2c 2d 2e 2f 2g 2h miLogP 2.58 3.02 4.59 3.39 3.77 4.57 2.24 1.841 TPSA 32.86 22 22 22 22 22 49.93 48.65 MW 247.34 275.4 317.48 289.43 303.45 331.51 231.28 230.29 NOHBA 2 2 2 2 2 2 3 3 NOHBD 1 0 0 0 0 0 1 2 V 205.41 239.16 289.56 255.74 272.54 306.15 196.53 199.69 NORB 2 3 6 3 4 6 2 2 NV 0 0 0 0 0 0 0 0 2a 2b 2c 2d 2e 2f 2g 2h miLogP 2.58 3.02 4.59 3.39 3.77 4.57 2.24 1.841 TPSA 32.86 22 22 22 22 22 49.93 48.65 MW 247.34 275.4 317.48 289.43 303.45 331.51 231.28 230.29 NOHBA 2 2 2 2 2 2 3 3 NOHBD 1 0 0 0 0 0 1 2 V 205.41 239.16 289.56 255.74 272.54 306.15 196.53 199.69 NORB 2 3 6 3 4 6 2 2 NV 0 0 0 0 0 0 0 0 Table IV. In Silico Determination of Physiochemical Properties 2a 2b 2c 2d 2e 2f 2g 2h miLogP 2.58 3.02 4.59 3.39 3.77 4.57 2.24 1.841 TPSA 32.86 22 22 22 22 22 49.93 48.65 MW 247.34 275.4 317.48 289.43 303.45 331.51 231.28 230.29 NOHBA 2 2 2 2 2 2 3 3 NOHBD 1 0 0 0 0 0 1 2 V 205.41 239.16 289.56 255.74 272.54 306.15 196.53 199.69 NORB 2 3 6 3 4 6 2 2 NV 0 0 0 0 0 0 0 0 2a 2b 2c 2d 2e 2f 2g 2h miLogP 2.58 3.02 4.59 3.39 3.77 4.57 2.24 1.841 TPSA 32.86 22 22 22 22 22 49.93 48.65 MW 247.34 275.4 317.48 289.43 303.45 331.51 231.28 230.29 NOHBA 2 2 2 2 2 2 3 3 NOHBD 1 0 0 0 0 0 1 2 V 205.41 239.16 289.56 255.74 272.54 306.15 196.53 199.69 NORB 2 3 6 3 4 6 2 2 NV 0 0 0 0 0 0 0 0 The molecular weights of investigated compounds are <500, hence the molecules are easily transported, diffused as well as absorbed. The number of hydrogen bond donors and acceptors for the studied compounds were determined to below Lipinski’s limit (<5 and 10, respectively) (19). TPSA is a very useful parameter for prediction of intestinal absorption, monolayers permeability and blood–brain barrier penetration. The parameter for the screened compounds are within the range of 22–49.93 and is well much more below the limit (26). Reduced molecular flexibility, as measured by the NORB, was found to be important predictors of good oral bioavailability (24). All the studied compounds were moderate flexible since the NORB are within the range of 2–6 which meets the Veber’s rules. Bioactivity of the tested compounds was examined by calculating the activity score of GPCR ligand, ion channel modulator, nuclear receptor legend, kinase inhibitor, protease inhibitor and enzyme inhibitor. The studies were conducted by means of software Molinspiration drug-likeness score online (www.molinspiration.com). The results are shown in Table V and the bioactivity is within the range of (−2.06)–(−0.19). These values imply that the molecules are moderately active (27). Table V. Bioactivity Score of the Studied Compounds 2a 2b 2c 2d 2e 2f 2g 2h GPCR ligand −1.28 −1.27 −0.86 −1.2 −1.04 −0.81 −1.06 −0.99 Ion channel modulator −1.88 −2.06 −1.69 −1.85 −1.79 −1.61 −1.04 −1.2 Kinase inhibitor −1.12 −1.26 −1 −1.05 −1.09 −0.96 −0.79 −1.19 Nuclear receptor ligand −1.36 −1.28 −0.91 −1.19 −0.96 −0.84 −0.94 −1.23 Protease inhibitor −0.83 −0.93 −0.56 −0.95 −0.66 −0.42 −1 −1.14 Enzyme inhibitor −0.28 −0.36 −0.2 −0.35 −0.29 −0.22 −0.19 −0.52 2a 2b 2c 2d 2e 2f 2g 2h GPCR ligand −1.28 −1.27 −0.86 −1.2 −1.04 −0.81 −1.06 −0.99 Ion channel modulator −1.88 −2.06 −1.69 −1.85 −1.79 −1.61 −1.04 −1.2 Kinase inhibitor −1.12 −1.26 −1 −1.05 −1.09 −0.96 −0.79 −1.19 Nuclear receptor ligand −1.36 −1.28 −0.91 −1.19 −0.96 −0.84 −0.94 −1.23 Protease inhibitor −0.83 −0.93 −0.56 −0.95 −0.66 −0.42 −1 −1.14 Enzyme inhibitor −0.28 −0.36 −0.2 −0.35 −0.29 −0.22 −0.19 −0.52 Table V. Bioactivity Score of the Studied Compounds 2a 2b 2c 2d 2e 2f 2g 2h GPCR ligand −1.28 −1.27 −0.86 −1.2 −1.04 −0.81 −1.06 −0.99 Ion channel modulator −1.88 −2.06 −1.69 −1.85 −1.79 −1.61 −1.04 −1.2 Kinase inhibitor −1.12 −1.26 −1 −1.05 −1.09 −0.96 −0.79 −1.19 Nuclear receptor ligand −1.36 −1.28 −0.91 −1.19 −0.96 −0.84 −0.94 −1.23 Protease inhibitor −0.83 −0.93 −0.56 −0.95 −0.66 −0.42 −1 −1.14 Enzyme inhibitor −0.28 −0.36 −0.2 −0.35 −0.29 −0.22 −0.19 −0.52 2a 2b 2c 2d 2e 2f 2g 2h GPCR ligand −1.28 −1.27 −0.86 −1.2 −1.04 −0.81 −1.06 −0.99 Ion channel modulator −1.88 −2.06 −1.69 −1.85 −1.79 −1.61 −1.04 −1.2 Kinase inhibitor −1.12 −1.26 −1 −1.05 −1.09 −0.96 −0.79 −1.19 Nuclear receptor ligand −1.36 −1.28 −0.91 −1.19 −0.96 −0.84 −0.94 −1.23 Protease inhibitor −0.83 −0.93 −0.56 −0.95 −0.66 −0.42 −1 −1.14 Enzyme inhibitor −0.28 −0.36 −0.2 −0.35 −0.29 −0.22 −0.19 −0.52 Conclusion RP-TLC was successfully applied to evaluate lipophilic properties of some 2-thioxo-1,3-thiazolidin-4-one derivatives and analogs. 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For Permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Chromatographic Science Oxford University Press

Chromatographic and Computational Studies of Molecular Lipophilicity and Drug-likeness for few 2-Thioxo-1,3-Thiazolidin-4-one Derivatives and their Analogs

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Oxford University Press
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© The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
ISSN
0021-9665
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1945-239X
D.O.I.
