GC–MS analysis of phytoconstituents from Kigelia africana (Lam.) Benth., and molecular docking interactions of bioactive molecules with target Penicillin-Binding Protein 2 (PBP2)

doi:10.21203/rs.3.rs-3970620/v1

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GC–MS analysis of phytoconstituents from Kigelia africana (Lam.) Benth., and molecular docking interactions of bioactive molecules with target Penicillin-Binding Protein 2 (PBP2)

https://doi.org/10.21203/rs.3.rs-3970620/v1

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In the present scenario, people are practicing the natural medicine from plants and its various parts to cure so many diseases. Gonorrhea is a Sexually Transmitted Infection (STI) caused by the bacterium Neisseria gonorrhoeae. If left untreated, gonorrhea can lead to serious health problems. Although symptoms of gonorrhea can vary, 10% of men and 50% of women who suffer from N. gonorrhoeae infection may not show any symptoms at all. Unfortunately, until then there is neither a vaccine nor an effective treatment. The bark of Kigelia arficana is traditionally used to treat syphilis and gonorrhea. During cell development in N. gonorrhoeae, the enzyme penicillin-binding protein 2 (PBP2) is required for cell wall formation. The aim of this work is to investigate the molecular interactions of three PBP2 variants with bioactive molecules from K. africana using molecular docking and ADMET analysis. 13 phytochemicals were selected based on how well each PBP2 protein receptor was docked after docking results were evaluated using the Glide score. The results of the docking analysis were evaluated using the Glide score, and the 13 compounds docked to each PBP2 protein receptor were selected. In addition, the selected phytocompounds were subjected to ADMET analysis, suggesting that they have the potential for therapeutic development. Among the selected 13 bioactive compounds, the docking score of 6-hydroxyluteolin Glide XP docking score is -10.225, the Glide XP energy (Kcal/Mol) is -35.841, the Glide XP emodel is -51.155 and the MM-GBSA binding score is -78.215 (Kcal/Mol)for PBP2. The results of the study suggest that these phytocompounds could potentially be used to treat N. gonorrhoea. Based on the efficiency of molecular docking, the present study concluded that they could be potential drug candidates for the development of drugs against N. gonorrhoea.

K. africana

GC-MS analysis

ADMET

Molecular docking

N. gonorrhoeae

One million men, women and children are affected by sexually transmitted infections (STIs), which are a leading cause of sudden illness, infertility, long-term disability and mortality with serious medical and psychological consequences. Over 30 bacterial, viral and parasitic infections can be transmitted through sexual contact. The most common sexually transmitted diseases are Neisseria gonorrhoeae, Trichomoniasis, Candidiasis, Chlamydia, Syphilis, Bacterial vaginosis, Human Immunodeficiency Virus (HIV) and Herpes Simplex virus infections¹.

Neisseria gonorrhoeae, often known as gonococcus (singular) or gonococci (plural), was identified as gram-negative diplococci bacterium by Albert Neisser in 1879. It is responsible for gonorrhoea, a sexually transmitted genitourinary infection, as well as disseminated gonococcemia, septic arthritis, and gonococcal ophthalmia neonatorum. N. gonorrhoeae can infect the genitals, throat, and eyes². It is the second most common bacterial STI worldwide after Chlamydia trachomatis. In 2016, the World Health Organization (WHO) predicted 87 million new cases of N. gonorrhoeae worldwide³. Although both men and women can suffer from dysuria and purulent urethral discharge, the vast majority of gonorrhea patients are asymptomatic. Untreated infections can lead to serious problems such as epididymitis and salpingitis, as well as pelvic inflammatory disease, ectopic pregnancy, and infertility. Gonorrhea can also cause complications during pregnancy and can be passed on to children, which can lead to blindness if left untreated. Like other sexually transmitted infections, N. gonorrhoeae may play a role in the transmission and acquisition of human immunodeficiency virus⁴.

