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. 2023 Feb 12;103:107827. doi: 10.1016/j.compbiolchem.2023.107827

Designing of thiazolidinones against chicken pox, monkey pox, and hepatitis viruses: A computational approach

Muhammad Asam Raza a,⁎, Umme Farwa a, Fatima Ishaque a, Abdullah G Al-Sehemi b
PMCID: PMC9922439  PMID: 36805155

Abstract

Computational designing of four different series (D-G) of thiazolidinone was done starting from different amines which was further condensed with various aldehydes. These underwent in silico molecular investigations for density functional theory (DFT), molecular docking, and absorption, distribution metabolism, excretion, and toxicity (ADMET) studies. The different electrochemical parameters of the compounds are predicted using quantum mechanical modeling approach with Gaussian. The docking software was used to dock the compounds against choosing PDB file for chickenpox, human immunodeficiency, hepatitis, and monkeypox virus as 1OSN, 1VZV, 6VLK, 1RTD, 3I7H, 3TYV, 4JU3, and 4QWO, respectively. The molecular interactions were visualized with discovery studio and maximum binding affinity was observed with D8 compounds against 4QWO (-13.383 kcal/mol) while for compound D5 against 1VZV which was −12.713 kcal/mol. Swiss ADME web tool was used to assess the drug-likeness of the designed compounds under consideration, and it is concluded that these molecules had a drug-like structure with almost zero violations.

Keywords: Thiazolidinone, Molecular Docking, DFT, ADMET, Chickenpox, Monkey Pox

Graphical Abstract

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1. Introduction

A serious and growing hazard to public health across the world is the introduction of novel viral diseases (Tang et al., 2020). The figure of the newly emergent infectious diseases (EIDs) has been increasing decade by decade and will stay to increase in near future according to an analysis of recent patterns in emerging illnesses (Pybus and Rambaut, 2009). Those organisms which cannot be seen without a microscope are called microorganisms, divided into five classes bacteria, protozoa, algae, fungi, and viruses (Ingraham, 2018). Bergh and his fellows used transmission electron microscopy to say that approximately 10 million viruses-like particles (VLP) per mL of sea water in 1989 (Bergh et al., 1989). Approximate 1031 viruses are present on earth but most of them are bacteriophages because they affect the bacteria (Breitbart and Rohwer, 2005), bacteriophages killed 4–50 % of bacteria every day (Heldal and Bratbak, 1991, Steward et al., 1992).

The virus only multiplies within the cell of micro and macro-organisms. They hold capsid proteins that encircle the nucleic acid, DNA or RNA and outer lipid envelop. They are divided into enveloped and non-enveloped based on the presence or absence of a lipid envelope. Hepatitis B and C, Measles, Dengue, Chicken pox, Monkeypox, Influenza, Ebola, and Covid-19 are the most common pathogenic enveloped viruses in humans. Animals and even directly humans (fecal-oval route, sexual contact, sneezing, coughing, or blood transfusion) are vectors for the transmission of these viruses (Rai et al., 2020). Genetic complexity caused harmful effects when it is transferred from one organism to another, for example, COVID-19 is more pathogenic because it is transferred from bats to humans (Lau et al., 2005, Rai et al., 2020, Ren-LL and Wu, 2020).

Monkeypox (MPX) is a member of the orthopox virus genus in the Poxviridae family which caused the monkeypox virus (MPXV) (Marennikova and Moyer, 2005). The natural host of the monkeypox virus is unknown but it can infect a wide range of mammalian species. MPXV is separate from wild animals, a sooty mangabey on the Ivory coast (Cao-Lormeau et al., 2014), and a rope squirrel in the Democratic Republic of Congo (Khodakevich et al., 1986). Dehydration, corneal infection with loss of vision, respiratory distress, gastrointestinal involvement, secondary bacterial infection, and bronchopneumonia are caused by MPXV. Symptoms that are found in infected persons are given in Fig. 1. Symptomatic and supportive care treatment only methods exist currently for the treatment of monkeypox virus (Reynolds et al., 2017).

Fig. 1.

Fig. 1

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Symptoms of monkeypox virus infection (Pastula and Tyler, 2022).

Body fluids, respiratory droplets, and contaminated material such as clothing and bedding are common causes of the transmission from human to human (Petersen et al., 2019, Shanmugaraj et al., 2022). Almost 3000 cases of monkeypox had been reported to WHO on 25 June 2022 from 47 countries; however, by 23 July 2022, that number had risen to almost 16,000 cases from 75 countries and territories, resulting in five mortalities (Taylor, 2022). Different countries confirmed monkeypox outbreaks in humans between August 1970 - May 2018, as depicted in Fig. S1(A) while cases between January 2017 - May 2018 are also depicted (Fig. S1(B)), However, estimated confirmed cases of monkeypox from the DRC since 2005 (Sklenovska and Van Ranst, 2018).

The chickenpox virus is caused due to varicella-zoster virus. It is a double-stranded DNA virus, that caused red blisters and itchiness in the whole body, sneezing, coughing, contact with fluid from a blister, saliva, and coughing are common causes of the spread of this virus. The risk of an attacked virus is less if vaccination is given or it has already been attacked in past (Lipsky et al., 2012, Qureshi and Yusuf, 2019). Varicella is a global disease, there are regional and geographic variations in its epidemiology, particularly between temperate and tropical areas. In the pre-vaccination era, more than 90 % of persons in temperate nations like the US and the UK were affected before puberty (Hambleton and Arvin, 2005). On the other hand, chickenpox infection occurs at longer ages in tropical non-developed locations, and pregnant women are infected in tropical areas. In addition, pregnant women are five times more likely to die from chickenpox as compared to a non-pregnant female. Another distinction is that varicella infection is more prevalent in temperate climates in the winter and early spring. The disease is uncommon in children in nations that have implemented a universal immunization program, while minor outbreaks can happen (Kadri et al., 2017).

The World Health Organization estimates that each year, 4.2 million serious problems that cause hospitalization and 4200 deaths are directly related to varicella. The high-income countries should give the residual burden of chickenpox considerable consideration (Hambleton and Arvin, 2005, Kadri et al., 2017). In the Kashmir Region, 30 % of the outbreak’s cases were due to chickenpox in the last year. These cases over three years, from January 2013 to December 2015 (eighty, ninety-seven, and one hundred twenty-nine cases respectively). According to Fig. 2, there were steady numbers of attacks (seven, six, and seven) (Kadri et al., 2017).

Fig. 2.

Fig. 2

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Total Number of Varicella Attacks and Cases during 2013–2015, Kashmir India (Kadri et al., 2017).

Hepatitis is considered the most fatal illness, and its symptoms, early identification enhances the likelihood of multiple curing (AbuSharekh and Abu-Naser, 2018). The inflammation and cell death caused by liver major damage occurred mostly by hepatitis (Webster et al., 2019). Hepatitis viruses comprise of mainly five forms as A, B, C, D, and E, acute types of hepatitis are A and E which are different from chronic hepatitis B, C, and D (Jalil al., 2020). The number of infected people with HBV worldwide is now greater than two billion individuals have been revealed and many of them have serological signs of prior infection (Razavi-Shearer et al., 2018). Primary liver cancer, the sixth-most frequent malignancy globally, has been linked to chronic HBV infection (Valery et al., 2018). Additionally, it causes 786,000 HBV-related fatalities annually, ranking it as the tenth most common cause of death globally. Hepatocellular carcinoma (HCC) and HBV-related mortality are among the problems that 15–40 % of patients with chronic HBV infection may experience during their lifetimes (Abara et al., 2017).

