In silico DFT study, molecular docking, and ADMET predictions of cytidine analogs with antimicrobial and anticancer properties

Abstract

Nucleoside analogs contribute in pharmaceutical and clinical fields as medicinal agents and approved drugs. This work focused to investigate the antimicrobial, anticancer activities, and structure–activity relationship (SAR) of cytidine and its analogs with computational studies. Microdilution was used to determine the antimicrobial activity, minimum inhibitory concentration (MIC), and minimum bactericidal concentration (MBC) of the modified analogs against human and phytopathogenic strains. Compounds (7), (10), and (14) were the most potent against Escherichia coli and Salmonella abony strains with MIC and MBC values from 0.316 ± 0.02 to 2.50 ± 0.03 and 0.625 ± 0.04 to 5.01 ± 0.06 mg/ml, respectively. The highest inhibitory activity was observed against gram-positive bacteria. Numerous analogs (10), (13), (14), and (15) exhibited good activity against the tested fungi Aspergillus niger and Aspergillus flavus. Anticancer activity of the cytidine analogs was examined through MTT colorimetric assay against Ehrlich’s ascites carcinoma (EAC) tumor cells whereas compound 6 showed the maximum antiproliferative activity with an IC₅₀ value of 1168.97 µg/ml. To rationalize this observation, their quantum mechanical and molecular docking studies have been performed against urate oxidase of A. flavus 1R51 to investigate the binding mode, binding affinity, and non-bonding interactions. It was observed that most of the analogs exhibited better binding properties than the parent drug. In silico ADMET prediction was attained to evaluate the drug-likeness properties that revealed the improved pharmacokinetic profile with lower acute oral toxicity of cytidine analogs. Based on the in vitro and in silico analysis, this exploration can be useful to develop promising cytidine-based antimicrobial drug(s).

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-021-00102-0.

Introduction

Nucleosides play an important role in cell physiology as both nutrients and cellular homeostasis modulators. They are implicated in crucial processes such as DNA and RNA syntheses, cell signaling, and metabolic regulation. Cytidine (Fig. 1) illustrates a ribonucleoside containing a pyrimidine base (i.e., cytosine), which is linked to a pentose sugar (i.e., ribose sugar) through the β-N₁glycosidic linkage. Cytidine is a component of RNA and a precursor for uridine. When RNA-rich food is consumed, RNA is broken down into ribosylpyrimidines (cytidine and uridine) and its basic elements are released for absorption from the intestine (Wurtman et al. 2000). RNA-rich foods are considered good cytidine sources. The supplementation of dietary cytidine (5′)-diphosphocholine protects against the development of memory deficits (Teather and Wurtman 2003). Cytidine is found in organ meats and pyrimidine-rich foods such as beer, tomatoes, broccoli, and oats. Cytidine is one of the RNA components that translate instruction from DNA to proteins. When RNA levels decrease, cytidine is supplemented to maintain high RNA levels for a better memory function. Another important function of cytidine is to increase dopamine production and release it in the brain. Cytidine is a powerful neurotransmitter, which is responsible for regulating functions such as mood and movement control.

Fig. 1.

3D structure of the urate oxidase from A. flavus complexes with its inhibitor 8-azaxanthin (PDB: 1R51)

Nucleoside analogs and nucleobases are a pharmacologically diverse family, which includes cytotoxic compounds, antiviral agents, and immune suppressive molecules. Cytidine analog 5-AZA-2′-deoxycytidine is used to control the growth of neuroblastoma malignant tumors (Bartolucci et al. 1989). In addition to its role as a pyrimidine component of RNA, cytidine controls neuronal-glial glutamate cycling by supplementing midfrontal/cerebral glutamate/glutamine levels that have decreased, and cytidine has received attention as a potential glutamatergic antidepressant drug (Rodrigo et al. 2010). The cytidine analog KP-1461 is an anti-HIV agent that acts as a viral mutagen (Harris et al. 2005). Various cytidine derivatives modified at the base or ribose exhibit antiviral or antitumor activities (Biron et al. 2002; Prichard et al. 2011; Williams et al. 2003).

Modifications in the sugar moiety of nucleosides have resulted in various effective therapeutic and biological applications. A literature survey (Hui et al. 2002; Patel et al. 2002) revealed that numerous biologically active compounds have aromatic and heteroaromatic nuclei and acyl substituents. If an active nucleus is linked to another nucleus, the resulting molecule may exhibit a high potential for biological activity (Gupta et al. 1997). Benzene and substituted benzene nuclei play an important role as the common denominator of various biological activities (Tannaza et al. 2014). The results of ongoing studies on the selective acylation of nucleosides (Kawsar et al. 2015; Rahman et al. 2019) and evaluation of antimicrobial activities have revealed the combination of two or more aromatic or heteroaromatic nuclei for many cases (Arifuzzaman et al. 2018; Ghorab et al. 2004). Moreover, N, S, and X containing substitution products show marked antimicrobial activities, that is, enhance the biological activity of parent compounds (El-Farargy and Amira 2009; Kawsar et al. 2014). Aspergillus flavus is an opportunistic pathogen of crops and animals, including humans, and it produces a carcinogenic toxin called aflatoxin. Because of this, A. flavus accounts for food shortages and economic losses in addition to sickness and death. The three-dimensional structure of the studied enzyme is urate oxidase from A. flavus complexed with its inhibitor 8-azaxanthin (PDB: 1R51) shown in Fig. 1, is an essential enzyme responsible for the first step in the degradation of uric acid. This enzyme demonstrated its activity to oxidize the uric acid, and it is known as one of the proteins docked to study the antioxidant activity theoretically (Retailleau et al. 2004; Tareq et al. 2019). The preclinical drug design trial consists of in silico and in vitro experiments. Based on the accurate structural models of biological targets and small molecules, molecular docking software can be used to estimate the affinity of ligand in the pocket of biological macromolecules (Pagadala et al. 2017). Now days, emergence of multiple drug-resistant pathogenic organisms became a matter of global concern and researchers encounter numerous obstacles to deliver drug molecules to the site of microbial infection. Many researchers are engaged to overcome these situations. In this regard, we continuously put the effort to find novel antibacterials and antifungals to carry out this investigation combining the in silico and in vitro studies. We report herein the in vitro antimicrobial efficacy of several cytidine analogs with different aliphatic and aromatic chains against seven pathogens, in vitro anticancer test, molecular docking against A. flavus (1R51) along with structure–activity relationship (SAR) study.

Computational chemistry is a popular approach to calculate the physicochemical, spectral, and biological properties of the newly synthesized chemicals (Chatfield and Christopher 2002). In this study, synthesized cytidine analogs were optimized to understand their thermal and electrical stability and biochemical behaviors based on quantum mechanical methods. Free energy, enthalpy, dipole moment, highest occupied molecular orbital–lowest unoccupied molecular orbital (HOMO–LUMO) gap, DOS (density of states), plot, and molecular electrostatic potential were calculated to compare their thermal and chemical behaviors. Molecular docking was performed against urate oxidase of A. flavus 1R51 to identify the binding mode, binding affinity, and non-bonding interaction of cytidine analogs with the receptor protein. The pharmacokinetic prediction was obtained to calculate the absorption, metabolism, and toxicity of the analogs. A computational investigation was conducted to understand the thermodynamic, molecular orbital, molecular electrostatic potential, physicochemical, biological, and ADMET properties. Encouraged by the literature (Juraj et al. 2017; Mohamed et al. 2015) and our findings (Devi et al. 2019; Kawsar et al. 2018; Shagir et al. 2016), we evaluated modified analogs of cytidine (Schemes 1, 2) containing various substituents in a single molecular framework of their antibacterial, antifungal, and anticancer activities and conducted computational studies on them for the first time.

