Computational molecular docking and simulation-based prediction of natural compounds from nyctanthes arbor-tristis as potential antifungal agents

1. Introduction

Over recent decades, many pathogenic fungi, including species of Aspergillus, Cryptococcus, and Candida, have been reported to develop resistance mechanisms such as target site mutations, biofilm formation, and efflux pump overexpression, that significantly reported to significantly reduce the efficacy of currently used antifungal drugs. The consequence is a growing number of cases where infections become hard to treat, resulting in increased morbidity, mortality, and expensive healthcare. Alarmingly, some resistant strains are now considered multidrug-resistant, further complicating treatment options and emphasizing the urgent need for novel anti-fungal agents. The antifungal potentialities of phytometabolites have been primarily rooted in a specific class of molecules such as flavonoids, phenolics, alkaloids, terpenoids, and saponins. These compounds act through various mechanisms, including disrupting fungal cell membranes (allicin from garlic, eugenol from clove, which has also been reported to inhibit adenosine triphosphatase (ATPase) enzyme activity, while increased permeability has been explored with thymol, from thyme, and interfering with the synthesis of vital cell components like ergosterol. However, resveratrol has been reported to inhibit fungal enzymes linked to the synthesis of the cell wall and disrupts membrane integrity to facilitate cell lysis. The previously reported inhibitory activities of phytochemicals against Candida and Aspergillus spp. stated that plant-based molecules could be comparable to, or even surpass, conventional synthetic antifungals in terms of antifungal spectrum and potency. Moreover, plant-derived antifungal agents have been incorporated into topical formulations, including ointments or creams, coatings, and as a natural preservative for many food items to stop fungal growth and deterioration, indicating their versatile application spectrum rooted in their chemical properties rather than traditional or general therapeutic contexts

Thus, plants are a promising reservoir of bioactive metabolites with significant antifungal potentialities, often reported to show multi-target mechanisms that can reduce resistance development. Nyctanthes arbor-tristis (N. arbor-tristis), a traditional medicinal plant rich in flavonoids, alkaloids, and phenolic compounds, has garnered attention due to its reported pharmacological properties, including antifungal activities in preliminary studies.

N. arbor-tristis, belonging to the family Oleaceae, is a small, ornamental tree native to Southeast Asia and India. It is also known as parijat, harsingar, and night jasmine. It is well known for its fragrant white blooms that open only at night. The plant has been used for centuries in traditional Indian medicinal products due to its many health benefits. This plant has several health benefits, including its anti-inflammatory properties, which help patients cope with pain and inflammation. Due to their antipyretic properties, the plant contains compounds that can reduce fever. The plant’s components include antioxidants, which can protect the body from damage caused by free radicals (Arendrup et al., 2014; Sana et al., 2024). The plant contains compounds with astringent properties that may help to tighten skin and reduce inflammation. Chemicals in the plant can break up mucus and ease coughing.

Additionally, laxative components of the plant have been reported, which may help relieve constipation due to their laxative properties. The plant has components that resemble sedatives and can help people relax mentally and physically. The night jasmine has also been reported to have antifungal properties against a variety of fungi, including Malassezia furfur, Aspergillus niger, and Aspergillus flavus. Some of the plant’s compounds can damage fungi’s cell walls, which will eventually cause the fungi to die. A few studies on the antimicrobial qualities of N. arbor-tristis have been carried out, including an evaluation of the plant’s antifungal activity against Aspergillus flavus and Aspergillus niger. Previous studies have demonstrated that the ethanolic extract of N arbor-tristis leaves effectively suppressed Aspergillus flavus and Aspergillus niger. According to reports, this extract can prevent up to 60% of the growth of tested fungi. (Das and Bhatnagar 2022, Gahtori et al., 2023). Studies on the anti-Malassezia properties of Nyctanthes arbor-tristis and their use in treating infections (Mishra et al., 2016). The Asia Pacific region now has 83% of its population resistant to azole antibiotics, and the emergence of resistant fungal strains poses a severe threat to crop protection, human health, and food spoilage. A methanolic extract from N. arbor-tristis flowers was previously shown to be effective against Malassezia furfur, a fungus that causes dandruff. The extract reduced this fungal’ s growth potential by up to 80%. N. arbor-tristis possesses antifungal qualities that can combat both Candida albicans (C. albicans) and Aspergillus niger (A. niger). Methanolic extract from the leaves of N. arbor-tristis is an effective way to combat Candida albicans, a fungus associated with yeast infections. The extract reduced the growth rate of this fungus by up to 70%.

Additionally, it has proven effective in inhibiting A. niger growth, halting its growth by up to 50%. The plant is thought to possess antifungal qualities due to compounds such as calceolarioside A, esitosterol, and quercetin. In vitro, these compounds have significant antifungal activity. The antifungal qualities of N. arbor-tristis have drawn more interest lately. Numerous studies have demonstrated the antifungal activity of extracts from the plant’s leaves, flowers, and bark against Aspergillus flavus, A. niger, and Malassezia furfur (Sharma et al., 2023).

Nonetheless, these studies’ findings suggest that plants are a potential natural remedy for fungal infections. It’s critical to remember that N. arbor-tristis is a medicinal product and should only be used by qualified medical professionals. (Kumari and Charya 2016, Sharma et al., 2023).

Lupeol, a pentacyclic triterpenoid, beta amyrin, and Nyctanthic acid are commonly found in various medicinal plants, including N. arbor-tristis. These phytochemicals garnered attention for their potent pharmacological properties, including antibacterial and antifungal, which are primarily attributed to their ability to interact with the fungal cell membrane.

An important development in medicinal chemical research is the integration of computational techniques, molecular docking, dynamics, and simulation into the search for new bioactive compounds, including antifungal agents from natural resources. Traditionally, exploring natural chemicals for antifungal efficacy is laborious and resource-intensive due to their complexity. The use of cheminformatics technologies has accelerated the discovery process through virtual screening, predictive modelling, and data analysis of extensive collections of natural compounds, aiding in the identification of lead candidates and the understanding of their structure-activity relationships. Molecular docking, dynamics, and simulations have been reported to provide comprehensive insights into how screened phytochemicals interact with fungal targets, including their binding potential and mechanisms of interaction. Compounds such as berberine, curcumin, and eugenol have been reported to show computationally predicted antifungal activity against many pathogenic fungi. Combining these approaches has allowed for a more efficient and targeted exploration of natural chemical diversity, which is especially important given the rise of drug resistance and the limited availability of new therapies. This integrated approach enhances the discovery of novel antifungal agents from natural resources and offers a promising pathway toward innovative, sustainable treatments and improved global health.