Neisseria gonorrhoeae is one of the most common bacterial infections associated with gonorrhea and its consequences. The bacterial pathogen N. gonorrhoeae causes symptoms when an asymptomatic infection spreads through the vaginal canal or to distant organs⁵. Asymptomatic infection can affect both men and women. An untreated gonorrhea infection can spread throughout the body, especially to the joints (septic arthritis) (disseminated gonorrhea infection). An untreated infection can cause pelvic inflammatory disease in women and, as a result of scarring, infertility⁶.

New drugs with unique chemistry and mode of action are urgently needed worldwide to combat the public health threat posed by antibiotic resistance. Due to economic and regulatory hurdles, the pharmaceutical industry's research into new antibiotics, which had previously been successful in combating antibiotic-resistant microorganisms, had come to a standstill⁷. In 2016, the United Nations (UN) World Health Assembly approved the WHO Global Health Sector Strategy for Sexually Transmitted Infections 2016–2021. The main goal is to reduce the prevalence of gonorrhea worldwide by 90% to achieve this goal⁸.

Nowadays, molecular docking is a popular structure-based in silico method used in drug discovery. Docking enables the discovery of new therapeutic compounds, the prediction of ligand-target interactions at the molecular level, and the visualization of structure-activity associations without knowing the chemical structure of other target inhibitors⁹. It is one of the most commonly used virtual screening methods, especially when the 3D structure of the target protein is available. This technique was able to estimate the protein-ligand binding affinity as well as the design of the protein-ligand complex, which is useful for lead optimization¹⁰. Therefore, in this work, we evaluated and confirmed the effectiveness of 13 phytoconstituents from K. africana their interactions with N. gonorrhoea through molecular docking.

2.1. Collection of Plant

The collection of fresh barks of K. africanawere was collected from Thanjavur Medical College Hospital, Thanjavur, Tamil Nadu, India (10.7870244° North and 79.1378024° South), and transported to research laboratory, Annai Vailankanni Arts and Science College, Thanjavur. Authentication of the plant was carried out by expert botanists and voucher specimen kept in laboratory for future reference as per method reported earlier¹¹.

2.1.1 Preparation of K. africana bark extract

The 1.5 kg of plant material (bark) was air-dried in the shade, coarsely powdered (Sieve no. 40), and defatted with petroleum ether (60–80 ºC) using a Soxhlet apparatus through a series of solvent extraction steps including n-hexane, chloroform, ethanol, ethyl acetate, and distilled water. Using a rotating vacuum evaporator, the extracted sample was dried out. The extract's ultimate yield was computed based on the dry weight of the powdered bark¹².

2.1.2 Preliminary phytochemical analysis

Preliminary phytochemical screening the dried bark extracts of K. africana methanol solutions were assessed for the existence of phytochemical analysis using the standard methods¹³.

2.1.3 GCMS-analysis Bark extract of K.africana

One microliter of the material was injected into the GC-MS instrument's injecting column to perform compound analysis. The Shimadzu GC-MS-QP2010S system was operated under the following chromatographic conditions: a 30-meter-long, 0.25-mm-diameter, 0.25-micrometer-thick DB-5MS column was employed. The temperature range of the oven that is employed is 70–300°C ¹⁴.

2.2 In silico analysis

2.2.1 Biological Dataset

This computational analysis was carried out in the packages of Schrodinger suite which includes ligprep, sitemap, grid generation, glide XP dock, MMGB-SA analysis ADMET properties and further computational approaches.

2.2.2 Protein optimization

The crystal structure of the Neisseria gonorrhoeae receptor and its active site was retrieved from the RSCB Protein Data Bank (PDB ID: 6VBC). The hetero atoms and water molecules were removed from the crystal structure using Schrodinger Maestro software. The structureof the protein was further optimized using the Protein preparation wizard (v.4.1.0) based on the energy minimal¹⁵.

