In this study, 14 cytidine esters were modified with different aliphatic and aromatic chains (2–15) (Table 1) and were geometrically optimized to realize the modes of their antimicrobial behavior. Initially, partial acylated derivatives were selected for antiviral activities using the online web tool. Subsequently, the observed activities were rationalized by measuring the IR frequency, physicochemical properties, molecular docking, in silico pharmacokinetics, and drug-likeness properties. In nucleoside chemistry, the selective alteration of certain hydroxyl groups is important because the resulting acylation products might be useful precursors for the synthesis of new, bioactive products. Moreover, the designed acyl derivatives might exhibit a high antiviral efficacy as versatile intermediates for synthesizing various other antiviral drugs of fundamental importance.
3.1 Structural Identification of the Designed Cytidine Derivatives
Table 1 and Fig. 3 present the atomic identification and structural variations of the substituted cytidine derivatives. Different aliphatic (pivaloyl, hexanoyl, octanoyl, decanoyl, laouroyl palmitoyl, myristoyl, and steroyl) and aromatic (4-chlorobenzoyl, cinnamoyl, 4-tert-butylbenzoyl, and trityl) groups were subjected to the hydroxyl (–OH) group modification of cytidine for investigating the variations in biological activities.
Table 1
Structural views of the cytidine derivatives with SMILES
Compounds | Molecular formula | Molecular weight | Compounds name | SMILES |
1 | C9H13N3O5 | 242.22 | Cytidine | NC1 = NC(= O)N(C = C1)C1OC(CO)C(O)C1O |
2 | C19H31N3O6 | 397.47 | 5´-O-Decanoylcytidine | CCCCCCCCCC(= O)OCC1OC(C(O)C1O)N1C = CC(N) = NC1 = O |
3 | C35H59N3O8 | 649.87 | 5´-O-Decanoyl-2´,3´-di-O-octanoylcytidine | CCCCCCCCCC(= O)OCC1OC(C(OC(= O)CCCCCCC)C1OC(= O)CCCCCCC)N1C = CC(N) = NC1 = O |
4 | C51H91N3O8 | 874.30 | 5´-O-Decanoyl-2´,3´-di-O-palmitoylcytidine | CCCCCCCCCCCCCCCC(= O)OC1C(COC(= O)CCCCCCCCC)OC(C1OC(= O)CCCCCCCCCCCCCCC)N1C = CC(N) = NC1 = O |
5 | C55H99N3O8 | 929.86 | 5´-O-Decanoyl-2´,3´-di-O-stearoylcytidine | CCCCCCCCCCCCCCCCCC(= O)OC1C(COC(= O)CCCCCCCCC)OC(C1OC(= O)CCCCCCCCCCCCCCCCC)N1C = CC(N) = NC1 = O |