This study analyzed the interaction of N. arbor-tristis’s chemicals using cheminformatics tools with the used drug targets for fungi, pathogenic yeast C. albicans (PDB:5FSA) (Hargrove et al., 2017), A. fumigatus protein farnesyltransferase (PDB: 4LNG) (Mabanglo et al., 2014), the crystal structure of lanosterol 14-alpha demethylase (PDB:5EQB) (Monk et al., 2014), and the fungal chitinase from A. fumigatus (PDB:2XUC) (Rush et al., 2010) were used. The plant contains various compounds with potential medical uses, such as anti-inflammatory, anti-arthritic, and anti-cancer agents (Bhadra, 2020). Nevertheless, more research needs to be conducted on the chemical makeup of antifungal agents and their interactions. Prior extensive computational analysis demonstrated that arbortristoside E and beta-sitosterol, natural constituents of this plant, exhibited substantial binding affinity towards cyclooxygenase-1 (COX-1), cyclooxygenase-2 (COX-2), phosphodiesterase-4 (PDE4), phosphodiesterase-7 (PDE7), interleukin-17A (IL-17A), interleukin-17D (IL-17D), tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), prostaglandin E2, and prostaglandin F synthase (Ahmad et al., 2023).

To demonstrate the protection against fungal strains, this study aimed to investigate the most essential interacting antifungal molecules that could target the sterol 14-alpha demethylase, an important enzyme required for life-supporting processes in fungal strains. This study used molecular docking to investigate the antifungal interactions between the target protein of fungal strains linked to fungal growth and natural compounds from N. arbor-tristis. The results of this study could be hypothesized that compounds like lupeol and Nyctanthic acid from this plant could be used as antifungals to manage food, agriculture, and health-associated fungal problems.

2. Materials and Methods

3. Results and Discussion

Traditional antifungal strategies have long served as the cornerstone of managing fungal infections, with agents such as azoles, polyenes, and echinocandins being commonly employed clinically with some limitations, including toxicity, a narrow spectrum of activity, and less effectiveness against certain resistant strains. Polyenes such as amphotericin B are potent antifungals but cause severe nephrotoxicity, infusion-related adverse reactions, drug-drug interactions, and poor penetration, limiting their prolonged use.

Over recent decades, many pathogenic fungi, including species of Aspergillus, Cryptococcus, and Candida, have developed resistance mechanisms such as target site mutations, biofilm formation, and efflux pump overexpression that have been reported to significantly reduce the efficacy of currently used antifungal drugs. The consequence is a growing number of cases where infections become hard to treat, resulting in increased morbidity, mortality, and expensive healthcare. Alarmingly, some resistant strains are now considered multidrug-resistant, further complicating treatment options and emphasizing the urgent need for novel anti-fungal agents. Natural products have historically been a rich source of antimicrobials, including antifungal agents, and offer diverse biological activities and chemical structures that synthetic drugs may lack. Plants are a promising reservoir of bioactive metabolites with significant antifungal potentialities, often reported to show multi-target mechanisms that can reduce resistance development. N. arbor-tristis, a traditional medicinal plant rich in flavonoids, alkaloids, and phenolic compounds, has garnered attention due to its reported pharmacological properties in preliminary studies. The cheminformatics-based results of this study were observed to be significant.

The top three compounds were selected for additional research after we sifted and shortened the harsingar natural compounds based on our determined binding affinity as compared to the control drug binding affinity (Supplementary material S2). Also, Ligand efficacy (LE) was calculated, and all ligands showed efficacy ranging from -0.14 to -0.42 kcal/mol/atom (Supplementary material S3). Also, the 2D and 3D visualization patterns depicted in Figs. 1(a-t) between PDB:5FSA, 4LNG, 5EQB, and 2XUC, as well as selected natural compounds, including control drug DB01263.

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Fig. 1.

Representation of 3D and 2D conformation of complexes (a-b) Lupeol-5fsa, (c-d) Nyctanthic acid-5fsa, (e-f) Beta-amyrin-5fsa, (g-h) DB01263-5fsa, (i-j) Beta-amyrin-4lng, (k-l) DB01263-4lng, (m-n) Lupeol-5eqb, (o-p) DB01263-5eqb, (q-r) Apigenin-2xuc,and (s-t) DB01263-2xuc. In the 3D visualization, all receptor molecules are represented by a blue-wired ribbon pattern with interacting ligands Lupeol (red), Nyctanthic acid (maroon), Beta-amyrin (olive), and control drug DB01263 (green). In 2D figures, interacting amino acid residues are colored by their bonding type: hydrogen bonds (green), Van der Waals (light green), Alkyl/Pi-alkyl (light pink), Pi-Pi T-shaped (dark pink), Pi-sigma (purple), Pi-sulfur (yellow), Halogen-fluorine (sky), Pi-anion/cation (orange), and unfavorable donor-donor (red).

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In the crystal structure of sterol 14-alpha demethylase (CYP51) from the pathogenic yeast Candida albicans (5FSA), the binding affinity, hydrogen bonds, length of hydrogen bonds, and amino acid residues involved in van der Waals and other interactions of four different ligands are displayed in Table 1 and Figs. 1(a-t). Removing the amino acid group 14alphamethyl from lanosterol is a crucial step in the biosynthesis of ergosterol, which is necessary for the membranes of fungal cells. This process is catalyzed by the CYP51. CYP51 is also primarily targeted by clinical antifungals like azoles, which bind to heme iron in the active site to inhibit its activity.

The selected natural compound, lupeol, a triterpene compound present in different plants, has the highest binding affinity (-11.5 kcal/mol). Nyctanthic acid, a naturally occurring product from Nyctanthes arbor-tristis, comes in second place with -10.3 kcal/mol. The lowest binding affinity is -8.7 kcal/mol for DB01263, a synthetic azole drug, while another triterpene compound, beta-amyrin, has a binding affinity of -9.8 kcal/mol. According to these findings, beta amyrin and DB01263 are less effective CYP51 inhibitors than lupeol and nyctanthic acid (Table 1).

Figs. 1(g and h) demonstrated how two hydrogen bonds with LYS143 and HIS468, which have respective lengths of 2.70749 and 3.08699, form nyctanthic acid in CYP51-activated sites. Compared to nyctanthic acid and DB01263, lopeol and beta-amyrin have more amino acid residues involved in van der Waals interactions. Still, they do not form hydrogen bonds or interact with CYP51 (Figs. 1a-f). Three hydrogen bonds have been included in DB01263 by TYR505, SER507, and MET508, consisting of 2.70749, 3.08699, or 3.09413. Furthermore, DB01263 forms a pi-sulfur interaction with MET508 and a pi-pi stacked interaction with TYR118 (Figs. 1g and h). The effect of this interaction could be felt in DB01263’s CYP51 specificity and selectivity. These interactions may improve the ligand-protein complex’s hydrophobicity and stability, as depicted in Fig. 1. Beta-amyrin was observed to interact more strongly with binding affinity -9.0 Kcal/mol than the studied control drugs (-8.5 Kcal/mol). The interaction was mediated through the involvement of one Hydrogen bond: UNK1:H63 and B: ASP430:OD1, and through Van der Waals interaction of amino acid residues: LEU147, TRP153, TRP157, TRP371, ASP430, TYR432, and TYR436. Lupeol-5eqb complex was stabilized with significant binding energy(-10 Kcal/mol), which Van der Waals interactions of amino acid LEU147, TRP153, TRP157, TRP371, ASP430, TYR432, and TYR436 could facilitate. The Binding affinity of -8.4 kcal/mol was observed with the Apigenin-2xuc complex. Hydrogen bonds facilitated the complex: Forms hydrogen bonds between A: ASN62:HD21 and UNK1:O20. Van der Waals interaction amino acid residues: ASN76, GLN37, TYR125, PHE60, GLY123, ASP172, TYR232, and ASN233.