2.2.3 Ligand optimization

Compounds with anti N. gonerreahoe activities isolated from natural products were selected as ligands through a GCMS analaysis of K. africana (Table 1). The collected bioactive molecules were loaded and processed by employing Ligprep module. With this module, the secondary plant metabolites were prepared for docking. To improve the topography of the selected phytochemicals, the OPLS force field was used in the ligand preparation¹⁶.

Table 1

Preliminary phytochemical test for methanolic extract of barks of *Kigelia africana* (Lam.) Benth.
S. No	Phytochemicals	Test	Aqueous extract
1.	Alkaloids	Dragendorff's	+
2.	Glycosides/Sugars	Molish	+
3.	Flovonoids	Shinoda	+
4.	Phenols	Ferric Chloride	+
5.	Saponins	Froth	+
6.	Steroids	Liebermann–Burchard	+
7.	Tannins	Lead acetate	+
Presence of phytochemical is denoted by (+) sign; absence of phytochemical is denoted by (-) sign.

2.2.4 Molecular docking

Mechanics-generalized Born surface area (MM − GBSA) binding energy calculations were conducted in Schrödinger Maestro V.12.7. 6VBC structures were prepared using Protein Preparation Wizard. We removed water molecules and other redundant, postcrystallization small molecules. The structures were minimized in the OPLS3 force field. Ligands were prepared in LigPrep. Docking was conducted in Glide with standard precision (SP).58,74 MM − GBSA binding energycalculations were performed using Prime, with VSGB salvation model75 and OPLS3 force field^15,16.

2.2.5 MM-GBSA

Generalized docking and molecular mechanics Schrödinger Maestro V.12.7 was used to do calculations of born surface area (MM–GBSA) binding energy. Protein Preparation Wizard was utilized in the preparation of Neisseria gonorrhoeae structures. Water molecules and other unnecessary tiny molecules that formed after crystallization were eliminated. The OPLS3 force field minimized the structures. In LigPrep, ligands were prepared. In Glide, docking was done with standard precision (SP). Prime was used to calculate the MM–GBSA binding energy using the VSGB solvation model and the OPLS3 force field¹⁷.

2.2.6 ADMET analysis

Using Schrödinger QikProp, we computed the physicochemical characteristics of the chosen substances. Next, using Lipinski's method 5 to identify compounds with the appropriate physicochemical characteristics, we adjusted the log P value to account for the high hydrophobicity of N. gonorrhoeae ligands. The precise values are as follows: MW ≤ 500 g/mol, log P ≥ 3, the number of rotatable bonds < 10, the number of hydrogen bond donor’s ≤ 5, and the polar surface area (PSA) ≤ 140 Å2^{17, 18}.

3.1. Phytoconstituents of methanol extract of K. africana bark

Phytochemical analysis of methanol bark extract of K. africana revealed that Alkaloids, Glycosides/Sugars, Flovonoids, Phenols, Saponins, Steroids and Tannins were present in the extract (Table 1). Anthraquinones, alkaloids, terpene and steroids were absent from the extracts.

The abundance of secondary metabolites in the K. africana plant gives it a wide range of therapeutic benefits. These substances include volatiles, naphthoquinones, irridoids and flavonoids, etc. The methanol extracts of the bark of K. africana were analyzed by GC-MS. Gas chromatography was carried out for approximately 32 minutes. The fractions separated from the GC were analyzed in the mass spectrometer. These compounds were used as ligands for docking analysis. A total of 13 bioactive molecules were identified from the bark extracts of K. africana (Fig. 1). The obligate pathogen N. gonorrhoeae occurs exclusively in humans and usually causes urethritis in men and cervicitis in women. Bacteria categorized as obligate pathogens are those that require disease to spread through the host. These bacteria cannot survive on their own; They need a host to thrive. Urogenital gout infections, which typically (but not always) affect women, can spread through the upper urogenital tract and cause a number of serious reproductive consequences if left untreated. Examples of these problems include endometritis, pelvic inflammatory disease, infertility, and/or potentially fatal morbidity due to ectopic pregnancy. In the present study, the crystal structure of the transpeptidase domain of PBP2 from N. gonorrhoeae was previously analyzed.