Human immunodeficiency virus is the source of Acquired Immunodeficiency Syndrome (AIDS) (HIV-1) and the biological effects of thiazolidinone and pyrazine pharmacophore exhibited anti-HIV potential (Asgaonkar et al., 2019). Despite the envelope protein of the human immunodeficiency virus exhibiting up to roughly 40 % sequence variation among strains and these variables may raise the risk of severe respiratory syndrome coronavirus in people living with HIV and SARS-CoV-2 (Dandachi et al., 2021). Globally, there were 36.9 million HIV-positive individuals as of 2017, with the bulk of infections occurring in sub-Saharan Africa (Bbosa, Kaleebu, and Ssemwanga, 2019). Around the world, 1.7 million teenagers between the ages of 10–19 were predicted to be HIV-positive in 2019. About 90 % of them lived in sub-Saharan Africa, while 8 % in Asia and the Pacific (Marsh et al., 2019, Slogrove et al., 2018).

The primary structural component of the majority of medications that are currently on the market is heterocyclic compounds (Farwa and Raza, 2022, Martins et al., 2015). According to a database analysis of U.S. FDA-approved medications, almost 59 % of minor molecule medications comprise nitrogen-based heterocyclic rings (Vitaku et al., 2014). Many different thiazolidinone derivatives were synthesized or designed in the last ten years for use in medicine. Thiazolidinone molecules, which include a pentagonal sulfur ring, are mostly employed for biological action.

Thiazolidinone-derived moieties have significant biological action in the recent era for example in antioxidants, anti-inflammatory, anti-diabetics (Raza et al., 2022), analgesic, antitumor, antimicrobial (Pucci et al., 2004), cystic fibrosis transmembrane conductance regulator (CFTR), peroxisome proliferator activator gamma receptor (PPAR) (Hosseinzadeh et al., 2013), and agonist for follicle-stimulating hormone (Jain et al., 2012, Tripathi et al., 2014) and thiazolidinone derivatives were used as an effective drug moiety (Nirwan et al., 2019).

In the current computational research work, all 44 compounds were theoretically designed, their density functional study was done using Gaussian 09 to optimize compounds. Compounds were docked with Molecular Operating Environment (MOE) software using PDB files of viruses:1OSN, 1VZV, 6VLK, 1RTD, 3I7H, 3TYV, 4JU3, and 4QWO. In silico adsorption, distribution, metabolism, excretion, and toxicity (ADMET) study of compounds using swissADME online web tool while the toxicity of compounds was checked using Protox-II Online available tool.

2. Methods and materials

2.1. Designing of thiazolidinone derivatives

The designing of thiazolidinone-based compounds as 3-(4-Methylphenyl)-2-thioxo-1,3-thiazolidin-4-one, (5Z)-5-(2-Hydroxy­benzyl­idene)-3-phenyl-2-thioxo-1,3-thia­zolidin-4-one, 1a-4a, 1b-4b, and 1–4c were accomplished employing previously stated three-step scheme of our research team (Aisha, Raza et al., 2020, Shahwar et al., 2010, Shahwar et al., 2009, Shahwar et al., 2009). D, E, F, and G series were planned corresponding to the aforementioned protocols via three steps which again react with distinct aldehydes to transform them into their corresponding compounds as mentioned in the synthetic Scheme 1.

Scheme 1.

Scheme 1

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The synthetic scheme for the synthesized and proposed compounds.

2.2. Density functional theory

Gaussian 09 was used for the quantum chemical calculation and the result was viewed with Gauss View 6.0 (Biczysko et al., 2010). Gauss View 6.0 helped to visualize the results of optimization (Frisch et al., 2009). To optimize the geometry of compounds hybrid functional B3LYP and 6–31 G (d, p) basic set was used without symmetry resistance (Hariharan and Pople, 1973, Lee et al., 1988). The basic set 6–31G (d, p) helped to choose the polarized function on all atoms. Frequency calculation is used to determine the structure as true minima (Aisha, Raza et al., 2020, Hariharan and Pople, 1973, Ilyas et al., 2017, Sherzaman et al., 2017).

2.3. Docking studies

Docking experiments were performed with the help of molecular docking environment (MOE) software. PDB codes; 1OSN, 1RTD, 1VZV, 3I7H, 3TYV, 4JU3, 4QWO, and 6VLK crystal structures were selected. Firstly, removed all water molecules in the protein molecule and then added all hydrogen atoms. Optimization of energy was carried out with help of the default force field process (De Graaf et al., 2005). The default parameter of the MOE energy minimization algorithm (gradient: 0.005, Force Field: MMFF94X) was used for energy minimization and protonation of downloaded enzymes. The ligand interaction module of MOE helped to determine 2D ligand enzyme interaction (Raza et al., 2023). Discovery studio visualizer and MOE are used to visualize the analysis and docking result with graphical representation (Raza et al., 2020). The highest affinity showed the best conformation between ligand-protein complex were determined by selecting the docking score (Tallei et al., 2020).

2.4. Homology study

Homology study is an approach which constructs a 3D model using a target sequence of interest, depending on 3D protein or target structure of an alike protein (Yang et al., 2021). The basic building blocks of biological structure and function are protein sequences. Homology study done using Swiss model expasy (https://swissmodel.expasy.org/) a web server. Swiss model is an automated comparative protein modelling server freely accessible to noncommercial users. A sequence identity of 35 % or higher considered rule of thumb for reliable homology modelling (E Lohning et al., 2017).

2.5. Adsorption, distribution, metabolism, excretion, and toxicity study

Pharmacokinetics and physiochemical properties of the designed compounds determined with in-silico ADME study. It helps in the identification of those unknown chemical substances that are important for drug discovery. Drug-like characteristics such as permeability, absorption, bio-availability, pka, plasma-protein binding, lipophilicity, metabolism, molecular weight, synthetic accessibility, and blood-brain-barrier were studied using this tool. ADMET of thiazolidinone was calculated with the Swiss online software http://www.swissadme.ch/ (Dege et al., 2021, Raza and Fatima, 2020). Moreover, in silico toxicity estimation was conducted also using ProTox-II online available servers https://tox-new.charite.de/protox_II/ (Prnová et al., 2019).

3. Results and discussion

Our research team is constantly developing and synthesizing novel chemicals that might be utilized as inhibitors for a variety of disorders. The current endeavor is a piece of our ongoing research to discover a novel powerful chemical with a favorable effect on several enzymes using clinical methodologies against humans. The 44 compounds belonging to 4 series (D-G) were selected and alike compounds were even synthesized in a wet laboratory and already reported by our research group (Aisha, Raza et al., 2020, Shahwar et al., 2010, Shahwar et al., 2009, Shahwar et al., 2009). Although, four series of remaining compounds were also designed because they comprise a comparable core of skeleton with previously described compounds (Raza et al., 2022).

3.1. Density functional theory

Density functional theory (DFT) is applied around the world to optimize and analyze the electrochemical functionalities of compounds (Abdulridha et al., 2020, Balakit et al., 2020, Schwarz, 2003). It is a computational-based tool for simulating quantum mechanical attributes of chemical substances. Several inhibitors' structures were proposed and optimized using DFT approaches. Among other parameters i.e., electronegativity (x), chemical hardness (ŋ), chemical potential (µ), ionization potential (IP), and electron affinity (EA) were determined and values are enlisted in a systematic manner in Tables S1, S2, S3 and S4. However, Fig. S2 depicts the ideal optimal structure of the compounds.

Frontier molecular orbitals (FMO) are described as both the highest occupied molecular orbitals (HOMO) and lowest unoccupied molecular orbitals (LUMO) and have the potential to donate electrons and accept respectively. With the use of FMO, the electron density in orbitals of molecules is measured easily (Belkafouf et al., 2019, Megrouss et al., 2019). Energy Gap (E) between the highest occupied and lowest unoccupied in FMOs can be calculated, and Fig. S3 depicted the diagram of the energy gap.