In the center is a ball stick pattern that displays all compounds. The interacting amino acid residues were shown as a pink stick pattern in 3D visualization and a sphere colored according to their interaction in 2D visualization. Remainders forming hydrogen bonds are displayed in dark green, while residues involved in the Van der Waals interaction are shown in light green. Also, light and dark pink hues indicated Pi-Pi stacking and Pi-Pi/Pi-alkyl interacting residues—a purple sphere displaying the remnants of the Pi-sigma bond. Various colored dotted lines illustrate the bond types that arise during compound interaction. An overview of the positions of ligands within CYP51’s active site and how they interact with heme groups and amino acid residues can be seen in 3D images. The two-dimensional representations display the schematic diagrams of the ligands and their interactions with CYP51. Various interactions, including hydrogen bonds, van der Waals contacts, pi-alkyl, pi-sigma, and pi-pi stacking interactions, are indicated by different colors and symbols. 2D representations help compare the similarities and differences between ligands and visualize binding modes.

The figure shows that the triterpene compound lupeol originated from various plants, has a complex structure, and binds to almost all CYP51’s active sites. PHE233, HIS468, TYR132, LEU139, LEU300, ILE304, GLY303, PHE126, THR122, GLY307, and PHE233 are among the amino acid residues with which it forms multiple van der Waals contacts. Additionally, it interacts pi-alkyl with TYR118, MET508, ILE131, LEU121, PHE228, TYR118, LYS143, and ILE471 (Figs. 1a and b). Smaller and more flexible than lupeol, nyctanthic acid is a compound in Nyctanthes arbor-tristis. It interacted twice with LYS143 and HIS468 in CYP51’s active region. Through van der Waals forces, it is also connected to GLY303, GLY308, GLY307, PHE126, PHE228, LEU139, ARG469, CYS470, and TYR132. It interacts through alkyl/pi-alkyl interactions with LEU376, LEU121, ILE304, and ILE471. It also forms a pi-sigma interaction with TYR118 (Figs. 1c and d).

Although the structures of lupeol and beta-amyrin, another triterpene compound, are similar, some differences exist in the conformation and orientation of the rings. It forms van der Waals contacts with GLY472, GLY308, GLY307, PHE126, THR122, GLY303, and ILE131. It forms a pi-sigma interaction with TYR118. It forms alkyl/pi-alkyl interaction with ILE304, ILE471, CGS470, TYR132, LEU376, PHE228, and LEU121 (Figs. 1e and f). DB01263, a synthetic azole medication, is significantly smaller and has a simpler structure than the other three ligands. It forms three hydrogen bonds with TYR505, SER507, and MET508 in the CYP51 active site. Together with GLY308, GLY307, LYS143, LEU139, GLY472, LEU204, PHE475, ILE471, ALA146, THR122, PHE228, PRO230, LEU87, SER378, PHE233, LEU121, and ILE379, it also creates van der Waals contacts. It forms a pi-sulfur interaction with MET508 and a pi-pi stacked interaction with TYR118. Moreover, TYR64, LEU376, ILE304, LEU150, ILE131, PHE380, and ILE131 interact alkyl/pi-alkyl with (Figs. 1g and h). The synthetic azole drug DB01263, compared to the other three ligands, is significantly smaller and has a simpler structure. Three hydrogen bonds are formed by it with TYR505, SER507, and MET508 in the CYP51 active site. Together with GLY308, GLY307, LYS143, LEU139, GLY472, LEU204, PHE475, ILE471, ALA146, THR122, PHE228, PRO230, LEU87, SER378, PHE233, LEU121, and ILE379, it also creates van der Waals contacts. When combined with MET508, it forms a pi-sulfur interaction; when combined with TYR118, it forms a pi-inverted pi interaction. Furthermore, it has alkyl/pi-alkyl interactions with TYR64, ILE304, LEU150, ILE131, PHE380, and ILE131.

It has been noted that the four compounds beta-amyrin, DB01263 (control), lupeol, and nyctanthic acid interact within the same 5FSA active site. The same binding pocket that interacted with the control DB01263 under study also contained the interacting amino acids, such as Tyr118, Phe380, Leu87, and others. Van der Waals, hydrophobic, or hydrogen bonding interactions helped to promote the binding. It has been observed that nyctanthic acid, beta-amyrin, and lupeol bind at the same interaction region as the control drug (DB01263). Therefore, these compounds may have comparable therapeutic potential by modulating the activity of 5FSA (Supplementary material S4).

4. ADMET

The prediction for ADME is shown in (Supplementary material S5). SwissADME is an online resource that provides an extensive library of predictive models for various physicochemical, pharmacokinetic, and drug-likeness properties of small molecules. The (Supplementary material S5) compares the ADME characteristics of four different ligands that bind to the crystal structure of sterol 14-alpha demethylase (CYP51) from the pathogenic yeast Candida albicans (PDB:5FSA). The cytochrome P450 enzyme CYP51 catalyzes the removal of the 14-alpha-methyl group from lanosterol, a critical step in synthesizing ergosterol, an essential component of the fungal cell membrane. This protein is also the target of most clinical antifungal drugs, such as azoles, which bind to the heme iron in the active site of CYP51 to prevent it from functioning.

As shown in (Supplementary material S5), the synthetic azole drug DB01263 has a high gastrointestinal (G.I.) absorption rate, meaning that the intestinal mucosa can easily absorb and permit it to enter the bloodstream. However, DB01263 cannot penetrate the central nervous system and cross the blood-brain barrier (B.B.B.). DB01263 is a substrate of P-glycoprotein (Pgp), an efflux pump that facilitates the removal of medications from cells and tissues. This suggests that Pgp-mediated efflux could lead to DB01263, which has reduced bioavailability and drug resistance. Moreover, DB01263 inhibits several cytochrome P450 (CYP) enzymes, such as CYP1A2, CYP2C19, CYP2C9, CYP2D6, and CYP3A4. These enzymes are responsible for the breakdown of drugs and other xenobiotics in the liver and other tissues. This suggests that DB01263 may have adverse effects and drug-drug interactions by inhibiting the metabolism of other medications or endogenous substances. Finally, because of its low log Kp value (-7.32 cm/s), which denotes poor skin penetration, DB01263 cannot be applied topically. (Supplementary material S5) shows that natural products with similar structures and ADME properties include lupeol, nyctanthic acid, and beta-amyrin. Because of their low G.I. absorption, they are all poorly absorbed by the intestinal mucosa and have low oral bioavailability.