Scheme 1.

a dry C₆H₅N, − 5 °C, 6 to 7 h; 2 = decanoyl derivative. b dry pyridine, 0 °C, rt, DMAP, stir for 6 to 7 h, R₁ = different acyl halides (3–7)

Scheme 2.

c dry C₆H₅N, 0–5 °C, 6 h; 8 = triphenylmethyl derivative; d anhydr. pyridine, 0 °C, DMAP, R₂ = several acyl halides (9–15)

Materials and methods

All reagents used were commercially available (Aldrich) and used without further purification unless otherwise specified. The following software’s were used in the present study: (1) Gaussian 09, (2) GaussSum 3.0, (3) AutoDock 4.2.6, (4) Swiss-Pdb 4.1.0, (5) Python 3.8.2, (6) Discovery Studio 4.1, (7) PyMOL 2.3, (8) ChemDraw Pro 12.0 was used to draw the two-dimensional structure of uridine derivatives, (9) admetSAR server (http://lmmd.ecust.edu.cn/admetsar2/about) and SwissADME free web tools (http://www.swissadme.ch) were employed to calculate the pharmacokinetic properties.

In vitro drug designing

In vitro experiments complemented with computational methods have been extensively used in early drug discovery to select compounds with more favorable ADME and toxicological profiles (Ripphausen et al. 2010). Based on various protein targets of diseases, multiple approaches (including biological and in silico) had been designed to screen new drugs towards the treatment of diseases. Cell-free system is another common method used in drug discovery. It has various advantages-fast, microscale-based, delivers high throughput, accurate and stable screening results (Fara et al. 2006). It is a more biologically relevant cell-based screening method that has been developed and widely used to predict responses of an organism to drugs. The MTT colorimetric assay is a common cell model used in this study to detect the proliferation of Ehrlich’s ascites carcinoma (EAC) cells. Our investigation was based on the in vitro biochemical compound screening (antimicrobial) and in vitro cell-based approach (anticancer).

In vitro antimicrobial evaluation

The antibacterial efficacy of fourteen newly synthesized cytidine analogs 2–15 against five different microbial strains was studied. Two gram-positive bacteria, Bacillus subtilis ATCC 6633 and Staphylococcus aureus ATCC 6538 and three gram-negative bacterial strains, Escherichia coli ATCC 8739, Salmonella abony NCTC 6017, and Pseudomonas aeruginosa ATCC 9027 were used in this experiment. In all cases, a 2–3% solution (w/v) of the chemicals in dimethylformamide (DMSO) was used. Moreover, the antifungal activities of the compounds were studied against two fungi, Aspergillus niger ATCC 16,404 and Aspergillus flavus ATCC 204,304. The test microorganisms were collected from the Department of Microbiology, University of Chittagong.

In vitro antibacterial efficacy test

The newly acylated cytidine analogs (Schemes 1, 2) in vitro were selected and screened to investigate their antibacterial activity against five human pathogenic bacteria by using the disk diffusion method (Bauer et al. 1966). In this method, paper disks and a glass Petri plate of 4 and 90 mm, respectively, in diameter were used throughout the experiment. Sterile dimethyl sulfoxide (DMSO) was employed to prepare the desired concentrations of the synthesized compounds and standard antibiotics. The paper disks were soaked with test chemicals at a rate of 0.2 mg (dry weight) per disk for the antibacterial analysis. The bacterial suspensions were swabbed with Mueller–Hinton Agar (MHA) media and then sterile soaked disks were placed on it. First, the plates were maintained at low temperature (4 °C) for 4 h, and the test chemicals diffused from the disks into the surrounding media by this time. The plates were then incubated at 37 °C for test organism growth and were observed at intervals of 24 h for 2 days. Azithromycin acquired from Asiatic Laboratories Ltd. (Bangladesh) was used as the positive control, and DMSO was used as the negative control. The activity was expressed in terms of inhibition zone diameters in mm, and the experiments were performed in triplicates.

Determination of MIC and MBC

MIC and MBC were determined using the two-fold broth dilution technique (Amsterdam 2005). In this method, microtiter plates containing 96 wells (12 rows and 8 columns) were used. In all the wells, 50 µl Luria Burtenii (LB) media were taken. For certain rows, in the second well, 50 µl of chemicals were added and mixed properly, and then this 50 µl of chemicals from the second well was transferred into the third well. After the mixing of the 50 µl of chemicals from the third well, it was transferred into the fourth and gradually to the fifth, sixth, and seventh wells. Subsequently, the bacterial suspension was added to each test well, and the micro titer plates were incubated at 37 °C for 20–22 h. After incubation, the tested microtiter plates were assayed using 10 µl of the 2,3,5-triphenyltetrazolium chloride 0.5% (w/v) solution. Cultures were then incubated at 37 °C for 24 h. A change in the color from yellow to pink-red indicated bacterial growth and MIC was interpreted visually. The next highest MIC dilution, at which at least 99% of bacteria were inhibited to grow, was considered the MBC that was confirmed by bacterial growth on MHA. In a certain row, the first well was treated as the negative control without using any chemical, and the eighth well was treated as the positive control by using standard antibiotic azithromycin. All analyses were performed in triplicates.

In vitro antifungal mycelial test

The in vitro antifungal mycelial growth activity of the test compounds was analyzed using the “poisons food” technique (Grover and Moore 1962), and potato dextrose agar (PDA) was used as the culture medium. A required amount of medium was separately taken in a conical flask and sterilized in an autoclave. After the autoclaving process, the weighed amount of test chemicals [in DMSO to a 1–2% (w/v)] was added to the sterilized medium in the conical flask at the point of pouring to obtain the desired concentration. The flask was shaken thoroughly to homogeneously mix the chemical with the medium before pouring. The medium with a definite concentration (2%) of the chemical was individually poured at the rate of 10 µl in the sterilized glass Petri dishes. Proper control was maintained separately with the sterilized PDA medium without compounds, and three replications were prepared for each treatment. After medium solidification, the fungal inoculums (5 mm approximately) were placed at the center of each Petri dish in an inverted position. All the plates were inoculated at room temperature on the laboratory desk for 5 days. The linear growth of a fungal colony was measured in a two-direction straight angle to each other after 5 days of incubation, and the average of three replicates was considered the colony diameter in mm. The percentage inhibition of the mycelia growth of the test fungus was calculated as follows:

$$\mathrm{I}=\frac{\mathrm{C}-\mathrm{T}}{\mathrm{C}}\times 100,$$

where I is the percentage of inhibition, C represents the diameter of the fungal colony in the control (DMSO), and T is the diameter of the fungal colony during the treatment. The results obtained were compared with those of the standard antifungal agent nystatin, (BEXIMCO Pharm. Bangladesh Ltd.).