According to the findings, the F7 molecule showed the greatest HOMO energy (−0.19801) of any of the series. For first series of 4-aminobenzoic acid based thiazolidinone the decreasing order of HOMO values as: D7  > D9 > D6 > D8 > D5 > D10 > D3 > D2 > D > D4 > D1 and for the second series of ammonia-based thiazolidinone, the order is E7 > E9 > E6 > E8 > E5 > E10 > E3 > E2 > E4 > E > E1 and for F series aniline based thiazolidinone compounds the order of HOMO: F7 > F9 > F6 > F8 > F5 > F10 > F3 > F2 > F > F4 > F1 and for phenylmethanamine based G series compounds G7 > G9 > G6 > G8 > G5 > G10 > G3 > G2 > G4 > G > G1.

The order of values of LUMO for D series compounds is D > D7 > D2 > D9 > D5 > D8 > D6 > D10 > D1 > D3 > D4, for the second E series compounds the order is E7 > E > E2 > E9 > E5 > E8 > E6 > E10 > E3 > E1 > E4, for the third F series compound the decreasing order of LUMO:F > F7 > F2 > F9 > F5 > F8 > F6 > F10 > F1 > F3 > F4 and for G series are G > G7 > G2 > G9 > G5 > G8 > G6 > G10 > G1 > G3 > G4.

When there is no substitution on the thiazolidinone ring in any of the four compounds, namely D, E, F, and G, the value of LUMO is found to be highest while the HOMO values are found to be lowered. The greatest values of HOMO were found for D7, E7, F7, and G7 while the values of LUMO were also greater but lower than D, E, F, and G due to extremely strong -I group. In the presence of a weak –I group, for example, acetaldehyde, benzaldehyde, and formaldehyde, then its values dropped as in the case of the D series however, when there are strong –I group, for example, 2-hydroxybenzldehyde, 4-hdroxbenzldehyde, 4-methoxybenzldehyde, 4-hydroxy-3-methoxy benzaldehyde, present then it was also seen that energy gap between HOMO and LUMO was also enhanced (Raza and Fatima, 2020).

The energy gap is the difference between (HOMO-LUMO) energy orbitals as the value of the energy gap is high the compounds are found to be more stable. The energy gap in the series of D compounds ranges between 0.15403 and 0.11292, E series compound 0.15675–0.11348, F series 0.15356–0.1143 while in G series 0.15514–0.11307. It was concluded from energy gap values that compounds D, E, F, and G are most stable while the others D7, E7, F7, and G7 are found to be more reactive due to their higher potential of electron transfer from HOMO to LUMO orbitals and a similar energy gap and relation with the stability of compounds was also observed.

The number of electrochemical properties was determined for all compounds using the Koopmans theorem, and their formulas are presented as;.

Electron Affinity (EA) = -ELUMO (1)
Ionization potential (IP) = -EHOMO (2)
Chemical Potential (µ) = [EHOMO + ELUMO] / 2 (3)
Chemical Hardness (ŋ) = - [ELUMO – EHOMO] / 2 (4)
Electronegativity (x) = - [EHOMO + ELUMO] / 2 (5)

The chemical reactivity and softness of the compounds were determined by the energy gap, and the global reactivity parameters which take into account electron affinity, and ionization potential which were also calculated with the assistance of these factors. The harder the behavior of the molecules as greater the energy gap and vice versa.

The results showed that proposed molecules can be easily synthesized in wet laboratories, because these compounds have IP values for D - D10 series compounds are 0.23939, 0.24139, 0.23655, 0.23511, 0.24044, 0.22847, 0.2259, 0.20225, 0.2269, 0.22342 and 0.23102 respectively. For E - E10 series compounds have IP values 0.24537, 0.24717, 0.24178, 0.23765, 0.24362, 0.22976, 0.22677, 0.20209, 0.22809, 0.22439, and 0.23256 respectively. The value of F - F10 series is 0.23252, 0.23461, 0.22977, 0.22903, 0.23447, 0.22357, 0.22152, 0.19801, 0.22225, 0.21892 and 0.22605 respectively while it is 0.23817, 0.23942, 0.23478, 0.23226, 0.23786, 0.22536, 0.22308, 0.19957, 0.22391, 0.22052, and 0.22785 for G - G10 respectively.

The ionization potential (Raza et al., 2022) of the compound helps to predict the energy required for the removal of valence electrons or reactivity of compounds as the higher the IP values of a compound are found to be stable and vice versa. Although from all four series compounds, D, E, F, and G compounds, E1 has a maximum IP value (0.24717), can be predicted with good stability, and is easily synthesized in contrast to compound F7 with the least IP value (0.19801). Theoretically, the chemical potential of a compound plays a significant role to determine the chemical nature of compounds computationally, as the chemical potential (µ) ranges for the D series from −0.17617 to −0.14579, for E; −0.17824 to −0.14535, for F; −0.17053–0.14086 and for G; -0.17374 to −0.14304.

Koopmans theorem was mostly used to measure the electron affinity that aid to predict the chemical nature of the compounds. Compound E4 has the greatest EA of 0.11285 among the four series while compound F has found with the least one 0.07896. The functional group as alkyl (CH3) group shows a +I effect though others Cl, -N(CH3)2, -OH, -OCH3 have –I. By substitution of electron-withdrawing (EW) and electron-donating (ED) groups on the aromatic ring impacted a significant effect over electrochemical parameters (x, ŋ, µ, etc.).

The EN values ranged from 0.14086 to 0.178235 compounds with Cl substitution exhibited higher electronegativity for E4 0.178235. Several variations in properties were more pronounced owing to the positioning of the ortho and para locations of functional groups on the benzene ring than at other positions. However, the presence of an electron-withdrawing (EW) group increases the electronegativity phenomenon in a substance, and vice versa. DFT calculations helped out to measure several types of physiochemical parameters (Raza and Fatima, 2020, Raza et al., 2020).

3.2. Docking studies

Interactive computerized designed structures of the thiazolidinone with certain chosen targets in various interaction modes ( Fig. 3, Fig. 4, Fig. 5, Fig. 6, Fig. 7, Fig. 8, Fig. 9, Fig. 10) were created via molecular docking, which is a kind of structure-based virtual screening (SBVS) study (Chaudhary and Mishra, 2016, Kansız et al., 2022, Raza and Fatima, 2020). It is highly valued in the structure-based rational drug designing study and shows how extremely large molecules, such as proteins and enzymes, created contacts with smaller molecules, such as ligands, to create new and unique medications (Chaudhary and Mishra, 2016, Raza and Fatima, 2020).

Fig. 3.

Fig. 3

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3D docking poses of the most active compounds on 1OSN Thymidine Kinase.

Fig. 4.

Fig. 4

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3D docking poses of the most active compounds on 1RTD HIV-Reverse Transcriptase.

Fig. 5.

Fig. 5

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3D docking poses of the most active compounds on 1VZV Virus Protease.

Fig. 6.

Fig. 6

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3D docking poses of the most active compounds on 3I7H DNA damage-binding Protein.

Fig. 7.

Fig. 7

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3D docking poses of the most active compounds on 3TYV NS5B Polymerase.

Fig. 8.

Fig. 8

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3D docking poses of the most active compounds on 4JU3 HCV NS5B Polymerase.

Fig. 9.

Fig. 9

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3D docking poses of the most active compounds on 4QWO A4R Profilin-like Protein.

Fig. 10.

Fig. 10

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3D docking poses of the most active compounds on 6VLK Virus Glycoprotein.

To investigate the active sites of the synthetic therapeutic compounds against the intended enzymes, docking experiments were carried out. Crystal structures of various targets against chicken pox, human immune deficiency syndromes, hepatitis, monkeypox, and having the PDB code of 1OSN, 1VZV, 6VLK, 1RTD, 3I7H, 3TYV, 4JU3, and 4QWO, respectively, used and their docking scores were illustrated in Table 1.

Table 1.