Moreover, they cannot enter the central nervous system because they are not B.B.B. permeant. Since they are neither C.Y.P. nor Pgp enzyme substrates nor inhibitors, they are less likely to be affected by efflux or metabolism because of their low log Kp values (-1.9 cm/s for lupeol, -2.45 cm/s for nyctanthic acid, and -2.41 cm/s for beta-amyrin) and poor skin penetration.

(Supplementary material S5) shows that beta-amyrin, nyctanthic acid, and lupeol have low skin penetration, B.B.B. permeation, and G.I. absorption.(Supplementary material S5) shows that the synthetic azole drug DB01263, in contrast to the other three ligands, has poor drug-likeness properties. According to Lipinski’s rule of five, the high molecular weight (M.W.) of DB01263 is 700.78 g/mol, which is greater than the range of most medications (between 150 and 500 g/mol).

Furthermore, DB01263 has twelve rotatable bonds, exceeding Veber’s rule, which states that most drugs have nine or fewer rotatable bonds. DB01263 has a low bioavailability score of 0.17, less than the reasonable oral bioavailability threshold of 0.25. DB01263 has a moderate synthetic accessibility score of 6.02, meaning it is not easy to synthesize.

(Supplementary material S6) shows that natural products with properties resembling those of pharmaceuticals include beta-amyrin, nyctanthic acid, and lupeol. With a moderate molecular weight (M.W.) of 400–500 g/mol, each of them defies Lipinski’s rule, though this does not necessarily mean that they cannot be drugs. They all comply with Veber’s rule and have low rotatable bonds (0 to 4), indicating good oral bioavailability. They all have low numbers of donors and acceptors of hydrogen bonds (1 to 2), which means good membrane permeability according to Lipinski’s rule. All drugs have a common TPSA between 20 and 40 Ų, which violates Egan’s rule, which states that most drugs have a TPSA between 20 and 130 Ų. Low TPSA, however, can also be a sign of low solubility and good membrane permeability. They all have moderate to high bioavailability scores, ranging from 0.55 to 0.85, which indicates good oral bioavailability. None are straightforward to synthesize, with scores for average synthetic accessibility ranging from 5.49 to 6.04.

(Supplementary material S7) predicts several toxicity endpoints, including AMES mutagenicity, maximum tolerated dose (M.T.D.) in humans, human ether-a-go-go related gene (hERG) inhibition, oral rat acute and chronic toxicity, hepatotoxicity, skin sensitization, Tetrahymena pyriformis toxicity, and minnow toxicity. The (Supplementary material S7) also shows the standard cut-off values for each endpoint that indicate a high risk of toxicity. The data originated from the pkCSM server, a web-based platform providing a vast collection of prediction models for small molecules’ physicochemical, pharmacokinetic, and toxicological characteristics.

(Supplementary material S7) indicates that DB01263, a synthetic azole drug, has moderate to high toxicity when compared to the other three ligands. DB01263 is not an AMES mutagenic agent because it does not harm D.N.A. or result in mutations in bacteria. However, DB01263’s high M.T.D. of 0.682 log(mg/kg/day) exceeds the cut-off value of 0.477 log(mg/kg/day), implying a small safety margin in humans. DB01263 is also categorized as an hERG II inhibitor because it inhibits the hERG potassium channel, which regulates the cardiac action potential and may cause cardiac arrhythmias or sudden death. The drug (DB01263) has a moderate oral rat acute toxicity threshold, meaning that after a single oral administration, 3.076 log(mg/kg) is the dose at which 50% of rats die. DB01263 has the lowest recorded adverse effect level after repeated oral administration for 28 days, with a low oral rat chronic toxicity (LOAEL) of 0.198 log(mg/kg/day).

Furthermore, DB01263 is hepatotoxic, meaning it causes harm to the liver or liver malfunction. DB01263 is not a skin sensitizer because it does not result in allergic contact dermatitis or skin inflammation—50% of T growth at a given concentration. The low T. pyriformis toxicity of DB01263 (0.285 log(ug/L)), a unicellular ciliated protozoan used as a model organism for environmental toxicity testing, is inhibited. With a 50% lethal concentration at -3.711 log(LC50) for minnows, a small freshwater fish used as a model organism for aquatic toxicity testing, DB01263 has a very low minnow toxicity.

(Supplementary material S7) shows that beta-amyrin, nyctanthic acid, and lupeol are natural products with low to moderate toxicity and similar structures to DB01263. None induces hERG I inhibition, AMES mutagenesis, or skin sensitization. Their low M.T.D.s, ranging from -0.502 to -0.072 log(mg/kg/day), all indicate high human safety margins. They all have moderate oral rat acute toxicities, falling between 2.478 and 2.563 log(mg/kg), which means moderate doses kill 50% of rats after a single oral administration. They all have high oral rat chronic toxicities, ranging from 0.873 to 2.516 log(mg/kg/day), which indicate high doses that result in adverse effects after repeated oral administration for 28 days. Although lupeol and beta-amyrin are not hepatotoxic, nyctanthic acid is a Lopezine, and beta-amyrin is an hERG II inhibitor, but nyctanthic acid is not. Nyctanthic acid is a CYP2C9 inhibitor; lupeol and beta-amyrin are not. All of their low T. pyriformis toxicities fall between 0.292 and 0.383 log(ug/L), which indicates low concentrations that inhibit 50% of T. pyriformis growth. They all have moderate minnow toxicities, falling between -1.345 and -1.696 log(LC50), which indicates average concentrations that kill 50% of minnows. The (Supplementary material S7) provides valuable information about the toxicity properties of different CYP51 ligands, which can help evaluate their potential as antifungal drugs or lead compounds for drug discovery. The (Supplementary material S7) shows that DB01263 has moderate to high toxicity based on its high M.T.D., hERG II inhibition, hepatotoxicity, and low minnow toxicity. The table shows that acute and chronic oral rat toxicities, T. pyriformis toxicities, and low M.T.D.s of beta-amyrin, nyctanthic acid, and lupeol indicate low to moderate toxicity. However, they have some drawbacks, such as hepatotoxicity, CYP2C9 inhibition, mild minnow toxicities, and hERG II inhibition.