In vitro anticancer activity test

According to the method of Hasan et al. (2019), the MTT colorimetric assay with slight modifications was used to detect the proliferation of Ehrlich’s ascites carcinoma (EAC) cells. EAC cells were grown in the peritoneal cavity of Swiss albino mice and harvested using normal saline after 1 week. In a 96-well flat-bottom culture plate, 5 × 10⁵ EAC cells (5 × 10⁵ in 200 μl of RPMI-1640 media) were plated in the presence and absence of different concentrations of compound 6 (31.25–500 μg/ml). There were three control wells containing only RPMI-1640 media. The plate was incubated at 37 °C in a CO₂ incubator for 24 h. After the removal of the aliquot from each well, 180 μl of PBS (phosphate-buffered saline) and 20 μl of MTT (5 mg/ml) were added to the 96-well plate and incubated at 37 °C for 4 h. Subsequently, the aliquot was removed again and 200 μl of acidic isopropanol was added to each well. The plate was agitated for 5 min, and then the absorbance was measured at 570 nm by using a titer plate reader. The following equation was used to calculate the cell proliferation inhibition ratio:

$$\text{Proliferation inhibition ratio}\left(\%\right)=\left\{\left(\text{A}-\text{B}\right)\times 100\right\}/\text{A}$$

where A and B are the OD₅₇₀ nm of the cellular homogenate (control) without and with compound 6, respectively.

Structure–activity relationship

SAR studies can be conducted to predict the biological activity from the molecular structure of pharmaceutical targets. This powerful technology is frequently used in drug discovery processes to guide the acquisition or synthesis of desirable new compounds and to characterize existing molecules. SAR assays were performed according to the membrane permeation concept of Kim et al. (2007) and Hunt (1975).

Designing and optimization of cytidine derivatives

In quantum mechanical chemistry, quantum mechanical methods are widely used to calculate thermal, molecular orbital, and molecular electrostatic properties. All calculations were performed using Gaussian 09 software package employing density functional theory (DFT) (Gaussian et al. 2009). DFT with Beck’s (B) (Becke 1988) three-parameter hybrid models and Lee, Yang, and Parr’s (LYP) (Lee et al. 1988) correlation function under 3-21G basis set was employed to optimize and predict the thermal and molecular orbital properties of the derivatives. Dipole moment, enthalpy, free energy, entropy, heat capacity, total energy, and polarizability were calculated for all the compounds. Frontier molecular orbital features, HOMO and LUMO, were counted at the same level of theory. For each cytidine derivative, HOMO–LUMO energy gap, hardness (η), and softness (S) were calculated from the energies of frontier HOMO and LUMO by considering the Parr and Pearson interpretation of DFT and Koopmans theorem (Pearson 1986) on the correlation of the ionization potential (I) and electron affinities (E) with HOMO and LUMO energies (ε). The following equations were used to calculate the hardness (η) and softness (S).

$$\eta =\frac{[\epsilon \mathrm{L}\mathrm{U}\mathrm{M}\mathrm{O}-\epsilon \mathrm{H}\mathrm{O}\mathrm{M}\mathrm{O}]}{2};\mathrm{S}=\frac{1}{\eta }$$

Protein preparation and molecular docking

The three-dimensional crystal structure of urate oxidase A. flavus (PDB ID: 1R51) (Fig. 1) was collected in the pdb format from the protein data bank (Berman et al. 2000). All hetero atoms and water molecules were removed using PyMol (version 2.3) software packages (Delano 2002). Swiss-Pdb viewer software (version 4.1.0) was employed for the energy minimization of the protein (Guex and Peitsch 1997). Subsequently, the optimized ligands were employed in a molecular docking study against urate oxidase A. flavus (1R51). Molecular docking simulations were performed using PyRx software (version 0.8) (Dallakyan and Olson 2015) by considering the protein as the macromolecule and the drug as the ligand. Autodock Vina was employed for the docking analysis, and the AutoDock Tools (ADT) of the MGL software package was used to convert pdb to the pdbqt format to input proteins and ligands.

Size of the grid box of AutoDock Vina was set to 59.8172, 69.9537, and 58.3507 Å for X, Y, and Z directions, respectively. After completion of docking, both the macromolecule and ligand structures were saved in pdbqt format required by Accelrys Discovery Studio (version 4.1) to explore and visualize the docking results and search the non-bonding interactions between the ligands and amino acid residues of the receptor protein (Accelrys 2017). Figure 2 represents the binding sites of co-crystallized ligand 8-azaxanthin.

Fig. 2.

Binding sites of co-crystallized ligand; a Ligplot of interactions involving ligand AZA produced by PDBsum; b original published location of the AZA inhibitor; c the revised orientation of AZA in the new refined structure

Pharmacokinetic parameters study

To predict the pharmacological properties and toxicity of the modified cytidine analogs, the admetSAR server was utilized. We utilized the admetSAR online database to evaluate pharmacokinetics parameters related to drug absorption and metabolism and the toxicity of the parent drug and its designed analogs (Cheng et al. 2012). By using structure similarity search methods, admetSAR predicts the latest and most comprehensive manually curated data for diverse chemicals associated with known ADME/T profiles. Generally, drug-likeness is evaluated using Lipinski's rule of five (Lipinski et al. 2001). Although it is quite difficult to verify all of these compounds and to know whether this program included cytidine based drugs or not, however, well-known Pt-based cisplatin, carboplatin, and metal-based drugs approved in the FDA can be used as test candidates to verify our cytidine analogs.

Strategies and optimization of designed cytidine derivatives

The newly synthesized analogs of cytidine were designated according to the reaction scheme. Cytidine (1) and its analogs were designated and optimized in the quantum mechanical method. Figure 3 shows the chemical and stable optimized structure of some cytidine analogs.

Fig. 3.

Chemical and stable optimized structure cytidine (1) and some of its derivatives. Optimized with DFT-B3LYP/3-21G

Statistical analysis

For each parameter investigated, the experimental results are presented as mean ± standard error for three replicates. Two-tailed Student’s t-tests were used for statistical analysis. Only theρvalues of < 0.05 were considered statistically significant.

Results and discussion

In the present investigation, the test analogs (2–15) (decanoylation and triphenylmethylation) (Schemes 1, 2) were previously prepared from a common precursor, namely, cytidine (1). These test analogs (2–15) contain a wide variety of substituents. These substituent groups were deliberately introduced to the ribofuranose molecule to study their effectiveness towards various micro-organisms. As a result of screening modified cytidine analogs for potential antimicrobial activity, we have observed that most of the compounds have potent bactericidal and fungicidal in vitro activity against five tested bacterial and two tested fungal pathogens. In vitroanticancer test revealed the anticancer potentiality of compound 6 against EAC. Besides, SAR study and in silico (quantum chemical, molecular docking, and pharmacokinetic) findings also rationalized the in vitro results and suggested modified cytidine analogs are probable antimicrobial candidates especially for A. flavus (1R51). Figure 4 represents the whole workflow of the present study.

Fig. 4.

Combined workflow of in vitro and in silico study

In vitro antimicrobial activities

Determination of the in vitro antibacterial activity

Table 1 and Fig. 5 present the antibacterial activity of the test compounds (1–15) measured in terms of zone of inhibition in mm. The test compounds exhibited promising inhibitory activity against both the Gram-positive and Gram-negative bacterial strains. The inhibition data indicated that compounds (7, 10, and 11) were more active against B. subtilis and S. aurious than the standard antibiotic, Ampicillin was. Furthermore, compound (7) (29 ± 0.25 mm) showed the highest activity against B. subtilis, which was higher than that of the standard drug, among all tested organisms. However, acylated compounds (2, 4, 5, and 13) showed slight inhibition or did not show any inhibition against the bacterial strains examined. Compounds (3, 7, 10, and 15) were highly active against both the Gram-positive and Gram-negative organisms. Starting cytidine compound 1 did not show any activity against any tested bacteria. This variation in the antibacterial activity of the examined compounds might have resulted due to incorporation of diverse acyl groups in cytidine.