10.1093/chromsci/bmy046
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Abstract

Abstract Hydrophobicity of the eight 2-thioxo-1,3-thiazolidin-4-one derivatives was determined experimentally by thin-layer chromatography and predicted by means of commercially available programmers. RM values were determined by reversed-phase thin-layer chromatography with using acetonitrile–water, methanol–water, acetone–water, propan-2-ol–water or 1,4-dioxane–water and compared with logP values calculated by using computer programs: HyperChem 8.0.10, Virtual Chemical Calculation Laboratory, ACD/LogP. The drug-likeness has been calculated using Molinspiration. All the heterocycles were found to obey Lipinski’s rule of 5 for an orally active drug. Introduction A very important molecular descriptor that often links well with the bioactivity of chemicals is a lipophilicity (1). The wide-ranging application of lipophilicity to drug design elucidates the requirement for fast procedures to quantify molecular lipophilicity, particularly at the screening level. Octanol–water partition coefficients (logP) is the most common lipophilicity parameter. It can be determined by directly by liquid-liquid extraction method (2) with appropriate analytical methods such as (ultraviolet–visible) UV/Vis spectroscopy (3) or high-performance liquid chromatography (HPLC) (4). The methods are poor reproducibility and time consuming as well as requires high purity of analytes. Reversed-phase (RP)-HPLC (4) or reversed-phase thin-layer chromatography (RP-TLC) (5) techniques are very well-known indirect alternative method in logP evaluation since they have the advantage of the high-throughput and small amount of solutes needed and less strict purity requirement since the impurities are separated during the chromatographic process. These methods characterize relatively simple, rapid, low cost and easy perform. Relying on the nature of the compounds and under appropriate conditions, one to one correlation may be established logP and logkw/RMw values (6). Despite experimental method determination of lipophilicity, various methods for logP computation have been proposed based on the different mathematic algorithms (7, 8). The lipophilicity data obtained experimentally are usually compared with the calculated lipophilicity indices e.g., logPHyperChem, milogP, clogP, ALOGPs, AClogP, AlogP, MLOGP, KOWWIN, XLOGP2 and XLOGP3 (9, 10). The main goal of the studies was to apply RP-TLC to indirect determination lipophilicity descriptor (RMW) of 2-thioxo-1,3-thiazolidin-4-one derivatives (Figure 1) with using acetonitrile–water, methanol–water, acetone–water, propan-2-ol–water or 1,4-dioxane–water mixtures. The second stage was evaluated of other lipophilicity parameters in silico method (AlogPs, AClogP, AlogP, MlogP, XlogP2, XlogP3, logPHyperChem and LogPACD). The next stage was comparison and assessment of all obtained results. The last stage was evaluate of bioactivity by means of online data server Molinspiration. Figure 1. View largeDownload slide Scheme of Knoevenagel condensation of rhodamine. Figure 1. View largeDownload slide Scheme of Knoevenagel condensation of rhodamine. Experimental part Synthesis of model compounds Synthesis of the studied series of 5-cinnamylidenerhodanines (2a–f) and 5-cynamylidine-2-thioimidazolidin-4-one (5-cynamylidene-2-thiohydantoin) (2h) derivatives was carried out by Knoevenagel condensation of rhodanine by means of the corresponding 3-alkylrhodanine and 1-acetyl-2-thio-imidazolidin-4-one (1-acetyl-2-tiohydantoin) with the cinnamic aldehyde (Figure 1). The condensation reaction between the cinnamic aldehyde of rhodanine, and 3-alkylrhodanine was carried out in acetic anhydride by the procedure described previously (11). Condensation of 1-acetyl-2-thio-imidazolidin-4-one with cinnamic aldehyde was carried out in isopropanol in the presence of triethylamine as a catalyst. Under the applied conditions, the reaction is followed by separation of the acetyl group of the N-1 in the ring of 1-acetyl-2-thiohydantoine and condensation of cinnamic aldehyde in C-5 position. 5-Cynnamylidene-2-thiohydantoin was obtained. Cynnamylidene-5-thiazolidine-2,4-dione (2g) was prepared from 5-cynnamylidenorhodanine (2a) subjecting it to hydrolysis in a hydrochloric acid conditions (12). Rhodanine and 3-alkylrhodanine were prepared according to the procedures described previously in order to carry out the necessary condensation. Unsubstituted rhodanine was obtained by the reaction of ammonium thiocyanate with chloroacetic acid according to the method developed by Nencki (13). 3-Alkylrhodanines used in the condensation were obtained with primary aliphatic amines in accordance with the procedure proposed by Holmberg (14). 