6 | C57H59N3O6 | 882.11 | 5´-O-Decanoyl-2´,3´-di-O-(triphenylmethyl)cytidine | CCCCCCCCCC(= O)OCC1OC(C(OC(C2 = CC = CC = C2)(C2 = CC = CC = C2)C2 = CC = CC = C2)C1OC(C1 = CC = CC = C1)(C1 = CC = CC = C1)C1 = CC = CC = C1)N1C = CC(N) = NC1 = O |
7 | C41H55N3O8 | 717.90 | 5´-O-Decanoyl-2´,3´-(4-tert-butylbenzoyl)cytidine | CCCCCCCCCC(= O)OCC1OC(C(OC(= O)C2 = CC = C(C = C2)C(C)(C)C)C1OC(= O)C1 = CC = C(C = C1)C(C)(C)C)N1C = CC(N) = NC1 = O |
8 | C28H27N3O5 | 485.54 | 5´-O-(Triphenylmethyl)cytidine | NC1 = NC(= O)N(C = C1)C1OC(COC(C2 = CC = CC = C2)(C2 = CC = CC = C2)C2 = CC = CC = C2)C(O)C1O |
9 | C40H47N3O7 | 681.83 | 2´,3´-Di-O-hexanoyl-5´-O-(triphenylmethyl)cytidine | CCCCCC(= O)OC1C(COC(C2 = CC = CC = C2)(C2 = CC = CC = C2)C2 = CC = CC = C2)OC(C1OC(= O)CCCCC)N1C = CC(N) = NC1 = O |
10 | C42H53N3O7 | 709.87 | 2´, 3´-Di-O-heptanoyl-5´-O-(triphenylmethyl)cytidine | CCCCCCC(= O)OC1C(COC(C2 = CC = CC = C2)(C2 = CC = CC = C2)C2 = CC = CC = C2)OC(C1OC(= O)CCCCCC)N1C = CC(N) = NC1 = O |
11 | C52H71N3O7 | 850.15 | 2´,3´-Di-O-lauroyl-5´-O-(triphenylmethyl)cytidine | CCCCCCCCCCCC(= O)OC1C(COC(C2 = CC = CC = C2)(C2 = CC = CC = C2)C2 = CC = CC = C2)OC(C1OC(= O)CCCCCCCCCCC)N1C = CC(N) = NC1 = O |
12 | C56H79N3O7 | 906.26 | 2´,3´-Di-O-myristoyl-5´-O-(triphenylmethyl)cytidine | CCCCCCCCCCCCCC(= O)OC1C(COC(C2 = CC = CC = C2)(C2 = CC = CC = C2)C2 = CC = CC = C2)OC(C1OC(= O)CCCCCCCCCCCCC)N1C = CC(N) = NC1 = O |
13 | C38H43N3O7 | 653.77 | 2´,3´-Di-O-pivaloyl-5´-O-(triphenylmethyl)cytidine | CC(C)(C)C(= O)OC1C(COC(C2 = CC = CC = C2)(C2 = CC = CC = C2)C2 = CC = CC = C2)OC(C1OC(= O)C(C)(C)C)N1C = CC(N) = NC1 = O |
14 | C42H33N3O7Cl2 | 762.64 | 2´,3´-Di-O-(4-chlorobenzoyl)-5´-O-(triphenylmethyl) cytidine | NC1 = NC(= O)N(C = C1)C1OC(COC(C2 = CC = CC = C2)(C2 = CC = CC = C2)C2 = CC = CC = C2)C(OC(= O)C2 = CC = C(Cl)C = C2)C1OC(= O)C1 = CC = C(Cl)C = C1 |
15 | C46H36N3O7 | 742.80 | 2´,3´-Di-O-cinnamoyl-5´-O-(triphenylmethyl)cytidine | NC1 = NC(= O)N(C = C1)C1OC(COC(C2 = CC = CC = C2)(C2 = CC = CC = C2)C2 = CC = CC = C2)C(OC(= O)\C = C/C2 = CC = CC = C2)C1OC(= O)\C = C/C1 = CC = CC = C1 |
Antiviral Activity Prediction
When considerable antimicrobial and anti-carcinogenic activities were acquired, we predicted the antiviral activities of cytidine derivatives (2–15) and compared them with those of azidothymidine (AZT, antiviral drug) and remdesivir (COVID-19 drug) by using an antiviral application (Table 2) [45].