Molecular docking scores of D, E, F and G series compounds against 1OSN, 1RTD, 1VZV, 3I7H, 3TYV, 4JU3, 4QWO, and 6VLK.

Code Chicken
Pox		 Chicken
Pox		 Chicken Pox HIV-1 HBV HCV HCV Monkey Pox
1OSN 1VZV 6VLK 1RTD 3I7H 3TYV 4JU3 4QWO
D Nil -8.926 Nil Nil Nil Nil Nil -10.365
D1 Nil -9.036 Nil Nil Nil -7.977 -8.599 -10.107
D2 -6.583 -8.579 Nil Nil -9.120 -7.745 -10.213 -10.500
D3 -8.515 -10.086 Nil Nil -8.145 -8.864 -8.798 -11.281
D4 -12.328 -9.285 Nil -7.528 -9.384 -10.186 -8.234 -9.607
D5 -8.993 -12.713 Nil Nil -9.785 -10.405 -10.584 -12.611
D6 -9.053 -10.852 -6.883 -8.614 -9.766 -8.210 -11.175 -12.477
D7 -11.869 -10.024 -6.848 -7.424 -9.063 -9.880 -11.782 -11.046
D8 -9.852 -10.564 Nil -7.486 -9.512 -11.142 -11.556 -13.383
D9 -8.836 -10.289 -7.408 -7.517 -9.075 -10.444 -10.973 -11.124
D10 -6.829 -10.368 Nil -5.099 -7.994 -9.956 -9.273 -11.42
E Nil -5.882 Nil Nil Nil Nil Nil -5.868
E1 Nil -5.860 Nil Nil Nil Nil Nil -5.328
E2 Nil -5.972 Nil Nil Nil Nil Nil -6.458
E3 Nil -7.119 Nil Nil Nil Nil Nil -6.814
E4 Nil -7.811 Nil Nil Nil Nil Nil -6.157
E5 Nil -9.954 Nil Nil Nil Nil Nil -9.609
E6 Nil -8.984 Nil Nil Nil -6.104 -5.729 -10.170
E7 Nil -7.406 Nil Nil Nil -5.593 -6.626 -6.711
E8 Nil -7.682 Nil Nil Nil Nil Nil -8.494
E9 Nil -8.967 Nil Nil Nil -3.736 -5.303 -6.794
E10 Nil -7.771 Nil Nil Nil Nil Nil -7.979
F Nil -7.101 Nil Nil Nil Nil Nil -5.981
F1 Nil -7.396 Nil Nil Nil Nil Nil -6.976
F2 Nil -7.017 Nil Nil Nil Nil Nil -7.868
F3 Nil -8.507 Nil Nil Nil -5.293 -5.901 -6.894
F4 -8.106 -8.463 Nil Nil -5.349 -5.873 -10.845 -6.591
F5 Nil -9.235 Nil Nil Nil -5.672 -11.059 -11.421
F6 -7.805 -9.143 Nil Nil -6.825 -6.552 -12.088 -9.296
F7 -4.703 -7.684 Nil Nil -4.861 -5.796 -10.923 -6.785
F8 -5.290 -8.423 Nil Nil Nil -6.533 -11.880 -8.513
F9 -4.888 -8.536 Nil Nil -4.973 -6.336 -11.627 -7.288
F10 Nil -7.767 Nil Nil Nil -5.639 -10.651 -6.942
G Nil -6.275 Nil Nil Nil Nil Nil -6.467
G1 Nil -6.542 Nil Nil Nil Nil Nil -6.297
G2 Nil -6.819 Nil Nil Nil -4.243 -4.776 -7.857
G3 -5.072 -8.197 Nil Nil -5.514 -6.358 -6.212 -7.475
G4 -5.067 -8.713 Nil Nil -6.984 -5.999 -10.334 -7.909
G5 -12.421 -9.652 Nil Nil -9.978 -6.415 -6.297 -10.872
G6 -7.00 -9.070 Nil Nil -4.934 -7.793 -11.369 -9.846
G7 -5.196 -8.481 Nil Nil -5.426 -5.538 -6.235 -6.986
G8 -6.056 -8.411 Nil Nil -5.564 -6.568 -6.579 -7.978
G9 -5.995 -9.816 Nil Nil -4.861 -7.066 -5.831 -7.805
G10 -6.071 -7.720 Nil Nil -5.340 -5.519 -6.346 -7.494
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Hydrogen atoms were initially added to the protein structure for docking purposes, and subsequently water molecules were removed. The default MOE energy minimization settings were used to execute the 3D protonation and energy minimization process. All 44 molecules from four distinct amine series, including benzylamine, ammonia, aniline, and p-aminobenzoic acid, were docked to energy lowered enzyme targets and the resulting docking complex was then further verified using Discovery studio visualizer to exhibit those hydrophobic interactions, Van der wall forces and hydrogen bonds that were present in it.

3.2.1. Thymidine kinase

In the case of varicella zoster thymidine kinase (1OSN), S-scores of all the compounds were calculated in the docking study (Table 1). It was determined that the G5 compound showed maximum interaction with 1osn having score of − 12.4215 kcal/mol. Amino acids residues that are present on active sites as Try66 and Arg130 (Prasana, Muthu, and Abraham, 2019). For the very first series of compounds, the decreasing order of ligand and enzyme interaction is D4 > D7 > D8 > D6 > D5 > D9 > D3 > D10 > D2. For third series of compounds the docking score in the decreasing order is F4 > F6 > F8 > F9 > F7 and the fourth series, the order is G5 > G6 > G10 > G8 > G9 > G7 > G3 > G4.

The compound G5 showed a maximum docking score of − 12.4215 kcal/mol and had several interactions with different amino acid residues on the active site of the target thymidine kinase. Arg71, Glu265 showed hydrogen bond interactions with a hydroxyl group of a compound at the 2.05 Å and 1.66 Å respectively (Fig. 3). The oxygen of thiazolidinone ring of the compound showed hydrogen bond interaction with Try277 and hydrogen of the methylene group showed hydrogen bond interaction with oxygen of Asn55 at the distance of 2.33 Å and 2.98 Å. Leu274 showed pi-alkyl interaction with phenyl ring as well as thiazolidinone ring of the compound at the distance of 4.04 Å and 4.51 Å, respectively. Benzyl ring of the compound showed pi-pi interactions with Tyr52 at the 4.5 Å distance. Sulfur of thiazolidinone compound developed the Sulphur-pi interaction with Glu265 at the distance of 2.71 Å.

In the case of D4, pi electronic cloud of Tyr52 represented the interaction with six-membered ring having carboxylate at the distance 3.95 Å. The carbonyl oxygen of thiazolidinone and carbonyl oxygen of six membered ring showed interactions with the hydrogen of Arg71 and Pro275 at the distance of 2.2 Å and 2.56 Å, respectively. Carbonyl substituted six-member ring of the compound showed pi-pi interaction with the benzyl group of Tyr52 at the distance 5.74 Å. Arg71 and Arg54 showed alkyl-pi interactions with substituted chlorine of phenyl ring at the distance of 3.64 Å and 3.63 Å. The carbonyl substituted six-member ring of compound developed pi-alkyl interaction with Leu274 at the distance 4.75 Å.

In D7, thiazolidinone and six-member ring showed pi-alkyl interaction with Arg71 at the distance of 4.71 Å and 4.02 Å. The carbonyl group and dimethyl amine substitute depicted pi-alkyl interactions with Agr54 and Leu274 at the distance of 3.55 Å and 4.93 Å respectively. The carbonyl oxygen depicted hydrogen bond interaction with the hydroxyl group of Try52 and Pro275 at the distance of 4.93 Å and 2.61 Å. Similarly, it also showed interaction with Ser51 at the distance of 2.18 Å.

