Computational Assessment of Punica Granatum Phytochemicals for Drug-Likeness and Their Prospective Role in Infertility – A Review

Punica granatum—a fruit that could hold the key to future medicines. Punica granatum, or pomegranate, is the focus of modern pharmacology because its remarkable therapeutic potential is attributed to its rich profile of phytochemicals, including tannins, triterpenoids, and glycosides.^1,22 Therefore, for a drug to be viable, it must have drug properties such as solubility, permeability, and bioavailability. These properties ensure that the compound can reach the target site in the body for therapeutic use at an effective concentration. The most widely used guideline for this evaluation is Lipinski’s rule of five, which calculates parameters such as molecular weight, hydrogen bond donors and acceptors, and lipophilicity (logP). Compounds that do not follow Lipinski’s rule are less likely to be orally active drugs; that is, they should pose zero violation.²⁰ This computational method provides the accuracy to predict the drug-likeness and therapeutic efficacy. Phytochemicals such as ellagic acid, gallic acid, ascorbic acid, thymol, etc., show anti-inflammatory and antioxidant properties.^3,4,5

Current research focuses on in-silico analysis of not only synthetic drugs but also natural yet ayurvedic traditional formulations as well as single drugs. Hence this article focuses on a single drug, i.e., Punica granatum, whose phytochemicals possess the drug-like properties and therapeutic potential. Studies have shown the Punica granatum has a strong affinity for the infertility treating targets, indicating that it may be useful for treating infertility. However, this computational technique has its own significance; it should be followed by in vitro and in vivo studies to confirm its effectiveness and applicability. This technique allows for the rapid screening and optimization of potential drug candidates.

Numerous bioactive substances derived from minerals, plants, and Ayurvedic drugs shows relevant action as medicines, but they might need to be optimized to satisfy drug-likeness standards. Rapid virtual screening of these substances, ADME property prediction, blood–brain barrier permeability, and possible off-target effects are all made possible by computational techniques. Combining this idea with pharmacophore modelling, ADMET profiling, and molecular docking provides a potent method for turning promising compounds into pharmaceuticals that are therapeutically feasible in the age of transdisciplinary research. Early detection of drug similarity helps prevent last-minute experiment failures.

In this review we have focused on phytochemicals that are useful in targeting the infertility-causing target and treating infertility.

MATERIALS AND METHODS

Software and servers used for phytochemicals were IMMPAT, the PubChem database for canonical smiles, SwissADME & ChemDraw for downloading the chemical structure, and Molsoft software to determine the drug likeness.

Inclusive and exclusive criteria for phytochemicals:

Inclusive criteria: those which are responsible in treating infertility and also present in Punica granatum.

Exclusive criteria: which does not show its role in treating infertility yet present in the Punica granatum.

Canonical smiles of selected phytochemicals were taken from the PubChem database.

To get the canonical smiles of each phytochemical, we have to open the database site and then enter the name of each phytochemical in the search bar and press the search option beside it. After that, the compound summary of entered phytochemicals appears on the page; we have to scroll down to the chemical and physical properties row and get the canonical SMILES mentioned under the heading "molecular description." Then copy the canonical smiles string, and hence repeat this procedure for the rest. (https://pubchem.ncbi.nlm.nih.gov/ )

ChemDraw—to access the chemical structure of selected phytochemicals.

To get the chemical structure of the selected phytochemicals, we have to access the ChemDraw database; in that, we have to click on the structure menu and from there select the option of canonical smiles to the structure option. After that, insert the canonical smiles string and click OK; ChemDraw automatically generates the structure. Table 1 shows the chemical structure of selected phytochemicals.

To find out drug likeness score,

The Molsoft web server (https://molsoft.com/mprop/) was used to see the drug-likeness score of phytochemicals. Lipinski’s rule of five was used to consider the drug-like properties, which determine the molecules should follow the following parameters: molecular weight of less than 500, C log P less than 0.5, hydrogen bond acceptor less than 10, and less than 5 for the donors. The canonical smiles from PubChem were taken and entered into this Molsoft online software and run to calculate the drug-like properties.

Table no.: 1 Chemical structure of selected phytochemicals.