Table 2
Predicted antiviral activities (% inhibition) of cytidine derivatives 2–15, remdesivir, and AZT
Compounds | General | HBV | HCV | HHV | HIV |
1 | - | - | - | - | - |
2 | 56.694 | 24.616 | 52.294 | 39.139 | 60.776 |
3 | 50.334 | 25.168 | 44.745 | 68.231 | 69.760 |
4 | 51.770 | 25.164 | 44.746 | 65.844 | 70.174 |
5 | 7.689 | 20.217 | 18.367 | 48.010 | 71.148 |
6 | 5.209 | 22.034 | 17.707 | 32.962 | 62.485 |
7 | 8.964 | 19.478 | 38.064 | 46.137 | 65.673 |
8 | 54.817 | 25.306 | 58.732 | 51.525 | 55.146 |
9 | 2.101 | 19.505 | 44.539 | 44.016 | 68.671 |
10 | 2.327 | 19.694 | 37.089 | 45.767 | 68.719 |
11 | 50.134 | 24.790 | 47.106 | 60.254 | 62.961 |
12 | 4.310 | 20.681 | 37.091 | 43.999 | 69.047 |
13 | 3.345 | 19.376 | 56.274 | 81.466 | 65.758 |
14 | 47.021 | 26.981 | 46.291 | 75.321 | 63.214 |
15 | 61.039 | 18.367 | 53.816 | 61.409 | 63.427 |
Remdesivir | 48.642 | 22.443 | 66.968 | 36.291 | 69.503 |
AZT | 87.038 | 19.619 | 24.962 | 28.728 | 92.855 |
HBV = Hepatitis B virus; HCV = Hepatitis C virus; HHV = Human herpesvirus; HIV = Human immunodeficiency virus. |
The predicted antiviral activities revealed that the modified cytidine derivatives (2–15) exhibit potential antiviral efficacy compared with their parent molecules. The aliphatic derivatives (2–4) and aromatic derivatives (8, 11, 14, and 15) exhibited more promising scores than aliphatic derivatives (3–5) along with standard drugs remdesivir and azidothymidine (AZT).
Computed and Experimental IR Spectrum for Characterization
The IR spectrum, which indicated the characteristic peaks for various functional groups, was calculated through optimization and frequency calculation by using Gaussian software 09 packet. In the modified cytidine derivatives, various aliphatic chains (pivaloyl, hexanoyl, octanoyl, decanoyl, laouroyl palmitoyl, myristoyl, and steroyl) and aromatic (4-chlorobenzoyl, cinnamoyl, 4-tert-butylbenzoyl, and trityl) groups were introduced. In some functional groups, such as CH3, CO and NH3, where the C–C, C–H, C–N, C = O, and N–H stretching vibrations were observed (Fig. 4).
For derivatives (2) and (8), where primary hydroxyl (–OH) was modified with decanoyl and trityl groups, peaks appeared at approximately 1730 and 1720 cm− 1 for –CO stretching, 3420–3500 cm− 1 for –OH stretching, and 3545 cm− 1 due to –NH stretching. For derivatives (3–5) and (9–13), where the secondary hydroxyl (–OH) groups were substituted with different aliphatic chains (C5–C18), the IR spectra displayed absorption bands at 1715–1730 and 3450–3480 cm− 1 for C = O and –NH stretching, respectively. Finally, aromatic substituents derivatives (6, 7, 14, and 15) displayed peaks for C = O and –NH stretching in the experimental IR range.
The experimental IR spectra of the cytidine derivatives (Fig. 5) displayed peaks at almost the same frequency as the computed frequency for all the functional groups. The IR spectra of derivatives (2 and 8) show the following absorption bands: 1731 and 1714 cm− 1 (due to –CO stretching), 3420 cm− 1 and 3416 cm− 1 (due to –OH stretching), and 3550 cm− 1 (due to –NH stretching). Furthermore, for derivatives (3–5) and (9–13) modified with different aliphatic chains (C5–C18), the IR spectra displayed absorption bands at 1729 and 1716 cm− 1 for C = O starching and 3470 cm− 1 for –NH stretching. Because no –OH group was present in these derivatives, the peak for OH was absent in their spectra. Moreover, derivatives (6, 7, 14, and 15), which comprised aromatic substituents, displayed absorption bands at 1726 and 3470 cm− 1 corresponding to C = O and –NH stretching vibrations. Both the experimental and predicted IR analyses confirmed the insertion of different aliphatic and aromatic substituents in the cytidine structure.
MEP
In the computer-aided drug design, atomic charges are employed to investigate the connectivity between the structure and biological activity of drugs. MEP is globally used as a reactivity map displaying the most suitable regions for the electrophilic and nucleophilic attacks of charged-point-like reagents on organic molecules [46].