In F4 compound, Arg71 and Asp76 showed hydrogen bond interactions with the oxygen of thiazolidinone ring at the distance of 3.05 Å and 2.95 Å, respectively. Leu274 depicted alkyl-pi interaction with thiazolidinone ring and chlorine substituted six-member ring at the distance of 4.0 Å and 5.6 Å. Leu266 showed pi-amide interaction with thiazolidinone ring at the distance of 4.41 Å and the phenyl of Trp277 showed pi-sulfur interaction with thiazolidinone ring of the compound at the distance of 5.29 Å. Carbonyl of Cys267 showed a steric bump with the carbon of thiazolidinone ring at the distance 2.23 Å. The electronic cloud of phenyl ring represented the pi-donor interaction with Arg71 at the distance of 2.23 Å. Parana and his colleagues determined the antiviral activity of valacyclovir compound with herpes simplex virus (2GV9), varicella zoster virus (1OSN), and dengue RNA protein (1R6A) using a docking study (Benarroch et al., 2004, Beutner et al., 1995, Prasana et al., 2019).

3.2.2. HIV- reverse transcriptase

The compounds were docked and their S-score were calculated to estimate the interactional behavior of the ligand with the HIV- Reverse Transcriptase (1RTD) and residues that found on active sites as Asp366 and Phe423 (Meng et al., 2015). It was known that among all the 44 compounds only D series showed interaction with 1osn. D6 compound depicted maximum score with a value of −8.61466 kcal/mol. The decreasing order of the D series compounds is D6 > D9 > D7 > D10 > D8 > D4.

In compound D6, Arg284 showed pi-alkyl interactions with the electronic cloud of thiazolidinone and carboxylic acid at the distance of 5.24 Å and 4.89 Å, respectively. Six-member ring with carboxylic acid substituted depicted the pi-alkyl interaction with Lys281 at the distance of 2.16 Å. Methoxy and hydroxyl showed hydrogen bond interactions with Lys287 at the distance of 2.87 Å and 1.77 Å as well as carboxyl group also showed hydrogen bond interaction with Lys281 at the distance of 216 Å. The pi-alkyl interaction occurred with Lys281 and phenyl at the distance of 5.13 Å. Parves and his fellows used antiviral natural compounds for example lamivudine and docked with 1RTD (Parvez et al., 2019).

In D7, thiazolidinone ring represented hydrogen bond interaction with amino group of Arg284 at the distance of 2.35 Å. In D9, the carboxyl group showed hydrogen bond interaction with Asn265 and Gln269 as well as the oxygen of thiazolidinone ring also depicted hydrogen bonding with Trp266 at the distance of 2.30 Å, 1.51 Å and 1.58 Å, respectively. In D10, thiazolidinone also represented hydrogen bond interaction with Ser48 at the distance of 1.52 Å (Fig. 4).

3.2.3. Protease

To check the potential of proposed compounds for protease, compounds were docked against varicella zoster virus protease (1VZV) having amino groups on binding sites as Leu121, Asn30, GLU 28, Ser123, Arg147 and Arg148 (Angamuthu et al., 2019). It was depicted that among 44 compounds, D5 compound of amino benzoic acid series exhibited maximum interaction with 1VZV enzyme with − 12.71373 kcal/mol score while in ammonia series of compounds, the highest score was shown by E5. The decreasing order of the D series compound was D5 > D6 > D8 > D10 > D9 > D3 > D7 > D4 > D1 > D > D2. Compounds E5 and F5 showed the highest score in the E and F series, respectively. The decreasing order of E and F series are E5 > E6 > E9 > E4 > E10 > E8 > E7 > E3 > E2 > E and F5 > F6 > F9 > F3 > F4 > F8 > F10 > F7 > F1 > F and for G series of compounds was G9 > G5 > G6 > G4 > G7 > G8 > G3 > G10 > G2 > G1 > G. Compound D5 which has −12.71373 kcal/mol score, Leu180, Pro41 and Pro42 depicted pi-alkyl interaction with hydroxyl at the distance of 5.41 Å, 5.22 Å and 4.81 Å, respectively. The electronic cloud of both rings showed pi-alkyl interaction with Pro41 and Leu45 at the distance of 4.69 Å and 4.70 Å. Lys189 and lle64 had hydrogen bonding with carboxylic acid group and a hydroxyl group at the distance of 1.86 Å and 5.41 Å respectively. Phenyl ring of Try184 depicted the pi-pi interaction at the distance of 5.16 Å with the targeted compound. In E5 compound, Ala63 and lle64 showed hydrogen bond interaction with the hydroxyl group at the distance of 2.96 Å and 1.44 Å respectively. The Carbonyl group of Val61 also represented hydrogen bond interaction at 3.10 Å with the amine group of thiazolidinone ring. The six-member ring showed pi-alkyl interaction with Pro41 and Pro42 at the distance of 5.07 Å and 4.97 Å. Thiazolidinone ring of the compound also depicted pi-alkyl interaction with Pro42 at the distance of 4.61 Å.

In compound F5, thiazolidinone ring represented pi-alkyl interaction with Pro42 and Leu180 as well as hydroxyl depicted pi-alkyl interaction with Pro40 and Pro41 at the distance of 5.08 Å, 4.52 Å, 4.63 Å and 4.99 Å, respectively. The oxygen of thiazolidinone showed hydrogen bond interaction with Ala63 and lle64 at the distance of 2.67 Å and 1.76 Å, respectively. Arg176 represented interaction with hydroxyl oxygen at the distance of 1.901 Å. Amide pi-stacked interaction present with six-member ring of the compound and lle62, while, pi-donor interaction between Arg176 and hydroxyl at the distance of 3.75 Å and 2.70 Å (Fig. 5). In G9, an electronic cloud of five and six-member ring depicted pi-alkyl interaction with Pro42 and Lys45 as well as methoxy substituted six-member ring of the compound represented pi-alkyl interaction with Pro42 and Leu180 at the distance of 4.10 Å, 4.95 Å, 4.70 Å, and 4.78 Å, respectively. Hydrogen bond interaction is present between sulfur of thiazolidinone ring and lle180 at the distance of 2.68 Å.

3.2.4. DNA damage-binding Protein 1(DDB1) in complex with H-Box Motif of HBX

To check the application of compounds against Hepatitis B virus (HBV), docking studies were used on the active site of the DNA damage-binding Protein 1 (DDB1) in complex with H-Box Motif of HBX (PDB: 3I7H). The docking studies revealed that G5 showed a maximum docking score (−9.978028 kcal/mol) among all the 44 compounds. The docking interactions were exhibited by G5 having 2-hydroxy-3-methoxy substitution on the phenyl ring of the benzylamine and it developed interactions with His905, Phe942, Leu890, and Asn941 (Fig. 6). Furthermore, this compound also showed strong interactions on the active site of 3I7H among all other series compounds. In case of 4-aminobenzoic acid series compounds, the maximum interaction was shown by D5 compound, and decreasing order is D5 > D6 > D8 > D4 > D2 > D9 > D7 > D3 > D10. The decreasing order of the F and G series is F6 > F4 > F9 > F7 and G5 > G4 > G8 > G3 > G7 > G10 > G6 > G9.

In D5, oxygen of the six-member ring represented hydrogen bond interaction with Ala9, Lys709, and His1140 at the distance of 2.02 Å, 2.09 Å, and 1.36 Å, respectively while Asp1099 depicted interaction at the distance of 1.38 Å.

In D6 compound, the carbonyl oxygen depicted hydrogen bond interaction with Lys60 at the distance of 1.38 Å. Sigma-pi interaction presents between hydroxyl and Ile121 at the distance of 2.70 Å. The hydroxyl of D6 represents hydrogen bond interaction with the carbonyl oxygen of Thr130, lle165, and Asp166 as well as with substituted oxygen showed hydrogen bond interaction with Gly119 and Ile120 at the distance of 2.83 Å, 2.81 Å, 2.02 Å, 3.02 Å and 1.97 Å, respectively.