Table 1.

Zones of inhibition observed against bacteria by using the test analogs

Compound	The diameter of the zone of inhibition in mm
	B. subtilis (+ve)	S. aureus (+ve)	E. coli (−ve)	S. abony (−ve)	P. aeruginosa (−ve)
1	NI	NI	NI	NI	NI
2	NI	09 ± 0.27	08 ± 0.28	NI	07 ± 0.39
3	*21 ± 0.30	18 ± 0.21	NI	*20 ± 0.34	15 ± 0.35
4	15 ± 0.41	NI	NI	NI	NI
5	12 ± 0.50	10 ± 0.13	NI	NI	10 ± 0.26
6	13 ± 0.20	08 ± 0.25	NI	NI	NI
7	*29 ± 0.25	*20 ± 0.31	*25 ± 0.23	*20 ± 0.34	NI
8	16 ± 0.41	NI	NI	10 ± 0.31	10 ± 0.39
9	15 ± 0.26	10 ± 0.13	NI	NI	15 ± 0.3
10	*28 ± 0.33	*20 ± 0.36	15 ± 0.39	15 ± 0.41	*20 ± 0.4
11	*27 ± 0.46	18 ± 0.31	15 ± 0.31	NI	*20 ± 0.5
12	14 ± 0.4	10 ± 0.11	09 ± 0.28	NI	NI
13	10 ± 0.5	NI	NI	NI	NI
14	17 ± 0.21	*20 ± 0.15	*20 ± 0.39	NI	NI
15	15 ± 0.3	13 ± 0.37	07 ± 0.39	14 ± 0.35	*20 ± 0.42
Azithromycin	**19 ± 0.4	**19 ± 0.31	**20 ± 0.39	**18 ± 0.38	**18 ± 0.39

Data are presented as mean ± SD. Values are represented for triplicate experiments. Statistically significant inhibition (p < 0.05) is marked with one (*) and double (**) asterisk for the test compounds and reference antibiotic azithromycin, respectively. NI no inhibition

Fig. 5.

Percentage of inhibition observed for a B. subtilis from compounds 3, 7, 10, and 11; b S. aureus from compounds 3, 7, and 10. DMSO and azithromycin were the negative and positive controls, respectively

On the basis of their activity against bacteria and inhibition zone, the tested compounds can be arranged in the order of 7 > 10 > 11 > 3 > 14 > 15 > 9 > 12 > 5 for Gram-positive bacteria and of 7 > 10 > 15 > 3 > 11 > 14 > 5 > 12for Gram-negative bacteria. The growth inhibition of bacteria washighly remarkable in many cases, which conformed to our previous study results (Misbah et al. 2020; Juraj et al. 2017). Compounds 7, 10, and 11 were more effective against B. subtilis S. aureus, E. coli, S. abony, and P. aeruginosa than Ampicillin. Thus, MIC and MBC tests were conducted for these compounds against this bacterial strains. Tables 2 and 3 present the results.

Table 2.

MIC values for compounds 7, 10, and 11 against the tested organisms

Compound	MIC values in mg/ml
	B. subtilis	S. aureus	E. coli	S. abony	P. aeruginosa
7	0.316 ± 0.02	0.625 ± 0.04	0.316 ± 0.03	0.625 ± 0.04	NF
10	0.316 ± 0.02	0.625 ± 0.04	2.50 ± 0.03	2.50 ± 0.03	NF
11	0.316 ± 0.02	0.625 ± 0.04	1.25 ± 0.01	NF	0.625 ± 0.03

NF not found

Table 3.

MBC values for compounds 7, 10, and 11 against the tested organisms

Compound	MBC values in mg/ml
	B. subtilis	S. aureus	E. coli	S. abony	P. aeruginosa
7	0.625 ± 0.04	1.25 ± 0.06	0.625 ± 0.06	1.25 ± 0.02	NF
10	0.625 ± 0.04	1.25 ± 0.06	5.01 ± 0.06	5.01 ± 0.02	2.50 ± 0.02
11	1.25 ± 0.04	1.25 ± 0.04	2.50 ± 0.02	NF	1.25 ± 0.06

NF not found

According to the MIC and MBC results, (7) (4-t-butylbenzoyl-), (10) (heptanoyl-), and (11) (lauryl-) derivatives were highly active against B. subtilis, and all compounds showed minimum MIC (0.316 ± 0.02 mg/ml) against B. subtilis. Moreover, these three compounds showed the same MBC (1.25 ± 0.04) mg/ml against most bacteria. This result indicated that both chemicals have the same potency for bactericidal activity. However, the MIC values of these three compounds differed. Against S. aureus, the MIC value of (7, 10, and 11) was 0.316 ± 0.02, 2.50 ± 0.03 and 1.25 ± 0.01 mg/ml, respectively. The MIC values of compounds (7, 10, and 11) were the same, that is, 0.625 ± 0.04 mg/ml against S. aureus. The MIC values of (7 and 11) against P. aeruginosa and S. abony, respectively, were not determined because these compounds did not show activity against these bacteria. Thus, compounds 7, 10, and 11 were equally potent against most bacteria. The analysis of MIC and MBC values of 7 (4-t-butyl benzoyl) showed that compound 7 exhibited minimum MIC (0.316 ± 0.02 mg/ml) and the MBC of 0.625 ± 0.04 mg/ml against B. subtilis. By contrast, it showed the maximum MIC (0.625 ± 0.04 mg/ml) and the MBC of 1.25 mg/ml against S. aureus. Compound 7 showed equal MBC (0.625 ± 0.04 mg/ml) against B. subtilis and E. coli and MBC (1.25 ± 0.06 mg/ml) against S. abony and S. aureus. But 7 and 11 were inactive against S. abony and P. aeruginosa. Therefore, from the MIC and MBC values, these three compounds follow the order of 7 > 10 > 11 for bacteriostatic and bactericidal activities. Moreover, this antibacterial activity screening test suggested that the incorporation of various acyl groups in cytidine 1 highly increases the activity of this compound. Thus, these three compounds (7, 10, and 11) can be used as therapeutic antibacterial agents against various infectious diseases caused by the test organisms after the investigation of their side effects and other necessary experiments.

Determination of the in vitro antifungal activity

Table 4 and Figs. 6, 7 present the results of the inhibition of fungal mycelial growth. The antifungal screening data suggested that compounds 6 (68.06 ± 0.9%), 10 (76.13 ± 1.8%), and 14 (80.66 ± 1.1%) showed marked toxicities toward A. niger, which were even higher than the toxicity of the standard antibiotic, nystatin (66.40 ± 1.8%). By contrast, 13 (60 ± 1.9%) showed excellent inhibition against A. flavus, which was comparable to inhibition by nystatin (63.10 ± 1.9%). The analogs of compounds (12–14) (myristoyl, pivaloyl, and 4-chlorobenzoyl) showed activity against both A. niger and A. flavus. The rest of the compounds (1–3, 7–9, 11, and 15) showed no activity against both tested fungi. Other test compounds also showed a moderate to considerable antifungal activity against the tested fungi. The incorporation of myristoyl, pivaloyl, and 4-chlorobenzoyl groups at C-5′ and C-2,3′-di-O-positions of the tested compounds increased their antifungal activity againsttested organisms, which is considered similar by our previous findings (Misbah et al. 2020; Kawsar et al. 2018). Figure 3 presents the graphical results.