MEP helps interpret the biological recognition process and hydrogen bonding interactions [47]. The counter map of MEP provides a simple approach to predict how different geometries can interact. The MEP of the title compound was obtained based on B3LYP with the basis set 3-21G-optimized results (Fig. 6). MEP is important because it simultaneously displays the molecular size and shape and positive, negative, and neutral electrostatic potential regions for color grading and is useful for studying molecular structures with the physicochemical property relationship [48]. MEP was calculated to determined the reactive sites for the electrophilic and nucleophilic attacks of the optimized structure of cytidine derivatives (7, 8, and 10). The red, blue, and green colors represent the maximum negative area favorable for electrophilic attacks, maximum positive area favorable for nucleophilic attacks, and zero potential areas, respectively.
Molecular Docking Simulation
In structural biology and the computer aided drug design, molecular docking is an important computational technique. The key aim of molecular docking is to determine the potential binding geometries of a putative ligand of a known 3D structure with a target protein. In this study, several cytidine derivatives were studied in silico to determine their possible binding energies and interaction modes with the active sites of SARS-CoV-2 Mpro (Table 4) by using AutoDock Vina software. Table 3 presents the estimated binding energies of the binding site of the 6LU7 enzyme (Fig. 7) structure for all the studied compounds. According to the docking screening results, eight derivatives (6–10 and 13–15) with the strongest binding energies were selected to describe the binding mode of cytidine inhibitors. Comparatively, the aromatic derivatives exhibited better binding scores than the aliphatic derivatives. Figure 8 illustrates the interactions between the inhibitor and bordering residues of SARS-CoV-2 Mpro in 2D schematics acquired by importing docking results into the Discovery Studio Visualizer. These interactions showed that the amino acids participated in interactions between the ligand and enzyme with an important contribution to the total interaction energy. Most interactions included hydrophobic contacts, Van der Waals interactions, hydrogen bonding, electrostatic interactions, carbonyl interactions, and a specific atom-aromatic ring and provided insights to understand molecular recognition. Figure 9 presents the docked conformation of the most active molecules (8 and 14) based on the docking studies. The results showed derivative (14) as the most promising ligand (− 9.2 kcal/mol) that bound with SARSCoV-2 Mpro through hydrophobic bonding and many hydrogen interactions. The binding site is located in the hydrophobic cleft bordered with amino acid residues HIS41, ILE249, PHE294, VA104, CYS145, HIS246, and VAL297. Four hydrogen bond contacts occur with four different amino acids, ASN151, ILE152, and GLN110 at distances of 2.526, 2.814, 2.417, and 2.282 Å, respectively. Compound (14) exhibited an additional benzene ring in cytidine, providing a high density of electrons in the molecule and the highest binding score. These results indicated that modification of the –OH group along with long carbon chains/aromatic ring molecules led to an increase in the binding affinity, and the addition of hetero groups such as Br caused some fluctuations in binding affinities; however, modification with halogenated aromatic rings led to an increase in the binding affinity. The docked pose showed that the drug molecules bind within the active site of the SARS-CoV-2 Mpro macromolecular structure.