1-Acetyl-2-thio-imidazolidine-4-one (1-acetyl-2-tiohydantoine) was obtained according to the procedure proposed by Burgess (15). Glycine, acetic anhydride and ammonium thiocyanate were employed in the reaction. The synthesis was carried out in water, heating the reaction mixture to 100°C for 30 min. Evaluation of lipophilicity by RP-TLC Five chromatographic systems were applied to determine RM values with the used of silica gel RP18 F254 plates (Merck, Darmstadt, Germany) as a stationary phase, mobile phase—water and organic modifier (methanol, acetonitrile, acetone, propan-2-ol, 1,4-dioxane) which content varied from 40% to 100% (v/v) in 10% increments. Studied compounds were dissolved in the solvent used as a modifier of mobile phase (2 mg/mL) and 1 μL were applied on the plate with an interval 1 cm between circular spots using micropipette (Brand, Wertheim, Germany). The starting line was 0.5 cm from the lower edge of the plate. The plates were developed over a path of 4 cm in a chamber 5 × 5 cm (Desaga, Sarstedt, Germany) at room temperature, previously equilibrated for 2h. After development, the plates were dried in a gentle stream of air and the spots were visualized in λ = 254 nm UV light by means of a Merck UV lamp. An arithmetic average was calculated from four independent TLC measurements. Calculation of lipophilicity (logP) Three computer softwares: HyperChem 8.0.10 (HyperCube Inc., Gainesville, USA; http://www.hyper.com/), Virtual Chemical Calculation Laboratory (http://www.vcclab.org) and ACD/LogP (Advanced Chemistry Development Inc., Toronto, Kanada; http://www.acdlabs.com/) based on different calculation methods for computing logP have been compared in this studies. Rule of five and bioactivity score The physicochemical parameters including octanol partition coefficients (miLogP), molecular mass (MW), number of hydrogen bonds donors (NHBD), number of hydrogen bond acceptors (NHBA), total polar surface (TPSA), molecular volume (V), number of rotatable bonds (NORB) and number of violation (NV) were calculated. The bioactivity score for studied compounds was assessed with the combination of G protein–coupled receptors (GPCR) ligands, kinase inhibitors, ion channel modulators, enzymes and nuclear receptors. Calculations were accomplished with Molinspiration Software using molinspiration server (http://www.molinspiration.com/cgi-bin/properties). Results Determination of lipophilicity parameters In the relation between the structure and activity, lipophilic character logP appears to be the most important among physicochemical parameter. The aim of the studies is to determine the lipophilicity of eight 2-thioxo-1,3-thiazolidin-4-one derivatives. Lipophilicity parameters RM0 in RP-TLC were established by means of Equation (16): RM=RM0+Aϕ, (1) where RM=log(1Rf−1) (17) and ϕ is the volume fraction of the organic solvent (methanol, acetonitrile, acetone, propan-2-ol, 1,4-dioxane) in the mobile phase. RM0 as an intercept is the extrapolated value corresponding to ϕ as 0% of the volume fraction of the organic solvent. A is the slope of the linear relationship of Equation (1). The obtained data are shown in Table I. Table I. Parameters of the Relationship Between the Retention Factor (RM) and Volume Fraction (v/v) of Organic Component in the Mobile Phase Equation Obtained by TLC-RP Eluent Content of organic modifier in the mobile phase, % Compound RM0 SD of RM0 Aa SD of A r2 Acetonitrile 40–100 2a 2.320 0.0499 −2.817 0.0526 0.9417 50–100 2b 4.125 0.0607 −4.384 0.0661 0.9920 70–100 2c 5.561 0.4336 −5.648 0.4727 0.8908 60–100 2d 4.875 0.0460 −5.101 0.0533 0.9668 60–100 2e 4.999 0.0967 −5.087 0.0959 0.9889 60–100 2f 4.772 0.1768 −4.761 0.1627 0.9752 30–100 2g 2.616 0.0209 −3.480 0.0405 0.9217 40–100 2h 2.412 0.0535 −3.615 0.0709 0.9461 Methanol 40–100 2a 5.889 0.467 −3.402 −0.405 0.9644 70–100 2b 6.537 0.998 −5.953 −0.878 0.9519 80–100 2c 7.879 1.300 −7.704 −1.183 0.8567 70–100 2d 5.452 0.5535 −5.393 −0.4767 0.8899 80–100 2e 6.864 1.172 −6.783 −1.079 0.9114 80–100 2f 5.452 1.235 −6.386 −1.172 0.9090 40–100 2g 2.729 0.257 −3.402 −0.2054 0.9721 40–100 2h 3.058 0.237 −3.515 −0.083 0.9645 Acetone 60–100 2a 3.812 0.195 −4.587 0.182 0.9217 70–100 2b 5.975 0.250 −6.736 0.277 0.9547 70–100 2c 7.587 0.293 −8.319 0.301 0.9718 70–100 2d 6.099 0.320 −6.816 0.377 0.9515 70–100 2e 7.298 0.403 −8.035 0.438 0.9625 70–100 2f 7.599 0.769 −8.365 0.839 0.9841 60–100 2g 3.590 0.120 −4.420 0.125 0.9247 60–100 2h 4.051 0.198 −5.158 0.184 0.9043 Propan-2-ol 30–100 2a 2.583 0.023 −3.459 0.019 0.9213 60–100 2b 2.922 0.198 −3.301 0.210 0.9389 60–100 2c 4.199 0.3457 −4.547 0.377 0.9195 60–100 2d 3.027 0.125 −3.396 0.120 0.9446 60–100 2e 3.636 0.1167 −3.997 0.134 0.9217 60–100 2f 3.434 0.285 −3.742 0.293 0.9512 30–100 2g 2.146 0.110 −3.156 0.134 0.882 30–100 2h 2.296 0.112 −3.642 0.120 0.8983 1,4-Dioxane 40–100 2a 4.625 0.017 −6.113 0.015 0.9390 70–100 2b 4.921 0.224 −5.712 0.248 0.8698 70–100 2c 7.588 0.767 −8.477 0.8227 0.9733 70–100 2d 5.566 0.367 −6.3642 0.422 0.9190 70–100 2e 6.364 0.144 −7.099 0.200 0.9005 70–100 2f 6.071 0.252 −6.777 0.309 0.8950 40–100 2g 4.041 0.080 −5.650 0.149 0.9355 40–100 2h 3.705 0.175 −5.351 0.194 0.9592 Eluent Content of organic modifier in the mobile phase, % Compound RM0 SD of RM0 Aa SD of A r2 Acetonitrile 40–100 2a 2.320 0.0499 −2.817 0.0526 0.9417 50–100 2b 4.125 0.0607 −4.384 0.0661 0.9920 70–100 2c 5.561 0.4336 −5.648 0.4727 0.8908 60–100 2d 4.875 0.0460 −5.101 0.0533 0.9668 60–100 2e 4.999 0.0967 −5.087 0.0959 0.9889 60–100 2f 4.772 0.1768 −4.761 0.1627 0.9752 30–100 2g 2.616 0.0209 −3.480 0.0405 0.9217 40–100 2h 2.412 0.0535 −3.615 0.0709 0.9461 Methanol 40–100 2a 5.889 0.467 −3.402 −0.405 0.9644 70–100 2b 6.537 0.998 −5.953 −0.878 0.9519 80–100 2c 7.879 1.300 −7.704 −1.183 0.8567 70–100 2d 5.452 0.5535 −5.393 −0.4767 0.8899 80–100 2e 6.864 1.172 −6.783 −1.079 0.9114 80–100 2f 5.452 1.235 −6.386 −1.172 