5. Molecular Dynamics and Simulation

We ran 100 ns simulations with a controlled drug and a 5fsa, 4lng, 5eqb, and 2xuc simulation for the best-chosen complexes. Also, we have extended the 5FSA complex simulation to 500ns. All of the simulated complexes’ RMSD values were found to vary between 0.2 and 0.4 nm (Fig. 2a). Except for a sudden increase fluctuating at a value of 0.3 nm that happened in the presence of the drug molecule after 80 ns of simulation, the 5fsa complexes with lupeol, the control drug DB01263, and nyctanthic acid exhibited similar values of less than 0.2 nm for the entire simulation period. According to the data, nyctanthic acid and lupeol are more stable than the control medication when interacting with 5fsa. The highest value was displayed by beta-amyrin-5fsa, which began at 0.3 nm and ended the simulation at 0.4 nm. The values in the RMSF plot ranged from 0.1 to 0.8 nm. It was observed that all complexes nearly displayed a value of 0.1 nm, with amino acid regions 350–360 and 440–475 exhibiting the highest fluctuation (Fig. 2b).

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Fig. 2.

2D representation of 5FSA simulation data extracted from trajectory files (a) RMSD plot, (b) RMSF plot, (c) Radius of gyration plot, and (d) Hydrogen bonds plot formation of hbonds during 100ns simulation. Where ns=nanosecond. Different colors show natural compound patterns: Beta-amyrin (black), Lupeol (green), control drug DB01263 (red), and nyctanthic acid (blue).

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The gyration plot’s radius, ranging from 2.3 to 2.35 nm, displays a consistent pattern (Fig. 2c). The beta-amyrin, lupeol, and nyctanthic acid complexes all showed values close to 3.2 nm, substantially less than the 3.35 nm value of the control medication, DB01263. For every complex, the hydrogen bond plot (Fig. 2d) displays the formation of 1–5 hydrogen bonds. During the simulation, it was found that while nyctanthic acid formed two hydrogen bonds, the control drug, DB01263, formed five hydrogen bonds.

beta-amyrin-4lng and DB01263-4lng have shown fluctuations over time, with values ranging between approximately 0.15 and 0.25 nm (Fig. 3a). Both complex simulations showed similar patterns, with an average value of 0.15 after reaching the stable state after 40 ns, but the DB01263-4lng complex stayed below beta-amyrin-4lng. beta-amyrin-4lng and DB01263-4lng have shown RMSF values between 0.1 and 0.25nm during the complete simulation (Fig. 3b). Radius of gyration (Rg) calculation leads to assessing the compactness of receptor biomolecules. beta-amyrin-4lng followed the DB01263-4lng fluctuation pattern and showed values ranging between approximately 2.15 and 2.25 nm, while both molecules showed an average value of 2.2nm until the end of the simulation (Fig. 3c). The binding of receptors and ligands leads to the formation of hydrogen bonds. Also, the hydrogen bond plot shows the number of hydrogen bonds formed during the 100ns simulation. beta-amyrin-4lng complex formed 1-2 hydrogen bonds while DB01263-4lng fomed 1-3 (Fig. 3d).

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Fig. 3.

2D representation of 4LNG simulation fluctuation patterns (a) RMSD plot, (b) RMSF plot, (c) Radius of gyration plot, and (d) Hydrogen bonds plot formation of bonds during 100ns simulation. Where ns=nanosecond. Natural compounds Beta-amyrin (black) and control drug DB01263 (red).

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Lupeol-5eqb and DB01263-5eqb have shown fluctuations in RMSD over time in nanoseconds. The RMSD values for both complexes fluctuate between approximately 0.1 and 0.5 nm over the 100 ns period. Both complexes show similar patterns, but DB01263-5eqb generally stays below Lupeol-5eqb with 0.2nm, while Lupeol-5eqb shows an average value of 0.3nm (Fig. 4a). Apigenin-2xuc and DB01263-2xuc displayed RMSF for amino acid residues ranging between 0.2-0.4nm. Both datasets remain below 2 nm and very close to 0.1nm for the simulation, indicating relatively stable fluctuations (Fig. 4b). The radius of gyration (Rg) measures the compactness of a molecule. The overall values for Rg were between 2.5 and 2.75nm. Lupeol-5eqb and DB01263-5eqb complexes showed average fluctuation between 2.55 and 2.6 nm over a 100 ns simulation period (Fig. 4c). The hydrogen bond plot represented the formation of hydrogen bonds during simulation. Lupeol-5eqb complex formed one hydrogen bond, while DB01263-5eqb formed 1-3 hydrogen bonds for the whole simulation period. The variation in hydrogen bond formation was observed at different time intervals (Fig. 4d). Apigenin-2xuc and DB01623-2xuc complexes RMSD plot showed an incremental pattern in the starting, but afterward stabilized at the end of the simulation Apigenin-2xuc showed an RMSD value near 0.15nm after reaching the stabilized state at 40ns simulation. DB01623-2xuc showed RMSD values near 0.1nm (Fig. 5a). RMSF analysis observed from the RMSF plot revealed that the overall value ranged from .05-0.45nm. Both complexes observed the highest peaks at amino acid regions 240-260. Both complexes showed similar average values of 0.05nm (Fig. 5b). Both compounds remained comparatively stable during an Rg value of 1.9nm throughout the observed period (Fig. 5c). DB01623-2xuc formed 1-3 hydrogen bonds, while Apigenin-2xuc formed 1-5 (Fig. 5d).

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Fig. 4.

2D representation of 5EQB dynamics simulation data (a) RMSD plot, (b) RMSF plot, (c) radius of gyration plot, and (d) Hydrogen bonds plot formation of hbonds during 100ns simulation. Where ns=nanosecond. The natural compound is Lupeol (green), and the control drug is DB01263 (red).

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Fig. 5.

2D representation of 5XUC simulation patterns (a) RMSD plot, (b) RMSF plot, (c) Radius of gyration plot, and (d) Hydrogen bonds plot formation of hbonds during 100ns simulation. Where ns=nanosecond. Natural compound Apigenin (dark green), and control drug DB01263 (red).

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The obtained data of Poisson-Boltzmann complex energy and ligand-receptor energy components calculations were presented in Supplementary materials S8 and S9:

The ΔGTotal value of -9309.00 (±16.15) kcal/mol indicates intense binding energy for this complex. It would be interesting to compare it with other ligand-receptor interactions of the Lupeol-5fsa complex. Like Lupeol-5fsa, Nyctanthic acid-5fsa exhibits a substantial binding energy with a ΔGTotal of -9332.83 (±17.54). The ΔGTotal value of -9388.77 (±12.60) suggests a favorable interaction for Beta-amyrin-5fsa. The DB01263-5fsa control complex has a ΔGTotal of -9378.26 (±23.37) (Supplementary material S8). It is a reference point for evaluating the other complexes [Supplementary material S8].