Table 3
Binding energy of the cytidine derivatives against Mpro
Main protease 6LU7 | Main protease 6LU7 |
Compounds | Binding affinity | No. of hydrogen bond | No. of hydrophobic bond | NBI | Compounds | Binding affinity | No. of hydrogen bond | No. of hydrophobic bond | NBI |
1 | -5.9 | 7 | 1 | H, A | 2 | -5.7 | 6 | 1 | H, PDH, PA |
3 | -5.1 | 3 | 4 | H, PAn, A, PA | 4 | -4.6 | 5 | 2 | H, A |
5 | -5.5 | 1 | 3 | C, A, PA | 6 | -6.1 | Absent | 2 | PPT, PA |
7 | -7.4 | 3 | 3 | H, PS, A | 8 | -7.4 | 3 | 3 | H, PAn, PA |
9 | -7.4 | 4 | 9 | H, PS, APS, A, PA | 10 | -7.0 | 5 | 8 | H, PS, APS, A, PA |
11 | -5.8 | 3 | 7 | H, PS, PPS, PPT, PA | 12 | -5.2 | 1 | 6 | H, PS, APS, A, PA |
13 | -8.0 | 4 | 6 | H, PS, APS, PA | 14 | -9.2 | 4 | 9 | H, PS, APS, A, PA |
15 | -6.8 | 1 | 3 | H, PS, PA | | | | | |
NBI: Nonbonding interaction; H = Conventional hydrogen bond; C = Carbon–hydrogen bond; A = Alkyl; PA = Pi-alkyl; PAn = Pi-anion; APS = Amide pi-stacked; PDH = Pi-donor hydrogen bond; PPS = Pi–pi stacked; and PPT = Pi–pi T-shaped. |
Parent molecule cytidine (1) interacted with the key residues of main protease CYS145 and HIS163 through hydrogen bonding within a close bond distance (2.173Å). Additionally, GLY143, SER144, and LEU141 interactions were observed, and interaction with SER144 showed a shorter bond distance (2.277Å) due to the unique interaction of the branched alkyl chain with the cytosine base. Acyl-chain-substituted derivatives (3–5) and (11 and 12) revealed low binding scores with the main protease, indicating the burying of the ligand in the receptor cavity. Although these derivatives exhibited low binding affinity, they interacted with the catalytic binding of the main protease, such as TYR154, HIS41, HIS163, HIS164, PHE294, GLN110, ASN238, GLU166, SER158, ILE152, THR199, and GLY143. |
Table 4
Nonbonding interaction data of the cytidine derivatives against Mpro
Main protease 6LU7 | Main protease 6LU7 |
Hydrogen bond | Hydrophobic bond | Hydrogen bond | Hydrophobic bond |
Compounds | Residues | Distance (Å) | Residues | Distance (Å) | Comp. | Residues | Distance (Å) | Residues | Distance (Å) |
1 | LEU141 | 2.838 | CYS145 | 5.085 | 2 | GLY143 | 1.883 | CYS145 | 5.343 |
HIS163 | 2.663 | | | GLU166 | 2.108 | | |
GLY143 | 2.483 | | | HIS164 | 2.251 | | |
SER144 | 2.277 | | | HIS163 | 2.398 | | |
SER144 | 2.659 | | | LEU141 | 2.015 | | |
CYS145 | 2.173 | | | HIS41 | 3.097 | | |
CYS145 | 2.613 | | | | | | |
3 | LYS102 | 2.433 | ASP153 | 4.637 | 4 | LYS137 | 2.737 | MET276 | 3.937 |
SER158 | 2.628 | PRO293 | 4.126 | LYS137 | 2.844 | LEU287 | 4.611 |
SER158 | 1.839 | VAL104 | 5.318 | LYS137 | 2.220 | | |
| | TYR154 | 5.306 | THR199 | 2.518 | | |
| | | | ASN238 | 2.851 | | |
5 | GLN110 | 3.056 | ILE249 | 5.095 | 6 | | | TYR237 | 5.126 |
| | PHE8 | 5.046 | | | LEU286 | 5.057 |
| | PHE294 | 4.595 | | | | |
7 | ASP289 | 2.119 | LEU287 | 3.835 | 8 | THR198 | 2.718 | ASP289 | 3.421 |
ARG131 | 2.329 | LEU287 | 4.926 | THR199 | 2.991 | LEU286 | 4.921 |
THR199 | 2.327 | LEU286 | 5.198 | ASN238 | 2.261 | LEU286 | 4.811 |
9 | ASN151 | 2.329 | ILE249 | 3.877 | 10 | ASN151 | 2.375 | ILE249 | 3.984 |
THR111 | 2.669 | PHE294 | 4.144 | ASN151 | 2.328 | PHE294 | 4.225 |
THR111 | 2.037 | VAL104 | 3.736 | THR111 | 2.388 | ILE249 | 5.107 |
THR111 | 2.611 | ILE106 | 4.574 | THR111 | 2.140 | PRO293 | 4.490 |
| | ILE249 | 5.080 | GLN110 | 2.267 | ILE249 | 4.733 |
| | PRO293 | 4.611 | | | VAL297 | 5.109 |
| | VAL297 | 4.982 | | | PHE294 | 5.480 |
| | PHE294 | 5.333 | | | PHE294 | 4.311 |
| | PHE294 | 4.231 | | | | |
11 | THR111 | 2.680 | ILE249 | 3.854 | 12 | ILE152 | 2.956 | ILE249 | 3.851 |
THR111 | 3.081 | PHE294 | 3.929 | | | PHE294 | 4.079 |