0.9090 40–100 2g 2.729 0.257 −3.402 −0.2054 0.9721 40–100 2h 3.058 0.237 −3.515 −0.083 0.9645 Acetone 60–100 2a 3.812 0.195 −4.587 0.182 0.9217 70–100 2b 5.975 0.250 −6.736 0.277 0.9547 70–100 2c 7.587 0.293 −8.319 0.301 0.9718 70–100 2d 6.099 0.320 −6.816 0.377 0.9515 70–100 2e 7.298 0.403 −8.035 0.438 0.9625 70–100 2f 7.599 0.769 −8.365 0.839 0.9841 60–100 2g 3.590 0.120 −4.420 0.125 0.9247 60–100 2h 4.051 0.198 −5.158 0.184 0.9043 Propan-2-ol 30–100 2a 2.583 0.023 −3.459 0.019 0.9213 60–100 2b 2.922 0.198 −3.301 0.210 0.9389 60–100 2c 4.199 0.3457 −4.547 0.377 0.9195 60–100 2d 3.027 0.125 −3.396 0.120 0.9446 60–100 2e 3.636 0.1167 −3.997 0.134 0.9217 60–100 2f 3.434 0.285 −3.742 0.293 0.9512 30–100 2g 2.146 0.110 −3.156 0.134 0.882 30–100 2h 2.296 0.112 −3.642 0.120 0.8983 1,4-Dioxane 40–100 2a 4.625 0.017 −6.113 0.015 0.9390 70–100 2b 4.921 0.224 −5.712 0.248 0.8698 70–100 2c 7.588 0.767 −8.477 0.8227 0.9733 70–100 2d 5.566 0.367 −6.3642 0.422 0.9190 70–100 2e 6.364 0.144 −7.099 0.200 0.9005 70–100 2f 6.071 0.252 −6.777 0.309 0.8950 40–100 2g 4.041 0.080 −5.650 0.149 0.9355 40–100 2h 3.705 0.175 −5.351 0.194 0.9592 aA is the slope of the linear relationship of Equation (1). Table I. Parameters of the Relationship Between the Retention Factor (RM) and Volume Fraction (v/v) of Organic Component in the Mobile Phase Equation Obtained by TLC-RP Eluent Content of organic modifier in the mobile phase, % Compound RM0 SD of RM0 Aa SD of A r2 Acetonitrile 40–100 2a 2.320 0.0499 −2.817 0.0526 0.9417 50–100 2b 4.125 0.0607 −4.384 0.0661 0.9920 70–100 2c 5.561 0.4336 −5.648 0.4727 0.8908 60–100 2d 4.875 0.0460 −5.101 0.0533 0.9668 60–100 2e 4.999 0.0967 −5.087 0.0959 0.9889 60–100 2f 4.772 0.1768 −4.761 0.1627 0.9752 30–100 2g 2.616 0.0209 −3.480 0.0405 0.9217 40–100 2h 2.412 0.0535 −3.615 0.0709 0.9461 Methanol 40–100 2a 5.889 0.467 −3.402 −0.405 0.9644 70–100 2b 6.537 0.998 −5.953 −0.878 0.9519 80–100 2c 7.879 1.300 −7.704 −1.183 0.8567 70–100 2d 5.452 0.5535 −5.393 −0.4767 0.8899 80–100 2e 6.864 1.172 −6.783 −1.079 0.9114 80–100 2f 5.452 1.235 −6.386 −1.172 0.9090 40–100 2g 2.729 0.257 −3.402 −0.2054 0.9721 40–100 2h 3.058 0.237 −3.515 −0.083 0.9645 Acetone 60–100 2a 3.812 0.195 −4.587 0.182 0.9217 70–100 2b 5.975 0.250 −6.736 0.277 0.9547 70–100 2c 7.587 0.293 −8.319 0.301 0.9718 70–100 2d 6.099 0.320 −6.816 0.377 0.9515 70–100 2e 7.298 0.403 −8.035 0.438 0.9625 70–100 2f 7.599 0.769 −8.365 0.839 0.9841 60–100 2g 3.590 0.120 −4.420 0.125 0.9247 60–100 2h 4.051 0.198 −5.158 0.184 0.9043 Propan-2-ol 30–100 2a 2.583 0.023 −3.459 0.019 0.9213 60–100 2b 2.922 0.198 −3.301 0.210 0.9389 60–100 2c 4.199 0.3457 −4.547 0.377 0.9195 60–100 2d 3.027 0.125 −3.396 0.120 0.9446 60–100 2e 3.636 0.1167 −3.997 0.134 0.9217 60–100 2f 3.434 0.285 −3.742 0.293 0.9512 30–100 2g 2.146 0.110 −3.156 0.134 0.882 30–100 2h 2.296 0.112 −3.642 0.120 0.8983 1,4-Dioxane 40–100 2a 4.625 0.017 −6.113 0.015 0.9390 70–100 2b 4.921 0.224 −5.712 0.248 0.8698 70–100 2c 7.588 0.767 −8.477 0.8227 0.9733 70–100 2d 5.566 0.367 −6.3642 0.422 0.9190 70–100 2e 6.364 0.144 −7.099 0.200 0.9005 70–100 2f 6.071 0.252 −6.777 0.309 0.8950 40–100 2g 4.041 0.080 −5.650 0.149 0.9355 40–100 2h 3.705 0.175 −5.351 0.194 0.9592 Eluent Content of organic modifier in the mobile phase, % Compound RM0 SD of RM0 Aa SD of A r2 Acetonitrile 40–100 2a 2.320 0.0499 −2.817 0.0526 0.9417 50–100 2b 4.125 0.0607 −4.384 0.0661 0.9920 70–100 2c 5.561 0.4336 −5.648 0.4727 0.8908 60–100 2d 4.875 0.0460 −5.101 0.0533 0.9668 60–100 2e 4.999 0.0967 −5.087 0.0959 0.9889 60–100 2f 4.772 0.1768 −4.761 0.1627 0.9752 30–100 2g 2.616 0.0209 −3.480 0.0405 0.9217 40–100 2h 2.412 0.0535 −3.615 0.0709 0.9461 Methanol 40–100 2a 5.889 0.467 −3.402 −0.405 0.9644 70–100 2b 6.537 0.998 −5.953 −0.878 0.9519 80–100 2c 7.879 1.300 −7.704 −1.183 0.8567 70–100 2d 5.452 0.5535 −5.393 −0.4767 0.8899 80–100 2e 6.864 1.172 −6.783 −1.079 0.9114 80–100 2f 5.452 1.235 −6.386 −1.172 0.9090 40–100 2g 2.729 0.257 −3.402 −0.2054 0.9721 40–100 2h 3.058 0.237 −3.515 −0.083 0.9645 Acetone 60–100 2a 3.812 0.195 −4.587 0.182 0.9217 70–100 2b 5.975 0.250 −6.736 0.277 0.9547 70–100 2c 7.587 0.293 −8.319 0.301 0.9718 70–100 2d 6.099 0.320 −6.816 0.377 0.9515 70–100 2e 7.298 0.403 −8.035 0.438 0.9625 70–100 2f 7.599 0.769 −8.365 0.839 0.9841 60–100 2g 3.590 0.120 −4.420 0.125 0.9247 60–100 2h 4.051 0.198 −5.158 0.184 0.9043 Propan-2-ol 30–100 2a 2.583 0.023 −3.459 0.019 0.9213 60–100 2b 2.922 0.198 −3.301 0.210 0.9389 60–100 2c 4.199 0.3457 −4.547 0.377 0.9195 60–100 2d 3.027 0.125 −3.396 0.120 0.9446 60–100 2e 3.636 0.1167 −3.997 0.134 0.9217 60–100 2f 3.434 0.285 −3.742 0.293 0.9512 30–100 2g 2.146 0.110 −3.156 0.134 0.882 30–100 2h 2.296 0.112 −3.642 0.120 0.8983 1,4-Dioxane 40–100 2a 4.625 0.017 −6.113 0.015 0.9390 70–100 2b 4.921 0.224 −5.712 0.248 0.8698 70–100 2c 7.588 0.767 −8.477 0.8227 0.9733 70–100 2d 5.566 0.367 −6.3642 0.422 0.9190 70–100 2e 6.364 0.144 −7.099 0.200 0.9005 70–100 2f 6.071 0.252 −6.777 0.309 0.8950 40–100 2g 4.041 0.080 −5.650 0.149 0.9355 40–100 2h 3.705 0.175 −5.351 0.194 0.9592 aA is the slope of the linear relationship of Equation (1). Correlation of retention constants and computer calculated logP ACD/logP, HyperChem and Virtual Chemical Calculation Laboratory that automatically generate logP from the structure were applied. The results