3.1.1 GC-MS analysis of methanol extract of K. africana bark

From the GC-MS analysis of the methanol extract of the bark of K. africana, a total of 13 compounds were identified that showed various phytochemical activities. The chromatogram is shown in Fig. 2, while the chemical components with their retention time (RT) and peak area (%) are listed in Table 2. The following bioactive compounds were present in the GC-MS analysis of the methanol fraction of K. africana bark.

Table 2

GC-MS Chromatogram analysis of methanolic extract fraction of *K. africana* bark
S. No	Retention time	Name of compound	Peak Area %
1	9.999	2-acetylfuro-1,4-naphthoquinone	18.42
2	13.926	Atranorin	25.56
3	34.855	Kigelinone	7.11
4	37.487	p-Coumaric acid	5.44
5	37.583	Lapachol	7.49
6	37.747	6-hydroxyluteolin	4.8
7	38.455	6-Methoxymellein	5.73
8	39.066	Kojic acid	1.22
9	39.421	Norviburtinal	1.28
10	39.574	Balaphonin	2.9
11	39.885	Caffeic acid	1.4
12	39.906	Luteolin	2.91
13	39.985	Ferulic acid	5.3

3.1. In silico analysis and validation

3.1.1 6-Methoxymellein

As a result of in silico analysis we examined the active site where 6-Methoxymellein binds to the target and found that it strongly interacted with the PPB2 residue to form a hydrogen bond. The SER A: 545, SER A: 310 were in contact with the ligand atoms and TYR A: 544 formed contacts with the side chain and π-π stacking contacts with PPB2. It had a first superior docking score to that of the other bioactive molecules, which is shown in Fig. 3 & Table 3. Among the selected 13 bioactive compounds, 6-hydroxyluteolin Glide XP docking score is -10.225, Glide XP energy (Kcal/Mol) -35.841, Glide XP emodel − 51.155 and MM-GBSA and Gbind score − 78.215 (Kcal/Mol) for PBP2. An intricate network of intermolecular interactions determined the surfaces as the PPB2 target residues interacted with the ligand atoms. Both the non-specific forces outside the target binding pocket and the specific interactions at binding site are required for such interactions to occur. The pattern of interaction in this complex between 6-Methoxymellein and PPB2 receptor. Similarly Hani Mohammed Ali, 2022 reported that the three conserved sequence motifs that make up the PBP2 active site are found in almost all betalactamases. Based on earlier research, the SXXK motif is situated at the N-terminal end of helix α2 and comprises two residues, Ser310 and Lys313, which are crucial for catalysis².

Table 3

List out the selected bioactive molecules from *K. africana* bark extract against PPB2 receptor (PDB entry: 6VBC) and its docking score (kcal/mol) of with and standard medicines detected by *in silico* analysis.
Phytochemicals Type	Phytoconstituents	Glide XP docking score	Glide XP energy(Kcal/Mol)	Glide XP emodel	MM-GBSAd Gbind (Kcal/Mol)
Coumarians	6-Methoxymellein	-10.225	-35.841	-51.155	-78.215
	Kigelinone	-9.738	-37.973	-55.498	-79.883
Phenolic Compounds	6-hydroxyluteolin	-8.973	-41.207	-45.167	-63.837
	Atranorin	-8.903	-41.168	-56.312	-53.223
	Balaphonin	-8.886	-35.862	-41.492	-51.610
	Caffeic acid	-8.88	-36.763	-47.696	-55.334
	Ferulic acid	-8.798	-38.029	-49.85	-59.114
	Luteolin	-8.638	-43.25	-51.467	-41.232
	p-Coumaric acid	-8.583	-40.982	-49.263	-43.471
Quinones	2-acetylfuro-1,4-naphthoquinone	-8.498	-35.597	-40.378	-58.673
	Kojic acid	-8.277	-37.699	-50.559	-42.152
	Lapachol	-8.254	-35.094	-42.556	-58.194
	Norviburtinal	-8.253	-33.693	-44.109	-43.136
Synthetic drugs	Ceftriaxone	-7-292	-38.219	-41.283	-44-328