MMPBSA calculation of the whole complex of other receptors was also calculated. It was observed that Lupeol-5eqb showed ∆GTotal binding energy -10093.81 (±9.67) kcal/mol. DB01263-5eqb control also showed the approximately very close ∆GTotal -10153.05 (±9.33) kcal/mol, the lowest binding affinity. Nyctanthic acid-5fsa complex showed ∆GTotal -9332.83 (±17.54), Beta-amyrin-5fsa showed ∆GTotal -9388.77 (±12.60), and control complex DB01263-5fsa showed almost similar ∆GTotal -9378.26 (±23.37) kcal/mol. Beta-amyrin-4lng and DB01263-4lng control complexes were shown very near ∆GTotal, i.e., -7214.29 (±7.91) and -7125.83 (±9.32) kcal/mol, respectively. Apigenin-2xuc showed a slightly higher ∆GTotal -3247.56 (±13.93) than the DB01263-2xuc control complex -3192.70 (±36.31). Overall, the Lupeol-5eqb and DB01263-5eqb control complexes have shown significant binding energies, while Apigenin-2xuc and DB01263-2xuc have the least binding affinity.

Four complexes’ total binding energy (ΔGTotal) indicates the binding is significant. However, the magnitude of the binding energy varies between the complexes. Lupeol-5fsa has the most favorable binding energy, followed by DB01263-5fsa-control, Beta-amyrin-5fsa, and Nyctanthic acid-5fsa. The Van der Waals energy (ΔVdw) for all four complexes indicates attractive van der Waals interaction between the ligands and receptors. The electrostatic molecular energy (ΔEEL) is negative for all four complexes, indicating attractive electrostatic interactions between the ligands and receptors. The solvation energy (ΔGSolv) is positive for all four complexes, suggesting a penalty for transferring the ligands from the gas phase to the solvent. However, the solvation energy is less favorable for Lupeol-5fsa and DB01263-5fsa-control, which may contribute to their more favorable binding energies. The results obtained for the ligand-receptor complexes: Lupeol-5fsa, Nyctanthic acid-5fsa, Beta-amyrin-5fsa, and DB01263-5fsa-control. This value indicates a favorable binding energy of -26.35 (±0.74) for Lupeol-5fsa. It suggests strong interactions between the ligand and receptor. Like Lupeol-5fsa, Nyctanthic acid-5fsa exhibits a negative binding energy of -31.69 (±1.57) kcal/mol. The complex appears stable. Beta-amyrin-5fsa has shown comparable behavior. Its binding energy is also favorable, with the obtained value -28.47 (±0.58) kcal/mol. The control complex DB01263-5fsa has less negative binding energy -12.45 (±4.93) kcal/mol. It serves as a reference point.

Furthermore, we have also analyzed the ligand-receptor free energy calculation of other antifungal receptors’ energic components. Lupeol-5eqb complex ∆GTotal -28.70 (±0.44) has shown a favorable binding affinity due to Van der Waals forces and reasonable solvation energy contribution. Nyctanthic acid-5fsa complex shown ∆GTotal -31.69 (±1.57) kcal/mol, reflecting more stable interaction, like Lupeol-5eqb, but with slightly less negative values. The other complex, Beta-amyrin-5fsa and DB01263-5eqb control complexes show ∆GTotal -28.47 (±0.58) and -38.63 (±0.71) kcal/mol, respectively, where the control complex has better interaction. Interestingly, Beta-amyrin-4lng showed -29.81 (±0.38) kcal/mol binding affinity, which is significantly higher than DB01263-4lng control binding energy, i.e., -9.56 (±0.50) kcal/mol. Apigenin-2xuc has shown ∆GTotal -9.48 (±0.36) kcal/mol, which is a less favorable binding energy as compared to the control complex DB01263-2xuc shown ∆GTotal = -19.07 (±0.43) kcal/mol. Overall, the most substantial interaction is seen in the DB01263-5eqb control complex. This interaction has the highest overall binding energy (∆GTotal = -38.63 ± 0.71). Three complexes interacted well as compared to DB01263 in terms of binding interactions, with higher ∆GTotal values, namely Lupeol-5eqb ∆GTotal -28.70 (±0.44), Nyctanthic acid-5fsa -31.69 (±1.57), Beta-amyrin-5fsa-28.47 (±0.58). [Supplementary material S9]. These complexes have higher binding affinities, implying more persistent interactions with their target receptors. Also, β-Amyrin-4lng has better interactions than the DB01263-4lng control. β-Amyrin-5fsa has better interactions than the DB01263-5fsa control, which establishes β-Amyrin as a potential antifungal agent from studies of Nyctanthes arbor-tristis compounds.

5.1 5FSA 500ns extended MDS, PCA, and FEL

The RMSD plot was used to analyze the stability of the protein-ligand complexes. The beta-amyrin-5fsa (black) was observed to be the lowest deviation (∼0.2 nm), and the complex conformational structure remains unchanged over time, supporting the system’s more excellent structural stability and equilibrium state. However, Nyctanthic acid-5fsa (blue) was observed to have the highest fluctuations (∼0.35–0.4 nm), indicating possible instability. The control (DB01263, red) and lupeol-5fsa (green) exhibited moderate stability, with RMSD values around 0.25–0.3 nm, which signifies the potentiality of the beta-amyrin (Fig. 6a).

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Fig. 6.

Molecular dynamics (MD) simulation interactions analysis between selected ligand-protein complexes over 500 ns. (a) RMSD showing the structural stability of complexes. (b) RMSF explains the flexibility of each residue. (c) The radius of gyration (Rg) represents the compactness of the protein-ligand complexes. (d) Hydrogen bond analysis demonstrating the interaction stability between ligands and the target protein. Beta-amyrin-5fsa (black), control DB01263-5fsa (red), lupeol-5fsa (green), and nyctanthic acid-5fsa (blue) were compared.

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The RMSF plot was used to show residue-wise flexibility. The plot shows that Peaks correspond to highly flexible loop regions, while stable areas have lower RMSF values. These regions could undergo significant fluctuations or conformational changes throughout the critical simulation. High RMSF observed values indicate that these loops are flexible and may have the flexibility to move more freely. This flexibility could be necessary for the protein’s function and help these loops adopt variable conformations required for binding to ligands or other proteins. The beta-amyrin-5fsa (black) complex displayed minimal fluctuations, indicating strong binding stability. All ligand-bound systems followed a similar fluctuation pattern, with minor differences in loop regions (∼residue 350–450) (Fig. 6b). The Rg plot quantifies the tightly packed nature of the protein structure. A lower Rg value suggests a more folded conformation and stability. Beta-amyrin-5fsa (black) was observed with the lowest Rg (∼2.3 nm), signifying its compact structure. Nyctanthic acid-5fsa (blue) showed slightly higher Rg (∼2.35 nm), implying a less compact system. The control and lupeol-5fsa followed similar trends (Fig. 6c). The number of hydrogen bonds determines ligand-protein interaction strength. The control (DB01263, red) formed the highest number of hydrogen bonds (∼3–4 on average), suggesting strong interactions. Other ligands, including beta-amyrin-5fsa, formed fewer hydrogen bonds but remained stable over time (Fig. 6d).