are given in Table II. Table II. Calculated LogP Value Value 2a 2b 2c 2d 2e 2f 2g 2h Virtual Chemical Calculation Laboratory AlogPs 2.24 3.80 5.04 4.04 4.32 5.18 2.38 2.51 AClogP 3.35 4.07 5.46 4.47 4.88 5.80 2.07 2.31 AlogP 3.31 3.86 5.30 4.24 4.71 5.55 2.41 2.10 MlogP 2.45 2.98 3.73 3.24 3.49 9.97 2.02 2.02 XlogP2 2.17 2.73 4.23 3.19 3.39 4.74 1.92 1.81 XLOGP3 3.44 3.99 5.41 4.42 4.95 5.67 2.84 2.32 HyperChem 8.0.10 logPHyperChem 1.15 1.1 1.55 1.1 1.1 1.25 0.5 0.54 ACD/LogP LogPACD 1.54 2.16 3.79 2.54 3.07 4.14 1.23 2.06 Value 2a 2b 2c 2d 2e 2f 2g 2h Virtual Chemical Calculation Laboratory AlogPs 2.24 3.80 5.04 4.04 4.32 5.18 2.38 2.51 AClogP 3.35 4.07 5.46 4.47 4.88 5.80 2.07 2.31 AlogP 3.31 3.86 5.30 4.24 4.71 5.55 2.41 2.10 MlogP 2.45 2.98 3.73 3.24 3.49 9.97 2.02 2.02 XlogP2 2.17 2.73 4.23 3.19 3.39 4.74 1.92 1.81 XLOGP3 3.44 3.99 5.41 4.42 4.95 5.67 2.84 2.32 HyperChem 8.0.10 logPHyperChem 1.15 1.1 1.55 1.1 1.1 1.25 0.5 0.54 ACD/LogP LogPACD 1.54 2.16 3.79 2.54 3.07 4.14 1.23 2.06 Table II. Calculated LogP Value Value 2a 2b 2c 2d 2e 2f 2g 2h Virtual Chemical Calculation Laboratory AlogPs 2.24 3.80 5.04 4.04 4.32 5.18 2.38 2.51 AClogP 3.35 4.07 5.46 4.47 4.88 5.80 2.07 2.31 AlogP 3.31 3.86 5.30 4.24 4.71 5.55 2.41 2.10 MlogP 2.45 2.98 3.73 3.24 3.49 9.97 2.02 2.02 XlogP2 2.17 2.73 4.23 3.19 3.39 4.74 1.92 1.81 XLOGP3 3.44 3.99 5.41 4.42 4.95 5.67 2.84 2.32 HyperChem 8.0.10 logPHyperChem 1.15 1.1 1.55 1.1 1.1 1.25 0.5 0.54 ACD/LogP LogPACD 1.54 2.16 3.79 2.54 3.07 4.14 1.23 2.06 Value 2a 2b 2c 2d 2e 2f 2g 2h Virtual Chemical Calculation Laboratory AlogPs 2.24 3.80 5.04 4.04 4.32 5.18 2.38 2.51 AClogP 3.35 4.07 5.46 4.47 4.88 5.80 2.07 2.31 AlogP 3.31 3.86 5.30 4.24 4.71 5.55 2.41 2.10 MlogP 2.45 2.98 3.73 3.24 3.49 9.97 2.02 2.02 XlogP2 2.17 2.73 4.23 3.19 3.39 4.74 1.92 1.81 XLOGP3 3.44 3.99 5.41 4.42 4.95 5.67 2.84 2.32 HyperChem 8.0.10 logPHyperChem 1.15 1.1 1.55 1.1 1.1 1.25 0.5 0.54 ACD/LogP LogPACD 1.54 2.16 3.79 2.54 3.07 4.14 1.23 2.06 Rule of five and bioactivity score Analysis of ADME (absorption, distribution, metabolism and elimination) property for compounds has been essential in drug development. The bioactivity and properties of studied compounds were determined by means of online data server Molinspiration (18). The octanol partition coefficient (miLogP), values and other physiochemical properties as MW, the NHBA, the NHBD, NORB, molecular volume (V) and TPSA were calculated. Molecules violating more than one of the Lipinski’s rule can have problems with bioavailability (19). The results are shown in Table IV. Discussion Determination of lipophilicity parameters The well-matched (r2 > 0.85) the linear equations of a relationship between the retention factor (RM) and φ volume fraction (v/v) of an organic component for experimental data for all compounds in organic modifier-water system was obtained (see Table I). The slope A of the regression line (Equation (1)) applied for obtaining RM0 is considered to be related to the specific hydrophobic surface area (20). Regular retention behavior was observed for each solute on TLCRP-18 plates. The RM values of the investigated compounds were decreasing with the increasing fraction volume of organic modifier in the mobile phase since the value A < 0. It was found that the RM0 values obtained from content of organic modifier in the mobile phase shown in Table I. have to be considered to extrapolate of ð‘𝑠values to a water content of 100% in the mobile phase. It has been shown in the literature that the linear correlation is usually established between the intercept RM0 and slope A of Equation (1) (21). The compounds form a congeneric class if linearity exists. The linear relationship for the RM0 and slopes A values was also found in this studied (Table I) with a correlation coefficient >0.8567. This result proves that the investigated 2-thioxo-1,3-thiazolidin-4-one derivatives may be considered as compounds belonging to the same group under the circumstances described. The lines of the dependence of the RM values versus the volume fraction of methanol in the mobile phase (φ) for the 2c and 2e, as well as 2d, 2f and 2b as well as 2a, 2h, 2g were running next to each other since the A values are similar. There are three group of lines of the dependence RM values versus the volume fraction (φ) of acetonitrile (the A values are similar within each group): 1. Group: 2c, 2e, 2d, 2. Group: 2f, 2b and 3. Group 2a, 2h, 2g. When acetone is used as a modifier of the mobile phases there are also three group of dependences: 1. Group: 2c, 2e, 2f, 2. Group: 2d, 2b and 3. Group 2a, 2h, 2g. When 1,4-dioxane is used as modifier of the mobile phases there are two groups of dependencies: 1. Group: 2c, 2e, 2. Group: 2d, 2f, 2b, 2a, 2h, 2g. For propan-2-ol there is only one group of lines. The significant influence of used organic modifiers (methanol, acetonitrile, acetone, propan-2-ol, 1,4-dioxane) on the chromatographic lipophilicity parameters ( RM0) were observed (Table I). The values of RM0 for all studied compounds are lower for propan-2-ol–water chromatographic system. As it is well-known elution strength in RP-TLC varies increase as solvent polarity decreases: propan-2-ol < 1,4-dioxane < acetone < methanol < acetonitrile (22). Studies solvents belong to three different groups of solvents based on the