In F6 compound, methoxy and hydroxyl oxygen showed hydrogen bonding with Lys60 as well as with Asn36 and lle31 at the distance of 2.31 Å, 1.66 Å, 3.04 Å, and 2.4 Å, respectively. Ile120 and depicted interaction at the distance of 2.17 Å while, Val63 and Ile121 had pi-alkyl interactions with phenyl ring at the distance of 5.32 Å and 5.41 Å respectively.

In G5, sulfur exhibited pi-sulfur interaction with Phe942 at the distance of 4.25 Å and 5.09 Å, respectively. The oxygen of the five-member ring showed hydrogen bond interaction with His905 and Asn941 while the -OH group showed interaction with Arg889 at the distance of 1.73 Å and 1.79 Å and 2.27 Å, respectively. The methylene group also depicted hydrogen bond interaction with Asn904 at the distance of 2.66 Å. The phenyl ring represented interaction with His905 and Leu890 at the distance of 4.78 Å and 2.46 Å respectively.

3.2.5. NS5B Polymerase

The docking results of the proposed compounds against NS5B Polymerase (PDB: 3TYV) having interactive amino residues Asp318 and Ser288 on active sites (Haudecoeur et al., 2013) depicted that D8 compound showed a maximum score (−11.14253 kcal/mol) and the order is D8 > D9 > D5 > D4 > D10 > D7 > D3 > D6 > D1 > D2 while in ammonia series, the highest score was depicted by E6. The order of the F and G series F6 > F8 > F9 > F4 > F7 > F5 > F10 > F3 and G6 > G9 > G8 > G5 > G3 > G4 > G7 > G10 > G2, respectively.

In D8, the carbonyl oxygen depicted hydrogen bond interaction with Arg394,Arg158 and Lys141 at the distance of 1.58 Å, 2.97 Å, 2.78 Å and 2.77 Å, respectively. The -OH group showed interaction with Ala97 and Asp559 with a distance of 2.27 Å and 1.34 Å, respectively. In compound E6, methoxy oxygen showed interaction with Lys212 at the distance of 1.67 Å.

In compound F6, the methoxy group depicted donor-donor interactions with Arg158 and the hydroxyl group showed hydrogen bond interaction with Arg394 and Glu143 at the distance of 189 Å, 1.36 Å and 1.62 Å, respectively. The six-member ring of the compound represented pi-sulfur interaction with sulfur of Cys366 at the distance of 3.70 Å. In G6, Cys366 and Try148showed pi-sulfur interaction with the phenyl ring of the compound at the distance of 5.28 Å and 5.70 Å, respectively. Methylene and methoxy hydrogen repented hydrogen bond interaction with Cys366 and Gln446 as well as the oxygen of thiazolidinone represented hydrogen bond interaction with Arg386 at the distance of 2.82 Å, 1.48 Å and 1.90 Å, respectively (Fig. 7).

3.2.6. HCV NS5B polymerase

In the case of HCV NS5B Polymerase (PDB:4JU3), docking study of all the compounds was carried out and it was found that F6 compound showed maximum interactions with the HCV NS5B polymerase having − 12.0888 kcal/mol docking score. For the very first series, the decreasing order is D7 > D8 > D6 > D9 > D5 > D2 > D10 > D3 > D1 > D4. The E6, F6 and G6 compounds exhibited maximum scores in their represented series while the remaining compounds give the following order E6 > E7 > E9 > F6 > F8 > F9 > F5 > F7 > F4 > F10 > F3 and G6 > G4 > G8 > G10 > G5 > G7 > G3 > G9 > G2, respectively. In compound D7, the electronic cloud of thiazolidinone ring and phenyl ring represented pi-alkyl interaction with Leu127, and carbonyl oxygen depicted the hydrogen bond interaction with amino group of Arg209 and Thr130 at the distance of 4.51 Å, 3.57 Å, 2.09 Å and 2.14 Å, respectively.

In compound E6, the hydroxyl group depicted hydrogen bond interaction with the carbonyl of Asp3591 and amino of Glu301 at the distance of 1.46 Å and 2.39 Å, respectively. The hydroxyl and amino groups of Thr130 showed hydrogen bonding with the oxygen of F6 as well as the methoxy group depicted hydrogen bond interaction with Glu131 at the distance of 2.20 Å, 1.97 Å and 2.97 Å, respectively. The pi-alkyl interaction of oxygen observed with Leu127 at the distance of 4.53 Å and 4.16 Å. In G6, the oxygen of thiazolidinone depicted hydrogen bond interaction with hydroxyl and the amino group of Thr130 as well as methoxy showed interaction with the carbonyl group of Glu131 at the distance of 2.28 Å, 1.94 Å and 2. 91 Å, respectively (Fig. 8). The hydroxy and methoxy group represented pi-alkyl interaction with Leu127 at the distance of 4.61 Å and 4.10 Å, respectively. Metwally and his colleagues checked the hydrogen bonding interaction between the active site of 1ZOY and the hydroxyl group attached to the ring with a docking score of − 14.6946 kcal/mol and linked it with the antifungal activity of the synthesized compound (Metwally et al., 2019). Others residues that are found as S476 and Y477 (Vrontaki et al., 2016).

3.2.7. A4R profilin-like protein

The proposed compounds were docked against A4R Profilin-like Protein (4QWO). It was depicted that among all 44 compounds, D8 showed maximum interactions with 4QWO enzyme with docking score −13.38396 kcal/mol. It showed interaction with Thr71, Ser73, Arg115, Tyr118, and Arg119 while in ammonia series, the highest score was observed against E6. Other amino residues also present as Asn37, Asp92, Thr18, Lys14, Glu145, and Glu142) (Preet et al., 2022). The decreasing order of the D series compound is D8 > D5 > D6 > D10 > D3 > D9 > D7 > D2 > D > D1 > D4 and ammonia series compounds the order is E6 > E5 > E8 > E10 > E3 > E9 > E7 > E2 > E4 > E > E1 > F5 and G5 compound showed highest score among F and G series of compounds. The decreasing order of F and G series are F5 > F6 > F8 > F2 > F9 > F1 > F10 > F3 > F7 > F4 > F1 and G5 > G6 > G8 > G4 > G2 > G9 > G10 > G3 > G7 > G > G1, respectively. In D8, the oxygen of thiazolidinone ring depicted hydrogen bond interactions with amino group of Arg115 and Arg119 while alkyl group Arg119 at the distance of 1.27 Å, 1.43 Å, and 2.30 Å, respectively. Hydrogen bond interaction showed by the hydroxyl group with Ser73 and Thr71 at the distance of 2.90 Å and 1.49 Å, respectively. The pi-pi interactions were observed with Tyr118 while pi-alkyl interaction is observed with Arg115 at a distance of 5.76 Å and 4.93 Å, respectively.

In compound E6, phenyl of Tyr118 represented pi-sulfur interaction with sulfur of thiazolidinone ring at the distance of 3.72 Å. The amino group of Arg114 and Arg115 showed hydrogen bond interaction with the oxygen of thiazolidinone as well as the hydroxyl group of the compound. The Ser73 showed a hydrogen bond with methoxy oxygen of the compound at the distance of 1.77 Å.

In compound (F5), oxygen of thiazolidinone ring showed hydrogen bond interaction with amino and methylene groups of Arg115 at the distance of 1.93 A and 2.77 A, respectively. The sulfur of thiazolidinone depicted hydrogen bond interaction with Arg119 while the hydroxyl group showed hydrogen bond with hydroxyl oxygen of Thr71 at the distance of 2.66 Å and 1.63 Å, respectively. The hydroxyl group and phenyl ring of the compound showed pi-alkyl interactions with Arg115 and Arg119 at the distance of 2.66 Å and 4.48 Å, respectively.