Table 4

Assessment of drug-like properties of the phytocompounds from *K. africana* bark extract
S.No	Ligands	Molecular Formula	Molecular Weight (g/mol)	LogP	No of Hydrogen bond Donor	No of Hydrogen bond Acceptor	Number of rotatable bonds	Lipinski’s Rule of Five
1.	6-Methoxymellein	C₁₁H₁₂O₄	208.21	1.502	1	4	1	3
2.	Kigelinone	C₁₄H₁₀O₅	238.239	1.42	3	4	1	0
3.	6-hydroxyluteolin	C₁₅H₁₀O₇	302.23		5	7	1	2
4.	Atranorin	C₁₉H₁₈O₈	374.341	2.547	3	8	6	1
5.	Balaphonin	C₂₀H₂₀O₆	356.369	2.831	2	6	6	0
6.	Caffeic acid	C₉H₈O4	180.159	1.196	3	3	3	0
7.	Ferulic acid	C₁₀H₁₀O₄	194.186	1.499	2	3	3	0
8.	Luteolin	C15H10O6	286.239	2.282	4	6	1	0
9.	p-Coumaric acid	C9H8O3	164.158	1.49	2	3	2	0
10.	2-acetylfuro-1,4-naphthoquinone	C14H8O4	240.211	2.258	0	4	1	0
11.	Kojic acid	C6H6O4	142.109	-0.162	2	4	1	0
12.	Lapachol	C15H14O3	242.270	3.234	1	3	2	0
13.	Norviburtinal	C9H6O2	146.145	2.197	0	2	1	0

3.1.2Kigelinone

Kigelinone's glide energy values are displayed in Table 1 and its docking score, which was close to that of Kigelinone among the 13 ligands, was − 9.738. The residue interactions with the ligand atoms were seen and the docked complex was analyzed. The residue interactions of LYS 313, ASN 364, GLN 345, THR 498, SER 310, and TYR 422 are displayed in the interaction plot. Different types of bonding lines were engaged in the formation of the connections, which included hydrophobic contacts with Kigelinone and back and side chain contacts Fig. 4 & Table 3.In the same way, K. africana’s bioactive components were identified by Olofinsan et al. (2023) as possible TNF-α converting enzyme inhibitors. The proposed compounds interact hydrophobically with amino acid residues Ala439, Val440, Val434, Tyr433, Ile394, and Leu401, as well as at the S1' pocket of the protein active site with other amino acid residues (Gly442, Ser441, Asn447, Glu398, and Lys432). It has been discovered that kigelinone inhibitors interact with the hydrophobic pocket of S1, leading to the selective inhibition and removal of physiological adverse effects¹⁹.

3.1.3 6-hydroxyluteolin

6-hydroxyluteolin showed that each ligand, particularly had a strong interaction with the 6VBC receptor. The 6-hydroxyluteolin is a third one of the better docking score − 8.973 interacts with the A-SER 545, TYR-A-544 SER, A-310, SER A-362 amino acids residues and hydrogen bonds side chains, back chains Fig. 5 & Table 3. According to Ogbodo et al., 2023, reported that 6-hydroxyluteolin had a one of better interacts with potential inhibitors targeting cdk1 in colorectal cancer²⁰.