Snyder’s selectivity triangle (23). The methanol and propan-2-ol are in the second group, 1,4-dioxane and acetone are in the fourth group and acetonitrile in the sixth. The proton-donor solubility parameter for methanol is high (acetonitrile does not have proton-donor properties) and the proton-acceptor solubility parameter is also higher for methanol than for acetonitrile (24). Based on obtained results stronger affinity of studies compounds to acetonitrile than to methanol were observed. Propan-2-ol and methanol belong to the same group of Snyder’s selectivity but the polarity index P-value of propan-2-ol is lower than the one of methanol. Stronger affinity of studies compounds to methanol than to propan-2-ol was also observed. Dioxane and acetone belong to the same group of Snyder’s selectivity. Their polarity index are 4.8 i 5.1, respectively. The stronger affinity to acetone are observed for analyzed compounds that there are alkane groups in their molecule (2c, 2e, 2d, 2f, 2b). Correlation of retention constants and computer calculated logP The constants RM0 for RP-TLC and the LogP is supposed to agree (25). Eight values of the theoretically calculated logP have been reflected in this research. The computational LogP values and individual constant RM0 and A value in TLC estimated in different binary systems were correlated. Linear relationships between LogP values and RM0 or A value constants (slope of the linear relationship of the Equation (1)) along with good statistical parameters are shown in Table III. The highest statistical quality was found for the relationships for acetone as a modifier of the mobile phase. Table III. Regression Coefficients (a and b, r2) for the Relationships Between Different Computational LogP Values and RM0 or A (Slope of the Linear Relationship of the Equation (1)), Respectively Computational LogP values Regression coefficients Acetonitrile Methanol Acetone Propan-2-ol 1,4-Dioxane RM0=a⋅LogP+b AlogPs a 1.0556 1.0265 1.4309 0.5336 0.9678 b 0.0660 1.6961 0.4731 1.0621 1.7901 r2 0.9043 0.4605 0.9693 0.8126 0.7812 AClogP a 0.8560 1.0384 1.1870 0.4639 0.8464 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8114 0.6431 0.9103 0.8382 0.8154 AlogP a 0.9315 1.1194 1.2800 0.5064 0.9393 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8099 0.6298 0.8921 0.8418 0.8464 MlogP a 0.2388 0.1488 0.4210 0.1226 0.2210 b 3.0676 4.9263 4.1779 2.5722 4.5341 r2 0.2235 0.0468 0.4054 0.2073 0.1969 XlogP2 a 1.0623 1.0738 1.4932 0.5707 1.0572 b 0.7493 2.2369 1.2380 1.3055 2.1646 r2 0.7551 0.4155 0.8704 0.7665 0.7688 XLOGP3 a 0.9862 1.1426 1.3464 0.5300 0.9895 b −0.1129 0.7638 0.1907 0.8416 1.2734 r2 0.8228 0.5948 0.8948 0.8358 0.8515 logPHyperChem a 2.8017 4.7249 3.7477 1.7338 3.2130 b 1.0567 0.5863 1.8678 1.2338 2.0307 r2 0.5654 0.8660 0.5902 0.7615 0.7643 LogPACD a 1.0592 1.0205 1.5453 0.5912 1.0521 b 1.2418 2.8635 1.7857 1.5133 2.6602 r2 0.6967 0.3483 0.8652 0.7633 0.7066 A=aLogP+b  AlogPs a −0.7486 −1.3538 −1.3716 −0.2425 −0.6494 b −1.6001 −0.3234 −1.4951 −2.7605 −4.0473 r2 0.8299 0.8975 0.9657 0.4110 0.5772  AClogP a −0.5655 −1.1057 −1.1256 −0.2041 −0.5729 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6462 0.8170 0.8877 0.3974 0.6130  AlogP a −0.6102 −1.2014 −1.2079 −0.2202 −0.6464 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6340 0.8129 0.8613 0.3897 0.6576  MlogP a −0.1417 −0.3090 −0.4068 −0.0419 −0.1303 b −3.8320 −4.1623 −5.0341 −3.4985 −5.9560 r2 0.1437 0.2260 0.4105 0.0592 0.1122  XlogP2 a −0.7209 −1.3648 −1.4251 −0.2659 −0.7375 b −2.1826 −1.1921 −2.2472 −2.8514 −4.2137 r2 0.6346 0.7522 0.8596 0.4074 0.6139  XLOGP3 a −0.6491 −1.2634 −1.2693 −0.2287 −0.6824 b −1.6809 −0.0993 −1.3123 −2.7105 −3.6244 r2 0.6505 0.8150 0.8623 0.3811 0.6646  logPHyperChem a −1.7369 −3.7958 −3.4884 −0.8190 −2.3442 b −2.5618 −1.3838 −2.9397 −2.8064 −4.0137 r2 0.3965 0.6263 0.5545 0.4160 0.6676  LogPACD a −0.7586 −1.4045 −1.5025 −0.3239 −0.7472 b −2.4149 −1.7130 −2.6986 −2.8237 −4.5255 r2 0.6521 0.7393 0.8869 0.5612 0.5847 Computational LogP values Regression coefficients Acetonitrile Methanol Acetone Propan-2-ol 1,4-Dioxane RM0=a⋅LogP+b AlogPs a 1.0556 1.0265 1.4309 0.5336 0.9678 b 0.0660 1.6961 0.4731 1.0621 1.7901 r2 0.9043 0.4605 0.9693 0.8126 0.7812 AClogP a 0.8560 1.0384 1.1870 0.4639 0.8464 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8114 0.6431 0.9103 0.8382 0.8154 AlogP a 0.9315 1.1194 1.2800 0.5064 0.9393 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8099 0.6298 0.8921 0.8418 0.8464 MlogP a 0.2388 0.1488 0.4210 0.1226 0.2210 b 3.0676 4.9263 4.1779 2.5722 4.5341 r2 0.2235 0.0468 0.4054 0.2073 0.1969 XlogP2 a 1.0623 1.0738 1.4932 0.5707 1.0572 b 0.7493 2.2369 1.2380 1.3055 2.1646 r2 0.7551 0.4155 0.8704 0.7665 0.7688 XLOGP3 a 0.9862 1.1426 1.3464 0.5300 0.9895 b −0.1129 0.7638 0.1907 0.8416 1.2734 r2 0.8228 0.5948 0.8948 0.8358 0.8515 logPHyperChem a 2.8017 4.7249 3.7477 1.7338 3.2130 b 1.0567 0.5863 1.8678 1.2338 2.0307 r2 0.5654 0.8660 0.5902 0.7615 0.7643 LogPACD a 1.0592 1.0205 1.5453 0.5912 1.0521 b 1.2418 2.8635 1.7857 1.5133 2.6602 r2 0.6967 0.3483 0.8652 0.7633 0.7066 A=aLogP+b  AlogPs a −0.7486 −1.3538 −1.3716 −0.2425 −0.6494 b −1.6001 −0.3234 −1.4951 −2.7605 −4.0473 r2 0.8299 0.8975 0.9657 0.4110 0.5772  AClogP a −0.5655 −1.1057 −1.1256 −0.2041 −0.5729 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6462 