THR111 | 2.749 | PHE294 | 5.516 | | | ILE249 | 4.633 |
| | PRO293 | 4.744 | | | ILE249 | 5.111 |
| | VAL297 | 5.048 | | | PRO293 | 4.326 |
| | ILE249 | 4.746 | | | VAL297 | 5.070 |
| | PHE294 | 5.052 | | | PHE294 | 3.772 |
13 | ASN151 | 2.340 | ILE249 | 3.691 | 14 | ASN151 | 2.526 | HIS41 | 3.834 |
ASP295 | 2.080 | PHE294 | 4.118 | ILE152 | 2.417 | ILE249 | 3.884 |
ASN151 | 2.445 | VAL297 | 4.998 | GLN110 | 2.282 | PHE294 | 4.463 |
GLN110 | 2.116 | PRO293 | 4.566 | ASN151 | 2.814 | ILE249 | 5.220 |
| | ILE249 | 5.007 | | | VAL104 | 3.958 |
| | PHE294 | 4.415 | | | VAL297 | 5.405 |
15 | GLN110 | 2.068 | PHE294 | 3.964 | | | CYS145 | 4.280 |
| | VAL104 | 4.881 | | | VAL104 | 4.203 |
| | ILE249 | 4.897 | | | HIS246 | 5.103 |
These derivatives exhibited diverse nonbonding interactions, such as pi–anion, pi–donor hydrogen bond, amide pi-stacked, pi–pi stacked, and pi–pi T-shaped interactions, with the active sites of the main protease.
The aromatic substituents led to an increase in the binding energies in derivatives; 7–10 = − 7.4, − 7.4, − 7.4, and − 7.0 kcal/mol, respectively, and 13–15 = − 8, − 6.2, and − 9.2 kcal/mol, respectively. These derivatives interacted with the similar binding sites of the main protease, and PHE294, THR111, GLN110, ILE249, LEU287, and ASN151 were the most common residues for them. Amongst all the proteases, GLN 110 exhibited the minimum bond distance of 2.116 and 2.068 Å. These results revealed that due to the high electron density, aromatic substituents can easily lead to an increase in the binding and antiviral abilities of the cytidine derivatives. Along with PHE294, all the derivatives showed the maximum π–π interactions with ILE249, indicating strong binding with the active site. PHE294 is considered the principal component of PPS, APS, and PPT, which is responsible for the accessibility of small molecules to the active site. Binding energies and binding modes were improved for derivatives (7–10 and 13–15) due to significant hydrogen bonding. The alterations of the –OH group in thymidine exalted the π–π interactions with the amino acid chain at the binding site, and their polarity improvement resulted in hydrogen bond formation. The maximum numbers of H-bonds were observed in derivative (10), with ASN151, THR111, and GLN110 residues.
Ten commercial medicines possibly form H-bonds with the key residues of the 2019-nCoV main protease [49]. H bonds executed a vital role in shaping the specificity of ligand binding with receptors, drug design in chemical and biological processes, molecular recognition, and biological activity. Figure 10 presents the H-bond surface and hydrophobic surface of derivative (10) with both the proteins. The blind docking study of all the cytidine derivatives with the SARS-CoV-2 protease revealed that the molecules were generally surrounded by the aforementioned residues, which is similar to the arrangement in standard drugs. This finding suggested that this molecule may prevent the viral replication of SARS-CoV-2.
Table 4 presents the bond distance for the ligands and the changes in the accessible area of the two important catalytic residues (Cys145 and His41) within the active site of the protease. The blind docking results revealed that all the molecules can act as potential agents for COVID treatment; however, the estimated free energies of binding values indicated derivative (14), with the highest negative minimum binding energy value of − 9.2 kcal/mol, as the optimum possible SARS-CoV-2 inhibitor among all the studied derivatives. Most selected cytidine derivatives exhibited promising activities and may use to develop effective antiviral drugs against SARS-CoV-2.