3.1.4Atranorin

Atranorin had the fourth highest docking score of -8.903and its glide energy value is shown in Table 3. It showed good binding affinities with the target residues. The scrutinized docked complex clearly showed the residue contacts. Specifically, THR 498, TYR 422, SER 310, LYS313,GLN 345 and ASN 364 formed contacts with various atoms of Atranorin. The interaction plot clearly shows the residue contacts with the side chain, back chain, and π-π stacking THR 498, TYR 422, SER 310 and GLN 345 formed H-bond back chain contacts. The remaining residues, LYS 313 and GLN 345 formed H-bond side chain contacts with Atranorin Arg327 formed covalent H-bond contacts with the ligand. The ligand molecule residue contacts, hydrogen bond distance values, and the types of contacts are shown in Fig. 6 & Table 3. Similarly Santanu Paulet al., 2023, investigated that it was observed that atranorin shows the lowest binding energy with CCND 1(-8.8 Kcal/mol), which is even lower than the standard drug against to treat for Anti-Hepatocarcinoma Activity and were substantiated by in silico docking study of three major compounds present in Parmotrema tinctorum against anti-apoptotic proteins, where atranorinhave shown the lowest binding energies with Bcl-2 and Bcl-XL, thus proving that bothatranorin has the potential to restrict the anti-apoptotic proteins from blocking the apoptotic pathway²¹.

3.1.5Balaphonin

Balaphonin showed the fifth highest docking score of -8.886and a good glide energy value, which was the highest in this study (Table 3). It also showed good binding affinity. The docked complex showed a higher level of residue interactions than did the other ligand interaction patterns in this study. Particularly, GLN 345, THR 347, SER 545, THR 498-π stacking TYR 422 was involved in the H-bond side chain contacts with Balaphonin. These amino acid residue formed covalent contacts with the functional groups of the ligand and its molecule residue contacts, hydrogen bond distance values, and the types of contacts are shown in Fig. 7.

3.1.6Caffeic acid

Caffeic acid was located in Table 3 with a decent gliding energy value and the sixth-highest docking score of -8.88. It did, however, show a lower binding affinity than the previously stated small molecules. The docked complex interaction template indicated residue interactions with LYS 361, SER 362, SER 545, and THR 500. Furthermore, THR 500 generated H-bond side chain connections with caffeine, while SER 361, SER 362, LYS 361, and SER 545 produced H-bond back chain connections. It was also covalently bound to the functional groups of the ligand (Fig. 8). Caffeine can reduce Fyn kinase activity, block the PKC signaling pathway, and produce less PGE2, per a previous study by Mazumder et al. (2022)²².

3.1.7 Ferulic acid

Ferulic acid was showed the one of the highest docking score (-8,798) with a good glide energy (Table 3). Docked complex examination showed residue in contact with ligand. THR 500 SER 545 LARES A313 LARES 361 & SER 483 formed back and side chain H-bond contacts with ligand. In particular, THR 500 residue is covalently attached to ligand at side chain contacts. One end of THR 500 is attached to ligand oxygen group and the other end is attached to functional group of ligand. The remainder of THR500 is covalented to ligand functional groups. Ligand molecule residue contacts and hydrogen bond distance values and types of contacts are presented in Fig. 9.Liza K Patel (2023) reported that were further used for molecular docking with ferulic acid to investigate ligand-protein interactions. All three docked structures demonstrated low binding energy suggesting that ferulic acid could interact with these target molecules. Of the three target molecules, ALOX15 demonstrated the least binding energy indicating significant interaction with ferulic acid, indicating that these bioactive molecules may have a wide range of pharmacological effects. Network pharmacology based on molecular docking and gene enrichment analysis can lead to the development of ferulic acid as an effective drug in the treatment of a wide range of conditions, such as cancer, neurological disorders and psychiatric disorders, as well as Alzheimer’s disease, Pulmonary Emphysema and Arteriosclerosis²³.