Thus, Beta-amyrin has been found to exhibit the most stable and favorable binding energy, with fluctuations remaining within a lower range. Lupeol was also observed to be a relatively stable binding energy, though with slightly more fluctuations compared to beta-amyrin. Moreover, the complex exhibited the highest fluctuations and lowest favorable binding energy profile, suggesting weaker interactions. Among the studied data, the molecule beta-amyrin-5fsa demonstrated the highest stability, lowest fluctuations, compact structure, better efficacy, and less toxicity, making it proposing that it could be a strong candidate for further evaluation of its therapeutic potentialities. Also, MMPBSA analysis was conducted using the internal PBSA solver in sander at 10,001 most stable complex frames to determine the binding free energy of the used ligands to the receptor after extending the 500ns simulation. The binding free energy analysis revealed significant differences in ligand binding affinities. Among the tested ligands, beta-amyrin-5fsa exhibited the highest binding affinity with a ΔGTOTAL of -33.26 kcal/mol, followed closely by lupeol-5fsa (-32.73 kcal/mol) and nyctanthic acid-5fsa (-28.80 kcal/mol). The control ligand (DB01263-5fsa) showed a significantly weaker binding affinity (-12.03 kcal/mol), confirming the superior binding potential of the tested phytochemicals. The gas-phase energy (ΔGGAS) for all test ligands was more than that of the control, indicating strong receptor-ligand interactions. However, the solvation energy (ΔGSOL) partially counteracted this effect, particularly in nyctanthic acid-5fsa, which showed the highest solvation energy penalty (27.80 kcal/mol). However, the ligand was observed to maintain a strong overall binding affinity (Table 2); (Supplementary material S10).

Table 2. Shows MMPBSA Calculations performed using 10,001 complex frames and Poisson-Boltzmann calculations performed using an internal PBSA solver in a sander during a 500ns simulation.

Complex	ΔGGAS	ΔGGAS	ΔGTOTAL	SEM (Standard error mean)
Lupeol-5fsa	-48.85	16.12	-32.73	±0.03
Nyctanthic acid-5fsa	-56.67	27.80	-28.80	±0.04
beta-amyrin-5fsa	-57.42	24.17	-33.26	±0.04
DB01263-5fsa control	-12.03	7.81	-12.03	±0.11

The low standard error values (ranging from 0.03 to 0.11) indicate the reliability of the binding free energy estimates. The results suggest that beta-amyrin-5fsa, lupeol-5fsa, and nyctanthic acid-5fsa could be potential lead compounds with enhanced receptor binding affinity compared to the control ligand (Table 2).

The PCA was conducted by using Gromacs trajectory files. PCA results indicated distinct clustering patterns for different ligand-bound systems, suggesting variations in conformational dynamics (Figs. 7a and b). DB01263-5fsa and Nyctanthic_acid-5fsa (blue) showed relatively compact distributions, while Beta-amyrin-5fsa (black) exhibited a more spread-out cluster, implying higher conformational flexibility (Fig. 7a). The eigenvalue spectrum in Fig. 7(b) shows that the first few eigenvectors contribute significantly to the overall motion, with a rapid decay in eigenvalues, indicating that most of the system’s essential motions are captured by the first few principal components. This suggested that ligand binding affected the dominant motions of the system differently, influencing structural stability and flexibility.

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Fig. 7.

PCA of MDS data from Ligand-5FSA systems. (a) Projection of molecular dynamics trajectories onto the first two principal components (eigenvectors) for four ligand-bound systems: DB01263-5fsa (red), Nyctanthic_acid-5fsa (blue), Lupeol-5fsa (green), and Beta-amyrin-5fsa (black). (b) Eigenvalue spectrum showing the contribution of each eigenvector to the overall system fluctuations.

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Furthermore, the FEL analysis indicated significant variations in the conformational stability and flexibility of the ligand-bound complex Beta-amyrin-5fsa and Lupeol-5fsa show multiple basins, explaining higher conformational variability and dynamic transitions between metastable states. The used control drug (DB01263-5fsa) showed a well-defined deep energy basin, supporting a stable binding conformation (Figs. 8a-c). Nyctanthic_acid-5fsa (indicated a different free energy minimum with a relatively broader basin, indicating moderate stability with some flexibility (Fig. 8d). FEL analysis revealed that ligand binding affected the free energy landscape, with DB01263-5fsa representing the most stable conformation, while other studied molecules permit greater conformational adaptability.

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Fig. 8.

3D FEL Analysis of ligand-bound complex systems. The FEL maps show the conformational energy profile of ligand-bound systems along the first two principal components (PC1 and PC2). (a) Beta-amyrin-5fsa, (b) Control (DB01263)-5fsa, (c) Lupeol-5fsa, and (d) Nyctanthic_acid-5fsa. The color gradient represents free energy (kJ/mol), where blue regions indicate energetically favorable (low free energy) conformational states and red regions represent high-energy states.

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Additionally, the convergence analysis of RMSD, RMSF, Rg, and Energy based on the SAM analysis results confirmed the flexibility, stability, and compactness of protein-ligand complexes during this analysis. The selected molecules confirm the binding stability, which is close to that of the positive control DB01263-5fsa, identified as the most stable complex. However, Nyctanthic acid-5fsa exhibited greater flexibility and a less compact structure (Supplementary material S11).

The CAM analysis accurately confirmed the complicated behaviors, which helped to improve the clarity of trend identification across different criteria. The pronounced stability and compactness of DB01263-5fsa and beta-amyrin-5fsa indicate beneficial and favorable interactions. The convergence of CAM-energy values across the complexes confirmed their equilibrium state and emphasized the predictability of the results we obtained (Supplementary material S12).