Sr.no	Phytochemicals	2D	3D
1.	Eugenol
2.	Thymol
3.	Limonene
4.	Beta-caryophyllene
5.	Gallic acid
6.	Ascorbic acid
7.	Ellagic acid
8.	Quercetin
9.	Punicalagin

Table no. 2—Showing the Lipinski’s rule and the violations

RESULTS

The drug-likeness is important for drug design, as it tells you the characteristics of a particular drug, specifically in term of bioavailability. In order to determine the medication's bioavailability in the human body, a number of drug similarity metrics were calculated for a few chosen phytochemicals. This investigation determines whether a phytochemical has the qualities needed for drug development. To assess the drug like properties of the selected phytochemicals, several parameters were considered like Molecular Weight (MW<500 Daltons), Hydrogen Bond Acceptors (HBA≤10), Hydrogen Bond Donors (HBD ≤5), partition coefficient (Log P ≤5) and adherence to Lipinski's rule of five (RO5) violations≤1 to observe the bioavailability of oral routes.   

The result as presented in the table no 2 indicate that the drug-likeness of selected phytochemicals which exhibits satisfactory levels of acceptable ranges with 0 violations.

DISCUSSION

Data analysis – asses the drug like property of selected phytochemicals

The selected phytochemicals of Punica granatum was assess using the physiochemical parameter that influence bioavailability in the human body. The  parameters were , Molecular Weight (MW<500 Daltons) it is important as it involved in the capability of a compound to be absorbed, metabolized and excreted from the body; Hydrogen Bond Acceptors (HBA≤10)influence the solubility and permeability , Hydrogen Bond Donors (HBD ≤5) important for drug-receptor interaction, partition coefficient (Log P ≤5) gives the hydrophobicity of the drug and ability to pass through the lipid bilayer of the cell membrane and Lipinski's rule of five (RO5) violations≤1 to observe the bioavailability of oral routes.  The analysis shows that selected phytochemicals from Punica granatum possess the drug-likeness properties based on the evaluated parameters. The results highlight the value of computational techniques in the initial phases of drug development and offer insightful information that can direct experimental research.²⁰

The Lipinski’s rule has been so well-established that assess the drug-likeness of a compound based on its physiochemical characteristics. The compound which follows the rule with 0 or 1 violation are more likely to be orally active drugs and more than that are less orally active. The fact that many of the evaluated phytochemicals met the drug-likeness criteria highlights their potential for further exploration as therapeutic agents.

This scientific review article discusses the therapeutic potential of Punica granatum and its phytoconstituents in the treatment of male and female reproductive health. Several compounds have shown promising effects against infertility-related conditions, mainly through their Oxidative Stress, antioxidant, anti-inflammatory, and cytoprotective mechanisms.^9,12

It has been reported that the ellagic acid improves semen parameters against genotoxic insults and thermal stress.³ Punicalagin and related pomegranate ellagitannins have shown effective results in enhancing fertility in preclinical models, which show significant improvement in embryonic and placental development under oxidative stress conditions.^12,18,19 Clinical evidence shows that pomegranate extract effect sperm motility in sub fertile males. In female reproductive health, flavonoids such as quercetin play a vital role in improving it, as quercetin is linked with improving ovulation, oocyte maturation, embryo quality, and pregnancy rate in women bearing PCOS.⁶ Correspondingly gallic acid has a role in enhancing the sperm quality and attenuating testicular damage in multiple pre-clinical studies.⁷ Other dietetic antioxidants, such as ascorbic acid, have improved sperm motility & morphology.^4,10 And now the lasting compounds, such as eugenol, thymol, β-caryophyllene, and D-limonene, showed protective roles against toxicant that cause reproductive damage.^15,16 In particular, eugenol enhanced ovulatory results in PCOS. Thymol improves semen storage quality; β-caryophyllene exerts anti-endometriotic and testis protective effects via CB2/PPAR signalling ^15,16; D-limonene recovers arsenic-induced testicular damage and improves sperm quality in aging models. D-limonene improved testicular weight and sperm count, improved seminiferous tubule health, and markedly increased testosterone, LH, and FSH levels in aged rats. Because of its antioxidant qualities, oxidative stress markers decreased, indicating that it has great potential as a natural remedy for age-related reproductive loss.²¹

Hence, the collected findings support the potential of phytochemicals and bioactive compounds present in pomegranates in treating infertility. All of these work by protecting or improving oxidative stress, hormonal regulation, and cellular protection, thus improving reproductive health for stronger implantation of the embryo in females and also primarily contributing to male reproductive health. However, all the evidence originated from the preclinical models, and well-controlled clinical studies remain limited.

Table no. 3—Summary table of the discussions