Table 4.

Antifungal growth inhibition (%) by the test compounds

Compound	% inhibition of fungal mycelial growth
	A. niger	A. flavus
1	NI	NI
2	NI	NI
3	NI	NI
4	*66.27 ± 1.8	NI
5	NI	55 ± 1.7
6	*68.06 ± 0.9	NI
7	NI	NI
8	NI	NI
9	NI	NI
10	*76.13 ± 1.8	NI
11	NI	NI
12	*66.13 ± 1.5	51 ± 1.3
13	*60.35 ± 1.7	*60 ± 1.9
14	*80.66 ± 1.1	55 ± 1.8
15	NI	NI
Nystatin	**66.40 ± 1.8	**63.10 ± 1.9

Data are presented as mean ± SD. Values are represented for triplicate experiments. Statistically significant inhibition (p < 0.05) is marked with one (*) and double (**) asterisk for test compounds and reference antibiotic nystatin, respectively. *Good inhibition; **standard antibiotic, NI no inhibition

Fig. 6.

Graph for the inhibition activity of the tested compounds against A. nigerand A. flavus

Fig. 7.

Inhibition of fungal growth observed in A. niger by the compound 14 (left); A. niger by the compound 13 (right)

The results showed that some of the newly synthesized acylated cytidine derivatives possess a wide range of antimicrobial activities and that the antimicrobial activities of cytidine derivatives depend on the type of substituents, the length of alkyl chains, and the number of acyl rings. Thus, cytidine derivatives (2–15) may be considered potential sources for developing new and better antimicrobial agents against numerous human and plant pathogenic microorganisms.

In vitro anticancer activity determination

The MTT assay was used to investigate the effect of compounds (2–15) in vitro on EAC cells. Among the fifteen compounds, only compound 6 [5′-O-decanoyl-2′,3′-di-O-(triphenylmethyl)cytidine] was potentially active. EAC cell death was dose-dependent (Fig. 4). At the concentrations of 500, 250, 125, 62.5, and 31.25 µg/ml, the inhibitory effect by compound 6 was 21.64%, 13.05%, 6.13%, 3.22%, and 2.15%, respectively. With the gradual decrease in concentrations, the inhibitory effect decreased and finally reached 1.32% at 15.625 µg/ml for compound 6 (Fig. 8). The IC₅₀ value of this compound was 1168.97 µg/ml.

Fig. 8.

Anticancer screening of compound 6. EAC cell growth inhibition was measured using the MTT assay (n = 6, mean ± SD)

The aforementioned results indicated that compound 6 showed mild anticancer activities among all the compounds listed in Schemes 1 and 2. Therefore, this compound can be a potential hit for the lead optimization step of anticancer drug discovery.

SAR study of antibacterial activity

Chemical structuresare interrelated for their biological activity, which has experienced significant concentration over the past years (Huseyin et al. 2019; Kumaresan et al. 2015). We attempted to determine the SAR of the tested chemicals based on our in vitro experimental results. The incorporation of different acyl groups, especially in the C-5′ position and later in C-3′ and C-2′ positions, increases the activity of the tested chemicals against bacteria and fungus. The test chemicals with more hydrophobic groups in their structure show higher activity than precursor 1, which shows relatively lower activity due to the presence of three free hydroxyl groups. Furthermore, when the hydroxyl group of C-5′ is blocked by a triphenylmethyl group and two hydroxyl groups, especially when C-2′ and C-3′ remain free, then compound 8 shows little activity (16 mm zone of inhibition against B. subtilis). The presence of different acyl groups instead of hydroxyl groups also leads to antibacterial activity enhancement. Compound 11 contains a triphenylmethyl group at the C-5′ position and a lauroyl group at C-2′ and C-3′ positions and shows the highest zone of inhibition of 27 mm against B. subtilis. Compound 8 contains a decanoyl group at the C-5′ position and an octanoyl group at C-2′ and C-3′ positions and shows a high zone of inhibition of 21 mm against B. subtilis. This acylation increases the hydrophobicity of molecules, which damages the lipid-like cell membrane of bacteria through hydrophobic interactions. Hydrophobicity is the primary contributor to antibacterial activity (Fig. 9). The hydrophobicity of materials as toxicity or alteration of membrane integrity is an important parameter to bioactivity because it is directly related to membrane permeation (Kim et al. 2007). Hunt (Hunt 1975) reported that the potency of aliphatic alcohols is directly related to their lipid solubility through hydrophobic interactions between the alkyl chains of alcohols and lipid regions in the membrane. The hydrophobic interaction might occur between the acyl chains of cytidine 1 accumulated in the lipid-like structure of bacterium membranes. As a consequence of their hydrophobic interactions, bacteria lose their membrane permeability, ultimately leading to bacterium death (Judge et al. 2013). Therefore, the activity order is 11 ˃ 8 ˃ 3 against B. subtilis. This result concluded that not only hydrophobicity but also aromatic nuclei increase the antibacterial activity of chemical substances. This finding led us to conclude that the incorporation of 2′,3′-di-O-octanoyl/lauroyl groups in the cytidine framework along with 5′-O-decanoyl/triphenylmethyl groups increased the antimicrobial potential of cytidine 1.

Fig. 9.

Structure–activity relationship of 3, 8, and 11 compounds against B. subtilis

Thermodynamic analysis

A frequent alteration of chemical structures significantly influences the structural characteristics including thermal and molecular orbital properties (Table 5). The spontaneityof reactionspontaneity and product stability can be calculated from free energy and enthalpy (Cohen and Benson 1993).

Table 5.

Stoichiometry electronic energy, enthalpy, Gibbs free energy in Hartree and dipole moment (Debye) of cytidine and its analogs

Entry	Stoichiometry	Electronic energy	Enthalpy	Gibbs free energy	Dipole moment
1	C9H13N3O5	− 885.9917	− 885.9907	− 886.04716	5.5936
2	C19H31N3O6	− 1334.3490	− 1334.3481	− 1334.4428	8.4365
3	C35H59N3O8	− 2106.7896	− 2106.7887	− 2106.9356	10.2747
4	C51H91N3O8	− 2731.9141	− 2731.9131	− 2732.1117	9.2219
5	C55H99N3O8	− 3768.8530	− 3768.8732	− 3768.8897	7.3568
6	C57H59N3O6	− 3438.2073	− 3438.1966	− 3438.3412	6.1439
7	C41H55N3O8	− 2347.7211	− 2347.7201	− 2347.8696	3.1182
8	C28H27N3O5	− 1598.1579	− 1598.1569	− 1598.2515	4.0776
9	C40H47N3O7	− 2230.2829	− 2230.2819	− 2230.4129	5.8594
10	C42H53N3O7	− 2308.4197	− 2308.4187	− 2308.5566	6.1603
11	C52H71N3O7	− 3514.2191	− 3514.1687	− 3514.3040	5.7035
12	C56H79N3O7	− 2855.4048	− 2855.4038	− 2855.5894	7.8364
13	C38H43N3O7	− 2152.1581	− 2152.1571	− 2152.2853	4.7864
14	C42H33N3O7Cl2	− 3213.7753	− 3213.7744	− 3213.9065	5.8436
15	C46H36N3O7	3054.2954	3054.2931	3054.5781	4.3428