The phenyl ring of G5 represented pi-alkyl interaction with Arg119 and pi-pi interaction with Thy118 at the distance of 5.0 Å and 5.07 Å, respectively. The hydroxyl group depicted hydrogen bond interaction with the oxygen of Thr71 and Glu83 at the distance of 1.74 Å and 2.76 Å, respectively. Hydrogen bond interaction is also seen between the oxygen of thiazolidinone and the amino group of Arg119 at the distance of 2.80 Å. The phenyl ring of Tyr118 showed pi-pi interaction with thiazolidinone and pi-sulfur interaction with sulfur of the compound at the distance of 4.7 Å and 4.4 Å, respectively (Fig. 9).

3.2.8. Glycoprotein

All compounds were docked and their S score was determined to check the interaction behavior with varicella-zoster virus glycoprotein (6VLK) according to standard protocols. To check the possible interaction of the compounds on the active sites of the enzyme, discovery studio, and MOE parameters were used and it was found that D6, D7, and D9 compounds showed good interactions among all 44 compounds and the order is D9 > D6 > D7. The compound D9 showed the highest docking score − 7.40849 kcal/mol and showed interactions with Ala560, Thr631, Arg569, and Asn557. The Ala560 depicted pi-alkyl interactions with the basic skeleton and methoxy group of the phenyl ring of the compound at the distance of 3.73 Å and 4.67 Å, respectively. The carboxylate group of the phenyl ring showed hydrogen bond interaction with Thr631 and Arg569 as well as methoxy group depicted hydrogen bond interaction with the hydroxyl group of Thr681 at 2.62 Å. The sulfur atom of thiazolidinone ring also showed hydrogen bond interaction with the amino group of Asn557 at the distance of 2.45 Å. In D6, thiazolidinone and phenyl ring represented pi-alkyl interaction with Ala560 at the distance of 4.89 Å and 4.45 Å, respectively. The carbonyl group of the compound represented hydrogen bond interaction with Arg569 at the distance of 1.38 Å. In D7, the carbonyl group of the compound also showed hydrogen bond interaction with Arg569 and Lys551 at the distance of 1.38 Å, and 2.77 Å (Fig. 10).

3.3. Homology study

The target sequence of A4R Profilin-like Protein (4QWO), HCV NS5B Polymerase (4JU3), and varicella zoster thymidine kinase (1OSN) that were screened on the basis of best binding affinity value with ligands D8, F6, and G5. Swiss modelling study of these targets sequences done, for A4R Profilin-like Protein (4QWO) found homology with the crystal template sequences of other proteins having PDB files 1FIK, 3UB5, 1PNE and 2PBD, with sequence Identity (30.23–31.01 %), global model quality estimate (GMQE) effective value (0.34–0.35), and sequence similarity (0.35). The target sequence of HCV NS5B Polymerase (4JU3) found templates with PDB as 1YUY, 3HKW, 4AEP, 3GSZ and 2XI2 having sequence identity (74.96–87.99 %), global model quality estimate GMQE (0.42–0.43), sequence coverage (0.50) and sequence similarity (0.54–0.58). The varicella zoster thymidine kinase (1OSN) sequence modelling study given template sequences of protein having PDB 1P7C, 1KI7, 1P6X, 1QHI and 1P6X and their values are GMQE (0.16–0.17), sequence identity (29.91–38.01 %), sequence similarity (0.36–0.39), lesser sequence coverage (0.25).

Template crystal structures of all three targets along their templates can be depicted in Table 2. A decent indicator of a model's accuracy is the proportion of the target and template's sequences that are identical. As sequence identity increases, model accuracy rises continuously (Waterhouse et al., 2018). The frequency of mistakes in computer produced sequence alignments rises as target and template sequence similarity decreases (Steinegger et al., 2019). The scoring function of QMEAN is used by Swiss model and to measure the quality of each residue globally and individually, QMEAN employs statistical potentials of mean force (Studer et al., 2020).

Table 2.

Homology modeling study of effective screened target proteins.

Target Protein
Crystal Structure of A42R Profilin-like Protein from Monkeypox Virus Zaire (4QWO)
Model Templates PDB Sequence Identity Sequence Similarity Sequence coverage GMQE Sequence range Method QMEAN DisCo Global
1 Human platelet profilin I crystallized in low salt 1FIK 30.23 % 0.35 0.50 0.34 2–130 X-ray, 2.30 Å 0.71 ± 0.07
2 Actin with a wide-open nucleotide cleft 3UB5 31.01 % 0.35 0.50 0.35 2–130 X-ray, 2.20 Å 0.72 ± 0.07
3 Crystallization and structure determination of bovine profilin at 2.0 angstroms resolution 1PNE 31.01 % 0.35 0.50 0.35 2–130 X-ray, 2.00 Å 0.73 ± 0.07
4 Ternary complex of profilin-actin with the poly-PRO-GAB domain of VASP 2PBD 30.23 % 0.35 0.50 0.35 131–259 X-ray, 1.50 Å 0.62 ± 0.07
Target Protein
HCV NS5B Polymerase (4JU3)
Model Templates PDB Sequence Identity Sequence Similarity Sequence coverage GMQE Sequence range Method QMEAN
DisCo Global
1 RNA-Dependent RNA polymerasehepatitis c virus NS5B RNA-dependent RNA polymerase genotype 2a 1YUY 75.49 % 0.54 0.50 0.42 1–559 X-ray, 1.90 Å 0.85 ± 0.05
2 NS5B RNA-dependent RNA polymeraseHCV NS5B genotype 1a in complex with 1,5 benzodiazepine inhibitor 6 3HKW 87.99 % 0.58 0.50 0.42 1–558 X-ray, 1.55 Å 0.88 ± 0.05
3 RNA-directed RNA polymeraseHCV-JFH1 NS5B polymerase structure at 1.8 angstrom 4AEP 74.96 % 0.54 0.50 0.43 1–559 X-ray, 1.80 Å 0.86 ± 0.05
4 RNA-directed RNA polymeraseStructure of the genotype 2B HCV polymerase 3GSZ 75.22 % 0.54 0.50 0.43 560–1116 X-ray, 1.90 Å 0.86 ± 0.05
5 RNA-directed RNA polymeraseHCV-H77 NS5B APO polymerase 2XI2 87.12 % 0.58 0.50 0.42 1–558 X-ray, 1.80 Å 0.87 ± 0.05
Target Protein
Varicella zoster thymidine kinase (1OSN)
Model Templates PDB Sequence Identity Sequence Similarity Sequence coverage GMQE Sequence range Method QMEAN DisCo Global
1 Thymidine kinasecrystal structure of HSV1-TK complexed with TP5A 1P7C 30.06 % 0.36 0.25 0.16 640–954 X-ray, 2.10 Å 0.68 ± 0.05
2 Thymidine kinasecrystal structure of thymidine kinase from herpes simplex virus type I complexed with 5-iododeoxyuridine 1KI7 29.91 % 0.36 0.25 0.16 2–328 X-ray, 2.20 Å 0.58 ± 0.05
3 thymidine kinasecrystal structure of EHV4-TK complexed with thy and SO4 1P6X 37.58 % 0.39 0.25 0.17 3–328 X-ray, 2.00 Å 0.62 ± 0.05
4 protein (thymidine kinase)herpes simplex virus type-I-thymidine kinase complexed with a novel non-substrate inhibitor, 9-(4-hydroxybutyl)-N2-phenylguanine 1QHI 30.28 % 0.36 0.25 0.17 325–644 X-ray, 1.95 Å 0.62 ± 0.05
5 thymidine kinasecrystal structure of EHV4-TK complexed with thy and SO4 1P6X 38.05 % 0.39 0.25 0.16 326–644 X-ray, 2.00 Å 0.61 ± 0.05
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Abbreviation: Protein data bank (PDB); Global mean quality estimate (GMQE); Qualitative Model Energy Analysis (QMEAN)

3.4. Adsorption, distribution, metabolism, excretion and toxicity study

The adsorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters of the molecules under investigation were calculated via Swiss internet program. In Tables S5-s8 list of most often discussed parameters, including molecular weight, number of heavy atoms, number of H-bond acceptors, topological surface area (TPSA), blood-brain barrier (BBB) permeability, P-glycoprotein substrates, gastric intestine (GI) absorption, and synthetic accessibility. Lipinski's 5.0 rule is highly workable to distinguish between compounds that resemble and do not resemble therapeutic agents and drugs.