0.8170 0.8877 0.3974 0.6130  AlogP a −0.6102 −1.2014 −1.2079 −0.2202 −0.6464 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6340 0.8129 0.8613 0.3897 0.6576  MlogP a −0.1417 −0.3090 −0.4068 −0.0419 −0.1303 b −3.8320 −4.1623 −5.0341 −3.4985 −5.9560 r2 0.1437 0.2260 0.4105 0.0592 0.1122  XlogP2 a −0.7209 −1.3648 −1.4251 −0.2659 −0.7375 b −2.1826 −1.1921 −2.2472 −2.8514 −4.2137 r2 0.6346 0.7522 0.8596 0.4074 0.6139  XLOGP3 a −0.6491 −1.2634 −1.2693 −0.2287 −0.6824 b −1.6809 −0.0993 −1.3123 −2.7105 −3.6244 r2 0.6505 0.8150 0.8623 0.3811 0.6646  logPHyperChem a −1.7369 −3.7958 −3.4884 −0.8190 −2.3442 b −2.5618 −1.3838 −2.9397 −2.8064 −4.0137 r2 0.3965 0.6263 0.5545 0.4160 0.6676  LogPACD a −0.7586 −1.4045 −1.5025 −0.3239 −0.7472 b −2.4149 −1.7130 −2.6986 −2.8237 −4.5255 r2 0.6521 0.7393 0.8869 0.5612 0.5847 Table III. Regression Coefficients (a and b, r2) for the Relationships Between Different Computational LogP Values and RM0 or A (Slope of the Linear Relationship of the Equation (1)), Respectively Computational LogP values Regression coefficients Acetonitrile Methanol Acetone Propan-2-ol 1,4-Dioxane RM0=a⋅LogP+b AlogPs a 1.0556 1.0265 1.4309 0.5336 0.9678 b 0.0660 1.6961 0.4731 1.0621 1.7901 r2 0.9043 0.4605 0.9693 0.8126 0.7812 AClogP a 0.8560 1.0384 1.1870 0.4639 0.8464 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8114 0.6431 0.9103 0.8382 0.8154 AlogP a 0.9315 1.1194 1.2800 0.5064 0.9393 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8099 0.6298 0.8921 0.8418 0.8464 MlogP a 0.2388 0.1488 0.4210 0.1226 0.2210 b 3.0676 4.9263 4.1779 2.5722 4.5341 r2 0.2235 0.0468 0.4054 0.2073 0.1969 XlogP2 a 1.0623 1.0738 1.4932 0.5707 1.0572 b 0.7493 2.2369 1.2380 1.3055 2.1646 r2 0.7551 0.4155 0.8704 0.7665 0.7688 XLOGP3 a 0.9862 1.1426 1.3464 0.5300 0.9895 b −0.1129 0.7638 0.1907 0.8416 1.2734 r2 0.8228 0.5948 0.8948 0.8358 0.8515 logPHyperChem a 2.8017 4.7249 3.7477 1.7338 3.2130 b 1.0567 0.5863 1.8678 1.2338 2.0307 r2 0.5654 0.8660 0.5902 0.7615 0.7643 LogPACD a 1.0592 1.0205 1.5453 0.5912 1.0521 b 1.2418 2.8635 1.7857 1.5133 2.6602 r2 0.6967 0.3483 0.8652 0.7633 0.7066 A=aLogP+b  AlogPs a −0.7486 −1.3538 −1.3716 −0.2425 −0.6494 b −1.6001 −0.3234 −1.4951 −2.7605 −4.0473 r2 0.8299 0.8975 0.9657 0.4110 0.5772  AClogP a −0.5655 −1.1057 −1.1256 −0.2041 −0.5729 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6462 0.8170 0.8877 0.3974 0.6130  AlogP a −0.6102 −1.2014 −1.2079 −0.2202 −0.6464 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6340 0.8129 0.8613 0.3897 0.6576  MlogP a −0.1417 −0.3090 −0.4068 −0.0419 −0.1303 b −3.8320 −4.1623 −5.0341 −3.4985 −5.9560 r2 0.1437 0.2260 0.4105 0.0592 0.1122  XlogP2 a −0.7209 −1.3648 −1.4251 −0.2659 −0.7375 b −2.1826 −1.1921 −2.2472 −2.8514 −4.2137 r2 0.6346 0.7522 0.8596 0.4074 0.6139  XLOGP3 a −0.6491 −1.2634 −1.2693 −0.2287 −0.6824 b −1.6809 −0.0993 −1.3123 −2.7105 −3.6244 r2 0.6505 0.8150 0.8623 0.3811 0.6646  logPHyperChem a −1.7369 −3.7958 −3.4884 −0.8190 −2.3442 b −2.5618 −1.3838 −2.9397 −2.8064 −4.0137 r2 0.3965 0.6263 0.5545 0.4160 0.6676  LogPACD a −0.7586 −1.4045 −1.5025 −0.3239 −0.7472 b −2.4149 −1.7130 −2.6986 −2.8237 −4.5255 r2 0.6521 0.7393 0.8869 0.5612 0.5847 Computational LogP values Regression coefficients Acetonitrile Methanol Acetone Propan-2-ol 1,4-Dioxane RM0=a⋅LogP+b AlogPs a 1.0556 1.0265 1.4309 0.5336 0.9678 b 0.0660 1.6961 0.4731 1.0621 1.7901 r2 0.9043 0.4605 0.9693 0.8126 0.7812 AClogP a 0.8560 1.0384 1.1870 0.4639 0.8464 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8114 0.6431 0.9103 0.8382 0.8154 AlogP a 0.9315 1.1194 1.2800 0.5064 0.9393 b 0.4922 1.2758 0.9426 1.1509 1.9313 r2 0.8099 0.6298 0.8921 0.8418 0.8464 MlogP a 0.2388 0.1488 0.4210 0.1226 0.2210 b 3.0676 4.9263 4.1779 2.5722 4.5341 r2 0.2235 0.0468 0.4054 0.2073 0.1969 XlogP2 a 1.0623 1.0738 1.4932 0.5707 1.0572 b 0.7493 2.2369 1.2380 1.3055 2.1646 r2 0.7551 0.4155 0.8704 0.7665 0.7688 XLOGP3 a 0.9862 1.1426 1.3464 0.5300 0.9895 b −0.1129 0.7638 0.1907 0.8416 1.2734 r2 0.8228 0.5948 0.8948 0.8358 0.8515 logPHyperChem a 2.8017 4.7249 3.7477 1.7338 3.2130 b 1.0567 0.5863 1.8678 1.2338 2.0307 r2 0.5654 0.8660 0.5902 0.7615 0.7643 LogPACD a 1.0592 1.0205 1.5453 0.5912 1.0521 b 1.2418 2.8635 1.7857 1.5133 2.6602 r2 0.6967 0.3483 0.8652 0.7633 0.7066 A=aLogP+b  AlogPs a −0.7486 −1.3538 −1.3716 −0.2425 −0.6494 b −1.6001 −0.3234 −1.4951 −2.7605 −4.0473 r2 0.8299 0.8975 0.9657 0.4110 0.5772  AClogP a −0.5655 −1.1057 −1.1256 −0.2041 −0.5729 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6462 0.8170 0.8877 0.3974 0.6130  AlogP a −0.6102 −1.2014 −1.2079 −0.2202 −0.6464 b −2.0707 −0.8379 −1.9943 −2.8281 −4.1220 r2 0.6340 0.8129 0.8613 0.3897 0.6576  MlogP a −0.1417 −0.3090 −0.4068 −0.0419 −0.1303 b −3.8320 −4.1623 −5.0341 −3.4985 −5.9560 r2 0.1437 0.2260 0.4105 0.0592 0.1122  XlogP2 a −0.7209 −1.3648 −1.4251 −0.2659 −0.7375 b −2.1826 −1.1921 −2.2472 −2.8514 −4.2137 r2 0.6346 0.7522 0.8596 0.4074 0.6139  XLOGP3 a −0.6491 −1.2634 −1.2693 −0.2287 −0.6824 b −1.6809 −0.0993 −1.3123 −2.7105 −3.6244 r2 0.6505 0.8150 0.8623 0.3811 0.6646  logPHyperChem a −1.7369 −3.7958 −3.4884 −0.8190 −2.3442 b −2.5618 −1.3838 −2.9397 −2.8064 −4.0137 r2 0.3965 0.6263 0.5545 0.4160 0.6676  LogPACD a −0.7586 −1.4045 −1.5025 −0.3239 −0.7472 b −2.4149 −1.7130 −2.6986 −2.8237 −4.5255 r2 0.6521 0.7393 0.8869 0.5612 0.5847 Rule