Higher negative values (Table 5) can more easily provide thermal stability. In drug design, dipole moment influences hydrogen bond formation and non-bonded interactions. Relatively higher dipole moment can improve the binding property (Lien et al. 1982) of ligands. The highest free energy was (− 3768.8897 Hartree) observed for cytidine derivative (5), which also showed the highest enthalpy (− 3768.8732 Hartree) and highest electronic energy (− 3768.8532 Hartree) (Table 6). The highest dipole moment of 10.2747 Debye was observed for cytidine derivative (3), whereas (7) showed the lowest dipole moment of 3.1182 Debye (Table 6). These values gradually increased with the increasing length of carbon chains (1–6). The halogenated derivatives exhibited better free energy and dipole moment, as evidenced by compound (14) (4-Cl.Bz), which also had free energy higher than that of therapeutics under investigation and showed markedly improved dipole moment.

Table 6.

Molecular weight (g/mol), polarizability (a.u.), heat capacity (cal/mol-kelvin), entropy (cal/mol-kelvin) and total energy (Hartree) of the derivatives

Entry	Molecular weight	Polarizability	Heat capacity	Entropy	Total energy
1	242.22	118.4260	57.902	118.714	− 886.2448
2	397.47	225.6916	111.495	199.237	− 1334.8966
3	649.87	391.9563	190.192	309.199	− 2107.7845
4	874.30	553.4870	266.129	417.870	− 2733.3920
5	929.86	683.2014	359.428	542.794	− 3770.4751
6	882.11	601.0244	289.630	457.527	− 3441.2311
7	717.90	456.3486	201.138	314.633	− 2348.6922
8	485.54	301.4623	122.443	199.012	− 1598.7105
9	681.83	416.1610	180.641	275.714	− 2231.1499
10	709.87	433.5900	189.867	290.187	− 2309.3477
11	850.15	492.3496	328.548	384.653	− 3517.0978
12	906.26	583.4060	256.681	390.584	− 2856.7552
13	653.77	397.9823	174.519	269.802	− 2152.9623
14	762.64	456.6136	176.107	278.093	− 3214.4966
15	742.80	431.251	163.239	272.309	3055.9561

The physicochemical and thermophysical data (Table 6) showed that among all the modified derivatives, compound (5), which has the highest molecular weight (929.86 g/mol), shows the highest total energy (− 3770.4751), polarizability (683.2014 a.u.), heat capacity (359.428 cal/mol-kelvin), and entropy (542.794 cal/mol-kelvin). All the hetero-ring-containing derivatives (7, 14, and 15) show comparatively higher energy values. This result may reveal that with an increase in the molecular weight of cytidine derivatives, their stability increases and that the presence of heteroaromatic ring increases physicochemical properties. Moreover, the presence of bulky acylating groups suggested the possible improvement of polarizability. Finally, all the synthesized cytidine derivatives may be more stable than their parent structures.

Frontier molecular orbital analysis

Frontier molecular orbitals are the most significant orbitals in molecules and are used to predict chemical reactivity and kinetic stability. The Frontier molecular orbitals are known as HOMO and LUMO. Electronic absorption relates to the transition from the ground to the first excited state and is mainly described using the excitation of an electron from HOMO to LUMO (Saravanan and Balachandran 2014). With an increase in the HOMO–LUMO gap, kinetic stability increases. As a result, the release of electrons from stable state HOMO to excited state LUMO requires more energy. Table 7 presents the values of orbital energies and two global chemical descriptors, hardness, and softness, which are calculated for all cytidine derivatives.

Table 7.

Energy (eV) of HOMO, LUMO, energy gap, hardness, and softness of cytidine and its derivatives

Entry	εHOMO	εLUMO	Gap	Hardness (η)	Softness (S)
1	− 6.4106	− 0.9796	5.4310	2.7155	0.3683
2	− 5.6416	0.5644	5.0772	2.5386	0.3939
3	− 5.8245	0.7559	5.0686	2.5343	0.3946
4	− 5.8152	− 0.7962	5.0190	2.5095	0.3985
5	− 6.3340	− 0.9320	5.4020	2.7010	0.3702
6	− 6.1597	− 1.1969	4.9628	2.4814	0.4029
7	− 5.9162	− 1.4194	4.4968	2.2484	0.4448
8	− 5.3267	− 0.3804	4.9463	2.4731	0.4044
9	− 5.9847	− 0.5685	5.4162	2.7081	0.3693
10	− 6.0209	− 0.5973	5.4236	2.7118	0.3688
11	− 6.1841	− 1.7823	4.4018	2.2009	0.4543
12	− 5.9700	− 0.5864	5.3836	2.6918	0.3715
13	− 5.9989	− 0.6357	5.3632	2.6816	0.3729
14	− 6.1202	− 1.8158	4.3044	2.1522	0.4647
15	− 6.2134	− 0.8415	5.3719	2.6859	0.3723

Compound (14) exhibited the highest softness and the lowest HOMO–LUMO gap (4.3044 eV) and hardness, which indicatedthat the molecule is more reactive than other compounds, according to Pearson et al. (Hoque et al. 2015; Parr and Zhou 1993).

By contrast, derivative (10) showed the highest HOMO–LUMO gap (5.4236 eV), which was nearest to the mother compound cytidine (1) (5.4310 eV), indicating that the stability of derivative (10) was closerto that of cytidine (1). The LUMO plot of compound (10) shows that electrons were localized at the modified upper part of the cytosine ring only, while the HOMO plot shows that electrons were localized on both the acyl group region and cytosine ring (Fig. 10). Figure 11 represents the density of states (DOS) plot for the highest and lowest energy gaps of the modified derivatives.

Fig. 10.

Molecular orbital distribution plots of HOMO and LUMO of cytidine (1) and its analogs (10)

Fig. 11.

DOS plot and HOMO–LUMO energy gap of (10) and (14)

Molecular electrostatic potential (MEP)

In the computer-aided drug design, atomic charges are employed to investigate the connectivity between the structure and biological activity of drugs. The molecular electrostatic potential (MEP) is globally used as a reactivity map displaying the most suitable regions for the electrophilic and nucleophilic attack of charged-point-like reagents on organic molecules (Amin 2013). MEP helps interpret the biological recognition process and hydrogen bonding interactions (Politzer and Murray1991). MEP counter map provides a simple approach to predict how different geometries can interact. The MEP of the title compound was obtained based on the B3LYP with the basis set 3-21G optimized result (Fig. 12). MEP is important because it simultaneously displays the molecular size and shape, and positive, negative, and neutral electrostatic potential regions in terms of color grading and is considered useful for studying molecular structures with physicochemical property relationship (Kawsar et al. 2020; Politzer and Truhlar 2013). MEP was calculated to predict the reactive sites for the electrophilic and nucleophilic attacks of the optimized structure of cytidine analogs (2, 3, 4, and 12). The red color representsthe maximum negative area, which shows a favorable site for electrophilic attacks, the blue color indicates the maximum positive area favorable for nucleophilic attacks, and the green color represents zero potential areas.