The molecular weight range of all compounds in series D, E, F, and G are 253.30–387.43, 133.19–267.32, 209.29–343.42, and 223.31–357.45, respectively. The maximum molecular weight was observed for the compound in the case of G6 (357.45), whereas, the lowest one for compound E of 133.19. The molecular weight of all the compounds was below 500 Dalton to permit skin absorption and act as drug-like candidates (Schnider, 2021). The values of TPSA observed for D, F, F, and G series were found between 115.0 and 144.46, 86.49–115.95, 77.70–107.16, and 77.70–107.16, respectively. TPSA (Ų) values are also by substitution of different functional groups as R-O-R (9.23), R-O-H (20.23), R-S-R (25.30), S=R (32.09), C Created by potrace 1.16, written by Peter Selinger 2001-2019 O (17.07), and NR3 (3.24), where R group other than hydrogen atom (Ertl, Rohde, and Selzer, 2000).

All compounds showed significantly maximum intestinal absorption, additionally, all compounds except F2, F3, G2, G3, and G10 exhibited no permeation in the blood-brain barrier. The risk of side effects from BBB-crossing medications is considered to be more severe (Bao et al., 2020). All compounds obeyed the Lipinski Rule (Tatlidil et al., 2022), which that specifies molecules must have a molecular mass of less than 500 Dalton, a value of Log Po/w not greater than 5, and a maximum of 10 hydrogen bond acceptors are acceptable.

Compounds demonstrated considerable synthetic accessibility values for series of D (2.23–3.28), E (2.22–2.86), F (2.27–3.31), and G (2.24–3.33) compounds. Compound G7 revealed the maximum synthetic accessibility value of 3.53. The structure-activity relationship (SAR) also affects the parameters of ADMET. The lipid permeability values regarding compounds D, E, F, and G are 1.65, 0.55, 2.09, and 2.16, respectively. The solubility of substances is reduced as their molecular weight increases (Bao et al., 2020).

The order of solubility of compounds was also dependent upon various R groups attached to R-NH2 as for D:-2.78, G:-2.89, F:-2.93, and E:-1.09. A drug's potential water and lipid solubility had an impact on its adsorption, distribution, metabolism, excretion, toxicity, and elimination pathways. A drug's solubility was an actually sum of each functionality present in it. As the hydrophilic functionalities were able to form hydrogen bonds and have the ability to ionize. Functionalities that contributed to the water solubility of compounds: Ar-OH, -N(CH3)2, A-NH2, and -N = CH2 however, those that were unable to ionize or formed hydrogen bonds tend to impart a measure of lipid solubility to a drug molecule. The main lipid-soluble functional groups were the aromatic ring and ring system like in C, -C Created by potrace 1.16, written by Peter Selinger 2001-2019 C-, aliphatic alkyl chain, R-O-R, and halogen group (Cl). The following functionalities contributed to compound water solubility: Ar-OH, -N(CH3)2, Ar-NH2, and -N = CH2. On the other hand, those functional moieties that do not easily ionize and form hydrogen bonds tend to give a chemical compound a certain amount of lipid solubility. The primary groups that are lipid-soluble included the aliphatic alkyl chain, R-O-R, halogen group (Cl), and in the aromatic ring such as C, -C Created by potrace 1.16, written by Peter Selinger 2001-2019 C- (Gleeson et al., 2009).

Pan assay interference structures of compounds contain disruptive functional groups, they can react with a variety of biological targets in a non-specific manner as opposed to specific ones. In (PAINS), compounds, almost all compounds were given a single alert due to single Rhodanines (ene_rhod_A) although, D7, E7, F7, and G7 were given 2 alerts that were owing to Rhodanines (ene_rhod_A) and (anil_di_alk_B) group (Baell and Holloway, 2010).

The toxicity potential of compounds is determined using the protox-II online web tool. Compounds that were screened on basis of higher binding affinities are D8, E6, F6, and G5, their oral toxicity estimation outcomes were also given in Fig. 11, although toxicity radar charts for these compounds are also predicted that projected right away demonstration of positive toxicity consequences usually related to its class is also given in Fig. S4-S7. Toxicity examination determined that molecules fit category IV, which is considered to be low to moderate toxicity. Both compounds D8 and F6 were given a median lethal dose (LD50) of 1233 mg/kg while both E6 and G5 were 350 mg/kg. The prediction accuracy percentage is more than 67 % in all four compounds. The average similarity percentage ranges between 58.62 % and 71.04 % for these compounds. The compounds D8, E6, and F6 were found to be hepatotoxic while D8 has some toxic potential against the mitochondrial membrane, and E6 was also found to be carcinogenic that depicted in a radar chart with a blue line active. Compound G5 is found to be highly safe owing to having no toxicity behavior. Although toxicity radar exhibited that no compound is active against other parameters depicted mainly by orange line as immunotoxicity, mutagenicity, ATPase family AAA domain-containing protein 5 (ATAD5), Phosphoprotein (p53), Heat shock response element (HSE), nuclear factor-like 2/antioxidant responsive element (nrf2/ARE), peroxisome proliferate activated receptor gamma (PPAR-Gamma), estrogen receptor ligand binding domain (ER-LBD), estrogen receptor alpha (ER), aromatase, androgen receptor (AR), aryl hydrocarbon receptor (Peytam et al., 2021), androgen receptor ligand binding domain (AR-LBD) and cytotoxicity (Nnadi et al., 2020).

Fig. 11.

Fig. 11

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Oral Toxicity Potential of screened therapeutical designed compounds.

4. Conclusion

According to WHO, chickenpox, and monkeypox virus were considered a source of pandemic and severe acute syndromes. In recent centuries, extensive research has been done to plan unique and dynamic molecule to treat new illnesses. The synthesis of heterocyclic derivatives was reported owing to have a wide range of biological activities. By keeping the significance and sound biological potential of targeted moiety, forty-four thiazolidinone were designed. The suggested compounds underwent optimization using DFT tool and had several theoretical characteristics were computed from output files of DFT. It was concluded after screening of compounds against various proteins that such thiazolidinone may be the most effective viral protein inhibitor and may one day to be possible therapeutic for several viruses.

Additionally, online web-based software was used to forecast the ADMET features of the compounds under study. Swiss internet program was used to determine the ADMET parameters of the compounds. This software found that virtually all of the compounds obeyed the Lipinski rule, having an effective range of topological surface area, good gastrointestinal absorption, and effective synthetic accessibility values. In order to apply these molecules in medicinal field, in-vitro as well as in-vivo studies must be done in depth.

CRediT authorship contribution statement

Muhammad Asam Raza has designed the whole project as supervisor, Umme Farwa has done DFT studies, Fatima Ishaque has conducted the docking studies along help in writing, Abdullah G. Al-Sehemi have helped in drafting and polishing the manuscript.

Conflict of Interest

All authors declared that they have no conflict of interest.

Acknowledgments

Deanship of Scientific Research at King Khalid University is greatly appreciated for funding this work under grant number R.G.P.1/274/43.

Footnotes

Appendix A

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.compbiolchem.2023.107827.

Appendix A. Supplementary material

Supplementary material

mmc1.docx (2.1MB, docx)

.

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