of five and bioactivity score The results showed (Table IV) that all tested compounds have zero violations of the rules and suggest the molecules have good bioavailability. LogP values of 2-thioxo-1,3-thiazolidin-4-one derivatives were found to be in the range of 1.841–4.59. It is clear that studied compounds fulfill the rule that calculated octanol/water partition coefficient is <5. Compound 2h is expected to have the highest hydrophilicity because its LogP value is the smallest, whereas compound 2c will be the most lipophilic. This implied that these compounds should have good permeability across the cell membrane. Table IV. In Silico Determination of Physiochemical Properties 2a 2b 2c 2d 2e 2f 2g 2h miLogP 2.58 3.02 4.59 3.39 3.77 4.57 2.24 1.841 TPSA 32.86 22 22 22 22 22 49.93 48.65 MW 247.34 275.4 317.48 289.43 303.45 331.51 231.28 230.29 NOHBA 2 2 2 2 2 2 3 3 NOHBD 1 0 0 0 0 0 1 2 V 205.41 239.16 289.56 255.74 272.54 306.15 196.53 199.69 NORB 2 3 6 3 4 6 2 2 NV 0 0 0 0 0 0 0 0 2a 2b 2c 2d 2e 2f 2g 2h miLogP 2.58 3.02 4.59 3.39 3.77 4.57 2.24 1.841 TPSA 32.86 22 22 22 22 22 49.93 48.65 MW 247.34 275.4 317.48 289.43 303.45 331.51 231.28 230.29 NOHBA 2 2 2 2 2 2 3 3 NOHBD 1 0 0 0 0 0 1 2 V 205.41 239.16 289.56 255.74 272.54 306.15 196.53 199.69 NORB 2 3 6 3 4 6 2 2 NV 0 0 0 0 0 0 0 0 Table IV. In Silico Determination of Physiochemical Properties 2a 2b 2c 2d 2e 2f 2g 2h miLogP 2.58 3.02 4.59 3.39 3.77 4.57 2.24 1.841 TPSA 32.86 22 22 22 22 22 49.93 48.65 MW 247.34 275.4 317.48 289.43 303.45 331.51 231.28 230.29 NOHBA 2 2 2 2 2 2 3 3 NOHBD 1 0 0 0 0 0 1 2 V 205.41 239.16 289.56 255.74 272.54 306.15 196.53 199.69 NORB 2 3 6 3 4 6 2 2 NV 0 0 0 0 0 0 0 0 2a 2b 2c 2d 2e 2f 2g 2h miLogP 2.58 3.02 4.59 3.39 3.77 4.57 2.24 1.841 TPSA 32.86 22 22 22 22 22 49.93 48.65 MW 247.34 275.4 317.48 289.43 303.45 331.51 231.28 230.29 NOHBA 2 2 2 2 2 2 3 3 NOHBD 1 0 0 0 0 0 1 2 V 205.41 239.16 289.56 255.74 272.54 306.15 196.53 199.69 NORB 2 3 6 3 4 6 2 2 NV 0 0 0 0 0 0 0 0 The molecular weights of investigated compounds are <500, hence the molecules are easily transported, diffused as well as absorbed. The number of hydrogen bond donors and acceptors for the studied compounds were determined to below Lipinski’s limit (<5 and 10, respectively) (19). TPSA is a very useful parameter for prediction of intestinal absorption, monolayers permeability and blood–brain barrier penetration. The parameter for the screened compounds are within the range of 22–49.93 and is well much more below the limit (26). Reduced molecular flexibility, as measured by the NORB, was found to be important predictors of good oral bioavailability (24). All the studied compounds were moderate flexible since the NORB are within the range of 2–6 which meets the Veber’s rules. Bioactivity of the tested compounds was examined by calculating the activity score of GPCR ligand, ion channel modulator, nuclear receptor legend, kinase inhibitor, protease inhibitor and enzyme inhibitor. The studies were conducted by means of software Molinspiration drug-likeness score online (www.molinspiration.com). The results are shown in Table V and the bioactivity is within the range of (−2.06)–(−0.19). These values imply that the molecules are moderately active (27). Table V. Bioactivity Score of the Studied Compounds 2a 2b 2c 2d 2e 2f 2g 2h GPCR ligand −1.28 −1.27 −0.86 −1.2 −1.04 −0.81 −1.06 −0.99 Ion channel modulator −1.88 −2.06 −1.69 −1.85 −1.79 −1.61 −1.04 −1.2 Kinase inhibitor −1.12 −1.26 −1 −1.05 −1.09 −0.96 −0.79 −1.19 Nuclear receptor ligand −1.36 −1.28 −0.91 −1.19 −0.96 −0.84 −0.94 −1.23 Protease inhibitor −0.83 −0.93 −0.56 −0.95 −0.66 −0.42 −1 −1.14 Enzyme inhibitor −0.28 −0.36 −0.2 −0.35 −0.29 −0.22 −0.19 −0.52 2a 2b 2c 2d 2e 2f 2g 2h GPCR ligand −1.28 −1.27 −0.86 −1.2 −1.04 −0.81 −1.06 −0.99 Ion channel modulator −1.88 −2.06 −1.69 −1.85 −1.79 −1.61 −1.04 −1.2 Kinase inhibitor −1.12 −1.26 −1 −1.05 −1.09 −0.96 −0.79 −1.19 Nuclear receptor ligand −1.36 −1.28 −0.91 −1.19 −0.96 −0.84 −0.94 −1.23 Protease inhibitor −0.83 −0.93 −0.56 −0.95 −0.66 −0.42 −1 −1.14 Enzyme inhibitor −0.28 −0.36 −0.2 −0.35 −0.29 −0.22 −0.19 −0.52 Table V. Bioactivity Score of the Studied Compounds 2a 2b 2c 2d 2e 2f 2g 2h GPCR ligand −1.28 −1.27 −0.86 −1.2 −1.04 −0.81 −1.06 −0.99 Ion channel modulator −1.88 −2.06 −1.69 −1.85 −1.79 −1.61 −1.04 −1.2 Kinase inhibitor −1.12 −1.26 −1 −1.05 −1.09 −0.96 −0.79 −1.19 Nuclear receptor ligand −1.36 −1.28 −0.91 −1.19 −0.96 −0.84 −0.94 −1.23 Protease inhibitor −0.83 −0.93 −0.56 −0.95 −0.66 −0.42 −1 −1.14 Enzyme inhibitor −0.28 −0.36 −0.2 −0.35 −0.29 −0.22 −0.19 −0.52 2a 2b 2c 2d 2e 2f 2g 2h GPCR ligand −1.28 −1.27 −0.86 −1.2 −1.04 −0.81 −1.06 −0.99 Ion channel modulator −1.88 −2.06 −1.69 −1.85 −1.79 −1.61 −1.04 −1.2 Kinase inhibitor −1.12 −1.26 −1 −1.05 −1.09 −0.96 −0.79 −1.19 Nuclear receptor ligand −1.36 −1.28 −0.91 −1.19 −0.96 −0.84 −0.94 −1.23 Protease inhibitor −0.83 −0.93 −0.56 −0.95 −0.66 −0.42 −1 −1.14 Enzyme inhibitor −0.28 −0.36 −0.2 −0.35 −0.29 −0.22 −0.19 −0.52 Conclusion RP-TLC was successfully applied to evaluate lipophilic properties of some 2-thioxo-1,3-thiazolidin-4-one derivatives and analogs. 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Journal of Chromatographic ScienceOxford University Press

Published: Sep 1, 2018

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