Fig.12.

MEP map of cytidine analogs (2, 3, 4, and 12)

In silico molecular docking analysis

Among all the derivatives, the synthesized cytidine derivatives (5, 12, 13, and 14) showed better biological activity against A. flavus bacteria. We performed in silico molecular docking for these compounds against an A. flavus cell protein 1R51 to investigate their binding mode and non-bonding interactions. Molecular docking analysis revealed that cytidine (1), which was inactive in the antifungal test, showed the lowest binding affinity of − 6.2 kcal/mol and the binding affinities of others derivatives decreased from compound 5 to 14 in the order of − 6.4 >  − 6.5 >  − 7.6 >  − 8.8 kcal/mol (Table 8).

Table 8.

Binding affinity (kcal/mol) and non-bonding interactions of cytidine and its analogs

Entry	Protein	Binding affinity	Residues in contact	Interaction types	Distance (Å)
1	1R51	− 6.2	Glu31	H	2.462
			Trp106	H	2.373
			Val73	H	2.349
			Val29	H	2.972
			Pro76	A	5.114
			Cys103	A	4.343
			Tyr30	PA	4.948
5	1R51	− 6.4	Arg108	H	2.436
			Arg108	H	2.755
			Arg108	H	2.556
			Lys17	A	3.760
			Val73	A	5.041
			Tyr30	PA	4.905
			Tyr30	PA	4.588
12	1R51	− 6.5	Phe258	PSi	3.924
			Phe159	PPS	3.975
			Phe159	PPS	5.555
			Leu170	A	3.975
			Arg176	A	4.031
			Leu170	A	5.072
			Lys171	A	4.100
			Pro284	A	5.483
13	1R51	− 7.6	Trp106	C	3.485
			Trp208	PPTs	5.374
			Tyr30	PPTs	5.290
			Cys103	PA	5.442
			Arg105	PA	4.180
			Arg128	PA	4.460
			Cys103	PA	4.200
			Trp208	PA	5.375
14	1R51	− 8.8	Asp165	H	2.602
			Thr168	H	2.838
			Asp165	H	2.842
			Thr169	H	2.209
			Leu170	H	2.429
			Leu170	PSi	3.820
			Phe159	PPTs	3.851
			His256	PPTs	4.045
			Phe159	PPTs	5.123
			Leu170	PA	5.326
			His256	PA	5.378
			Phe258	PA	4.665

H conventional hydrogen bond, C carbon hydrogen bond, A alkyl, PA pi-alkyl, Psi Pi-sigma, PPS Pi–Pi stacked, PPTs Pi–Pi T-shaped. Tyr tyrosine, Cys cysteine, His histidine, Arg arginine, Leu leucine, Thr threonine, Val valine, Trp tryptophan, Phe phenylalaine, Pro proline, Lys lysine, Glu glutamic acid, Asp aspartic acid

The structural comparison showed that compound (14) has an additional aromatic (cinnamoyl ring) substituent in the cytidine structure, which providesit a high density of electrons in the molecule leading to the highest binding affinity (Fig. 13). To predict the shape and behavior of molecules, non-bonding interactions are widely used (Fig. 14). Among all non-bonding interactions such as hydrogen bond (conventional hydrogen bond, carbon-hydrogen bond) and hydrophobic interactions (alkyl, Pi-alkyl, Pi-sigma, Pi-Pi stacked, and Pi-Pi T-shaped), alkyl Pi-alkyl and Pi–Pi T-shaped interaction is most common in ligand–protein interactions. A molecule of parent ligand cytidine (1) interacted with the Val73 moiety of the protein including one intensive interaction within a short distance of 2.34974 Å. Besides, tryptophan and glutamic acid interactions were observed where Trp106 was close (2.37338 Å) due to the interaction of the branched acyl chain with the cytosine ring.

Fig.13.

Docked conformation of compound (14) at the inhibition bounding site of 1R51 (A) and superimposed view of all compounds after rigid docking (B)

Fig. 14.

Non-bonding interactions of compound (13) and (14) with the amino acid residues of 1R51 generated through Discovery Studio

Compared with parent ligand (1), compound (5) mostly exhibited hydrophobic interactions such as alkyl and Pi-Alkyl and showed most of the interactions for Arg108 with a closed distance of 2.43675 Å. Similar to the parent ligand; it interacted with amino acid residue Tyr30. Compounds (12) and (13) exhibited new types of interaction such as Pi–Sigma, Pi–Pi stacked and Pi–Pi T-shaped interactions, and all these interactions were hydrophobic. Compound (12) mostly interacted with the residues of phenylalanine (Phe258 and Phe159) with a short distance of 3.92416 Å, but compound (13) interacted with tryptophan residues (Trp106 and Trp208) because the structural requirement of two compounds (12 and 13) allowed small amino acids in the vicinity of the neighboring drug moiety. Moreover, compound (13) showed an interaction with the Tyr30 moiety similar to compounds (1 and 5). Finally, compound (14) with the highest binding affinity showed both hydrogen and hydrophobic interactions due to structural conformation. Phe159, Asp165, and Leu170 are the most common moieties that were observed with closed distance interactions for Thr169 of 2.20921 Å. Binding affinity and binding specialty increased for all compounds due to significant hydrogen bonding.

The molecular docking analysis revealed Tyr30, Phe159, and Leu170 as the major and common residues of the 1R51 active site is according to various non-bonding interactions with the ligand (Table 9). Hydrogen bonds perform a vital function in shaping the specificity of ligand binding with the receptor, drug design in chemical and biological processes, molecular recognition, and biological activities (Perlstein et al. 2001). The hydrogen bond surface and hydrophobic surface of compound (14) (Figs. 15, 16) represent the ionizability surface and solvent accessibility. Although compound (14) showed mostly hydrogen type non-bonding interactions, it has considerable hydrophobicity due to the presence of the heteroaromatic ring.

Table 9.

Pharmacokinetic properties of cytidine and its analogs

Entry	BBB	Human intestinal absorption	P-glycoprotein inhibitor	hERG	Carcinogen	Acute oral toxicity
1	+ (0.9862)	+ (0.9141)	NI(0.9526)	WI(0.7018)	NC(0.9857)	III
2	+ (0.9705)	+ (0.9364)	NI(0.6499)	WI(0.5708)	NC(0.9571)	III
3	+ (0.9828)	+ (0.9766)	NI(0.7593)	WI(0.5945)	NC(0.9286)	III
4	+ (0.9828)	+ (0.9766)	NI(0.7486)	WI(0.6159)	NC(0.9286)	III
5	+ (0.9828)	+ (0.9766)	NI(0.7483)	WI(0.6214)	NC(0.9286)	III
6	+ (0.9824)	+ (0.9730)	NI(0.8501)	WI(0.8434)	NC(0.9429)	III
7	+ (0.9785)	+ (0.9686)	NI(0.8232)	WI(0.8538)	NC(0.9000)	III
8	+ (0.9717)	+ (0.9394)	NI(0.5842)	WI(0.5703)	NC(0.9571)	III
9	+ (0.9815)	+ (0.9730)	NI(0.8819)	WI(0.8432)	NC(0.9429)	III
10	+ (0.9815)	+ (0.9730)	NI(0.8673)	WI(0.8392)	NC(0.9429)	III
11	+ (0.9815)	+ (0.9730)	NI(0.8121)	WI(0.6625)	NC(0.9429)	III
12	+ (0.9815)	+ (0.9730)	NI(0.7765)	WI(0.4075)	NC(0.9429)	III
13	+ (0.9735)	+ (0.9703)	NI(0.8487)	WI(0.8232)	NC(0.9000)	III
14	+ (0.9794)	+ (0.9603)	NI(0.8458)	WI(0.7613)	NC(0.9286)	III
15	+ (0.9793)	+ (0.9128)	NI(0.8648)	WI(0.8280)	NC(0.8167)	III

 + positive, I inhibitor, NI non-inhibitor, WI weak inhibitor, NC non-carcinogenic, III category III includes compounds with LD50 of > 500 mg/kg but < 5000 mg/kg

Fig. 15.