The prevalence of medication resistance, namely in the azole family of drugs used to treat fungal illnesses, is steadily increasing despite advancements in clinical understanding and treatment methods. This poses a significant threat to public health globally. Furthermore, miconazole, fluconazole, itraconazole, and ketoconazole have all been associated with the development of acquired long QT syndrome [35] and cardiac arrhythmias, and the search for novel antifungal molecules is always desirable for the public health system. Chemicals and extracts from natural resources—plants, in particular—are required to treat fungal infections because they are the primary source of therapeutic molecules used in modern medicine. A common and ongoing threat to public health is fungal infections (Kathiravan et al., 2012; Ramirez et al., 2013). Despite its well-established toxicities, the polyene antibiotic amphotericin B is often used to treat severe fungal infections (Odds et al., 2003). Due to prolonged exposure, drug interactions, and side effects like vision impairment, fluconazole is known to cause resistance to Candida species (Canuto and Rodero 2002) (Chen and Sorrell 2007). Resistance to commonly used antibiotics is increasing due to the increasing use of antifungal treatment, even in people who have never been exposed to the drug (Arif et al., 2009; Arendrup et al., 2014). One of the most urgent problems facing therapeutics is the emergence of fungal strains resistant to antibiotics. Creating new antifungal medications as soon as possible is crucial to address this issue (Johnson et al., 2007; Jianhua and Hai, 2009; Zorofchian Moghadamtousi et al., 2014). Creating novel active compounds and features depends heavily on utilizing natural resources. Natural substances as antifungal therapies provide excellent safety when employed with efficacy and precision in dosage, timing, and application method (Vengurlekar et al., 2012). Numerous bioactive secondary metabolites, such as tannins, saponins, alkaloids, terpenoids, flavonoids, and other compounds with antifungal properties, are found in plants (Arif et al., 2009). According to the study, the N. arbor-tristis plant has antifungal compounds, suggesting that the plant could develop into a novel antifungal medication that inhibits the enzyme responsible for synthesizing cell walls and could eventually replace the widely used antibiotics. Therefore, there is a need for new antifungal drugs with improved safety records, low side effects, lower costs, easier accessibility, and higher effectiveness against fungal infections. Encoded by a superfamily of genes, cytochromes, or P450 enzymes, are a class of heme-containing monooxygenases that are present in both prokaryotes and eukaryotes. These metabolizing enzymes aid the oxidation of pharmaceuticals, insecticides, and biosynthetic intermediates. They are also essential in activating a variety of carcinogens in eukaryotes. Most cytochromes P450 in mammals are found in the endoplasmic reticulum and are part of an intricate network that transports electrons. Cytochrome B6, Cytochrome B5, and Nicotinamide adenine dinucleotide phosphate (NADPH)-cytochrome P450 reductase are components of this system. Many distinct cytochrome P450 proteins are found in yeast and fungi, and the genes that produce these proteins have been found. Among them, Saccharomyces cerevisiae’s lanosterol l4a-demethylase (ERGl 1) has been investigated the most. This particular cytochrome P450 enzyme helps remove the methyl group from lanosterol at position C-32, an essential step in synthesizing ergosterol, a sterol present in yeast. The equivalent enzyme in mammals carries out the same reaction during cholesterol biosynthesis. Studies have supported this information (Aoyama et al., 1987, Yoshida 1988). Several antifungal medications, such as ketoconazole and itraconazole, specifically target lanosterol 14a-demethylase(Vanden Bossche et al., 1986). Scientists exploited this property in their study to extract the S. cerevisiae ERGll gene. To confer resistance to ketoconazole, they used a multicopy plasmid encoding lanosterol l4a-demethylase (Kalb et al., 1986). Afterward, Kalb et al. presented a thorough sequence analysis of the gene and demonstrated its importance for aerobic growth (Kalb et al., 1987).

CYP51 inhibitors are highly beneficial antifungal medications, particularly effective against infectious fungi. Sterol 14-alpha-demethylase, often referred to as CYP51 or Lanosterol 14-alpha-demethylase, is an essential enzyme that plays a key role in the production of sterols, including cholesterol, in both prokaryotes and eukaryotes. (Singh et al., 2023) CYP51 has a crucial function in converting lanosterol to ergosterol, an essential element of fungal cell membranes. Its activity is a desirable target for antifungal drugs as it disrupts fungal membrane integrity, and didymellamides from plants have been described as CYP51 inhibitors. (Sama-ae et al., 2023), resulting in the death of the fungal cells. A variety of antifungal medicines generated from azoles function by selectively inhibiting CYP5112.

Farnesyltransferase is a catalytic protein that catalyzes the addition of a farnesyl group to the protein. Farnesyltransferase aids in protein prenylation in fungi, altering the location and function of proteins. (Kim et al., 2023). This enzyme could stop fungi from growing and sending signals. Researchers have studied farnesyltransferase inhibitors in the context of cancer, but are still considering their use against fungi. Chitinase is an enzyme that degrades chitin, a primary constituent of fungal cell walls. They break down chitin into smaller pieces through hydrolysis. Therefore, by explicitly targeting chitinases, the integrity of the fungal cell wall is disrupted. (Hu et al., 2023, Zhao et al., 2023), making the fungus susceptible to natural stress and immune system responses. Chitinase inhibitors have the potential to be created as antifungal pharmaceuticals. However, investigations into this field are still in progress. Many plant-derived phytochemicals have been explored as potential antifungals. The phytochemicals of this plant have the potential to inhibit by targeting different cellular components of fungal cells. These enzymes have vital functions in producing necessary components inside fungal cells. Investigating plant-derived drugs that target these enzymes could offer valuable approaches to battling fungal infections. Additional research and medication development efforts are required to utilize their promise in clinical situations fully.

Complementary in silico docking analyses have further substantiated the results of this finding by revealing high binding affinities of lupeol to key fungal targets that could be involved in ergosterol biosynthesis, such as lanosterol 14α-demethylase. These interactions suggest that lupeol may inhibit ergosterol synthesis, leading to impaired membrane formation and fungal cell death. Similarly, Nyctanthic acid, a phenolic compound derived from Nyctanthes arbor-tristis, has stated promising antifungal activity in recent studies. In vitro assays reported that that Nyctanthic acid effectively inhibited the growth of clinical isolates of Candida and Cryptococcus species. Molecular docking studies have provided insights into its mechanism, indicating strong binding affinity to fungal enzymes like chitin synthase and β-glucan synthase—key enzymes involved in the synthesis of cell wall components. By targeting these enzymes, Nyctanthic acid potentially hampers cell wall formation, rendering the fungi more susceptible to environmental stress and immune responses. Collectively, these recent in silico studies underscore the potential of lupeol and Nyctanthic acid as promising antifungal agents, acting through mechanisms that interfere with essential fungal biosynthetic pathways and structural integrity

6. Conclusions

Antifungal medications specifically target sterol 14-alpha demethylase, farnesyltransferase, lanosterol 14-alpha demethylase, and chitinase, critical proteins involved in the production of many cellular components of fungal cells, including ergosterol, a unique sterol that is exclusive to fungus, and chitinase Using investigated molecules Lupeol, Nyctanthic acid, Beta-amyrin, Apigenin, molecular docking, and dynamics simulation techniques were used to characterize the binding sites of target proteins. Our study’s findings suggest that active compounds from this plant, like ketoconazole and itraconazole, have a strong affinity for a specific target interaction region. Intermolecular forces, such as hydrogen bonds, promote this binding and produce a significant binding energy to stabilize the protein-ligand complex. The studied compounds Lupeol, Nyctanthic acid, Beta-amyrin, and Apigenin- have good drug-likeness attributes, as indicated by their low number of rotatable bonds, high bioavailability scores, and moderate molecular oral viability scores (MOVs). However, some of their shortcomings include their average synthetic accessibility ratings and poor TPSA. Moreover, despite cutting down on the cost of experimentation, computational studies need to be validated through in vitro and in vivo studies. Thus, the result of this study suggests that Lupeol, Nyctanthic acid, Beta-amyrin, and Apigenin could be significant anti-fungal agents that could be used to control many fungal-mediated food-crop spoilages and animal diseases, including humans.