Biological explication
The inhibition capacity of cytidine-like nucleosides against SARS-CoV-2 Mpro has been investigated in vitro [33–34]. Because SARS-CoV and SARS-CoV-2 viruses are highly similar, we investigated the in silico behavior of the cytidine derivatives toward SARS-CoV-2 Mpro. Selecting this protein as the target led to considerable advances in antiviral treatment because it participates in the proteolytic processing of polyproteins replication. Consequently, it plays a key role in the expression and replication of viral genes. Therefore, the inhibition of this enzyme hampered the replication of the viral genome and multiplication of SARS-CoV-2. Nucleoside derivatives that can inhibit SARS-CoV 3CLpro may inhibit SARS-CoV-2 Mpro in the same manner due to their high-sequence identity.
Pharmacokinetic profile and molecular radar
To predict the pharmacokinetic properties, such as solubility, lipophlicity, and toxicity of the compounds, we used the pkCSM ADMET descriptor algorithm protocol. Drug absorption depends on various factors, including membrane permeability [indicated by the cell line of colon cancer (Caco-2), intestinal absorption, skin permeability thresholds, substrate, and P-glycoprotein inhibitors.
Table 5
Prediction in silico of absorption of cytidine derivatives
Compounds | Water solubility (log mol/L) | Lipophlicity (Consensus Log Po/w) | Caco2 permeability | Skin permeability |
1 | -1.689 | -1.77 | 0.025 | -2.745 |
2 | -3.166 | 1.35 | 0.233 | -2.749 |
3 | -4.042 | 6.47 | 0.263 | -2.735 |
4 | -2.977 | 12.28 | -0.807 | -2.735 |
5 | -2.920 | 13.47 | -0.917 | -2.735 |
6 | -2.892 | 9.15 | -1.732 | -2.735 |
7 | -3.616 | 6.95 | -0.355 | -2.735 |
8 | -3.728 | 2.44 | 0.559 | -2.735 |
9 | -4.363 | 5.83 | -0.590 | -2.735 |
10 | -4.077 | 6.65 | -0.598 | -2.735 |
11 | -3.075 | 9.86 | -0.625 | -2.735 |
12 | -2.951 | 11.23 | -0.627 | -2.735 |
13 | -4.458 | 5.05 | -0.118 | -2.735 |
14 | -2.931 | 6.44 | 0.769 | -2.735 |
15 | -2.950 | 5.94 | 0.870 | -2.735 |
All the derivatives showed excellent lipophlicity with the values of − 1.35 to 13.47 (Table 5). Skin permeability is an important factor for drug efficacy improvement, especially in the development of transdermal drug delivery. A molecule barely penetrates the skin if log Kp is more than − 2.5 cm/h [50]. The skin permeability Kp of the cytidine derivatives is − 2.731 cm/h ( < − 2.5) (Table 5). Therefore, all the presented derivatives exhibit high skin penetrability.
In the pkCSM predictive model, high Caco-2 permeability is translated into the predicted log Papp values > 0.90 cm/s.7 The value of Caco-2 permeability (log Papp) of the cytidine derivatives ranges from − 4.3 to − 2.4 cm/s, log Papp < 0.9 cm/s (Table 6); thus, these derivatives exhibit a low Caco-2 permeability. Molecular radar is a crucial QSAR factor exhibiting the molecular volume of compounds. Figure 11 illustrates the physicochemical radar of all the cytidine derivatives and reveals the promising QSAR features of the designed compounds. To discover oral administrative drugs, solubility is a major descriptor. High water solubility is useful to deliver active ingredients in a sufficient quantity with small volumes of pharmaceutical dosage. These water solubility values are presented as log (mol/l) (insoluble ≤ − 10 < poorly soluble < − 6 < moderately soluble < − 4 < soluble < − 2 < very soluble < 0 ≤ highly soluble). The tested compounds are soluble (Table 6).