Hydrogen bond and hydrophobic surface of 1R51 with compound (14)

Fig. 16.

Ionizability and solvent accessibility surface of 1R51 with compound (14)

Pharmacokinetic analysis

Pharmacological properties were predicted to compare the absorption, metabolism, and toxicity among all cytidine derivatives. Some recent studies revealed that the modified nucleoside derivatives possessed promising pharmacokinetic profiles (Alam et al. 2021; Kawsar et al. 2020a, b; Bulbul et al. 2021). Generally, drug-likeness is evaluated using Lipinski's rule of five (Lipinski et al. 2001). An orally active drug should have no more than one interruption of the following conditions: (1) ≤ 5 hydrogen bond donors, (2) ≤ 10 hydrogen bond acceptors, (3) molecular mass of < 500 Da; and (4) an octanol–water partition coefficient of ≤ 5. If two or more of these conditions are not satisfied, reduced absorption can be estimated. AdmetSAR calculations (Table 9) indicated that these cytidine derivatives are non-carcinogenic and possess category III oral toxicity; thus, cytidine derivatives may be harmless for oral administration. All drugs are P-glycoprotein non-inhibitors where P-glycoprotein inhibitor can interrupt the absorption, permeability, and retention of drugs. All drugs show positivity, allowing for blood–brain barrier. However, all these derivatives show weak inhibitory characteristics for human ether, a gogo-related gene (hERG). The inhibitory feature of hERG can cause long QT syndrome (Kawsar et al. 2020; Sanguinetti and Firouz 2006); therefore, this aspect must be further investigated. Moreover, all derivatives were evaluated with the SwissADME web tool (Table 10) for their drug-likeness and pharmacokinetics properties, which are crucial for rational drug design.

Table 10.

Oral bioavailable parameter of cytidine and its analogs

Entry	Molar Refractivity (Å)	Log Po/w (XLOGP3)	NRB	NHA	NHD	TPSA (Å2)	Csp3
1	55.85	− 2.13	2	6	4	130.83	0.56
2	104.04	1.78	12	7	3	136.90	0.74
3	181.20	9.27	28	9	1	149.04	0.80
4	258.11	17.93	44	9	1	149.04	0.86
5	277.34	20.10	48	9	1	149.04	0.87
6	260.19	12.53	22	7	1	114.90	0.28
7	201.86	9.94	20	9	1	149.04	0.54
8	133.92	2.88	7	6	3	119.83	0.21
9	191.85	7.66	19	8	1	131.97	0.40
10	201.47	8.74	21	8	1	131.97	0.43
11	249.54	14.16	31	8	1	131.97	0.54
12	268.76	16.32	35	8	1	131.97	0.57
13	181.72	6.64	13	8	1	131.97	0.37
14	203.22	8.41	13	8	1	131.97	0.14
15	212.62	8.00	15	8	1	131.97	0.13

NHD no. of H-bond donors, NHA no. of H-bond acceptor, NRB no. of rotatable bonds, TPSA topological polar surface area, Csp3 fraction of sp³ carbon atom

However, topological polar surface area (TPSA) was employed as a contributing factor for oral absorption and blood–brain barrier permeation capacity, and the screened drug-likeness of molecules should have TPSA between 130 and 150 Ų. The prediction obtained using the SwissADME web tool revealed that all ligands exhibiteda standard value in this range and showed better TPSA than the parent ligand. The molar refractivity and fraction of the sp³ carbon atom of all derivatives increased with the molecular weight.

This promising context would be more interesting if we could validate the study by QSAR and molecular dynamics simulation. However, more experimental tests and theoretical investigations should be carried to confirm the effect of these compounds on urate oxidase (A. flavus 1R51) enzyme and antioxidant properties. Besides, more in silico, in vitro, and in vivo studies will be conducted in the forthcoming manuscript to assess the drug-likeness of cytidine analogs.

Conclusions

In conclusion, the antimicrobial activity results indicated that some of the new cytidine analogs may exhibit a wide range of antimicrobial activities. The antimicrobial screening results indicated that tested compounds 7 (4-t-butylbenzoyl-), 10 (heptanoyl-), and 11 (lauryl-) have a promising biological activity and are potential sources of antimicrobial agents in the microbiology field. The most significant features for biological chemistry, such as chemical reactivity and frontier orbital studiesincluding HOMO, LUMO, HOMO–LUMO gap, and molecular electrostatic potential of molecules were optimized, which indicated that the cytidine analogs can be regarded as good drug molecules. Numerous designed cytidine analogs have HOMO–LUMO energy gapssimilar to cytidine (1) and have exalted pharmacokinetic properties than the parent ligand does. As a result, some modified cytidine analogs,which show lower HOMO–LUMO energy gaps, may become more reactive than cytidine and some can be stable similar to cytidine (1). Moreover, the docked complex of analogs (12, 13, and 14) with 1R51 exhibits better binding affinity with significant non-bonding interactions than the parent molecule does. Based on the above observations, our docking results revealed that compounds 12, 13, and 14 are more active than compound 5, suggesting those as potential antioxidants and inhibitors of A. flavus. The results of the MEP study showed the most negative and positive surface areas of the investigated ligandsto anticipate suitable hydrogen bonding sites. The ADMET analysis result suggested that the modified analogs were less toxic than the parent drug and exhibit an improved pharmacokinetic profile. In addition, structural modifications of cytidine molecules with different aliphatic and aromatic groups may reveal probable antimicrobial candidates. Finally, this study will be useful to realize the chemical, thermal, physicochemical, biological, and pharmacokinetic properties of cytidine analogs.

Supplementary Information

Below is the link to the electronic supplementary material.

Abbreviations

EAC

Ehrlich ascites carcinoma

MTT

[3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide]

MIC

Minimum inhibitory concentration

MBC

Minimum bactericidal concentration

DFT

Density functional theory

HOMO

Highest occupied molecular orbital

LUMO

Lowest unoccupied molecular orbital

QM

Quantum mechanical

LYP

Lee, Yang and Parr’s

MEP

Molecular electrostatic potential

DOS

Density of states

ADMET

Absorption, distribution, metabolism, excretion, and toxicity

hERG

Human ether-A-Go-Go-related gene; BBB: Blood brain barrier

Author contributions

SMAK and KMR designed and planned the experiments; KMR, JM, and AA performed the synthetic and computational experiments; SD and KMRconducted biological evaluation; AH, SMAK, YO interpreted the data and wrote the paper; and YF and IH edited the manuscript. All authors have read and approved the final version of the manuscript.

Declarations

Conflict of interest

The authors declare that they have no conflict of interest.