3.1.8 Luteolin

Luteolin has a better docking score of -8,638 with good protein ligand interactions TYR 422, THR 500 formed back and side chain H-Bond Interactions with ligand, SER 545 side chain interactions with target. Interestingly, SER 483, THR 498 have residue covalently associated with ligand at side chain interactionsFigure 10 & Table 3. According to previous researcher Sahu (2020), Phytochemical screening revealed the presence of one of the flavonoids compounds luteolin has best docking score − 8,5 Kg/mol compared to other ligand molecule antimicrobial potential against resistant uropathogens²⁴.

3.1.9 p-Coumaric acid

The p-Coumaric acid molecular docking analysis reveals that the phytocompounds interacted interact with the PPB2 target involved multiple amino residues, including SER 483 THR498, SER310 THR500, SER 362 and TYR 544, as indicated by the improved docking score of -8.583Figure 11 & Table 3.. Numerous forces, including carbon-hydrogen bonds, π-interactions, and conventional hydrogen bonding, were used by the compounds to engage with the amino residues. The p-Coumaric acid molecule had strong binding affinities for AChE, BuChE, and MAO targets in molecular docking studies of AChE carried out by Ojo et al. (2021) ²⁵.

3.1.10 2-acetylfuro-1,4-naphthoquinone

In the molecular docking study 2-acetylfuro-1,4-naphthoquinone had a good docking score − 8.498 and also interact with the PPB2 target. 2-acetylfuro-1,4-naphthoquinone were involved the following amino acids residues like THR 500, SER 310 and THR 498 these amino acids were interact with PPB2 target. Among these amino acids THR 500 interacts with two hydrogen bonds. THR 498 and SER 362 are formed contact with side chains. It had a second superior docking score to that of the other bioactive molecules, which is shown in Fig. 12 Table 3. According to Kuete et al., 2011 reported that 2-acetylfuro-1,4-naphthoquinone, and clearly justify the fact that all compounds with any pharmacological activity should also be evaluated for its cytotoxicity. The most sensitive cancer cell lines to xanthone V1 and 2-acetylfuro-1,4-naphthoquinone were Colo-38 (melanoma), HeLa and Caski (cervix cancer) with IC₅₀ values being closer or lower those obtained with doxorubicin²⁶.

3.1.11 Kojic acid

The results of the computational technique used to estimate the amino acid residues of PPB2 using Kojic acid are shown in Fig. 13 and Table 3. The molecular docking experiments showed that the compounds interacted with several amino acids, including TYR 544, SER 545, THR 500, SER 310, and THR 498. The compounds interacted with the amino acids using a variety of forces, including standard hydrogen bonding, carbon-hydrogen bonds, and π-interactions (such as π-alkyl bonds, π-sulfur, amide-π stacking, alkyl, π-π stacking, and π-π-T-shaped stacking). Previous studies Saber et al., 2021, reported that tyrosinase is an enzyme required for the synthesis of melanin and neuromelanin. One substance that inhibits tyrosinase and is used in cosmetics to lighten skin is kojic acid²⁷.

3.1.12 Lapachol

The studies on molecular docking the phytocompounds interacted with multiple amino acids, including TYR 544, SER 545, and THR 500, as demonstrated by lapacol's interaction with the PPB2 target. Various forces, such as conventional hydrogen bonding, carbon-hydrogen bonds, and π-interactions (such π-alkyl bonds, π-sulfur, amide-π stacking, alkyl, π-π stacking, and π-π-T-shaped stacking) were used by this molecule to interact with the amino acid residues Fig. 14 Table & 3. Lapachol molecular docking with COX-1 and COX-2. Similarly, Rauf et al., 2023 stated that lapachol-COX-1 and COX-2 enzyme binding interactions were investigated by molecular docking experiments. The findings showed that lapachol engages in distinct binding interactions with the active areas of COX-1 and COX-2²⁸.

3.1.13 Norvibutrinol

Molecular docking is an in-silico modeling technique used to study the interaction between protein targets and compounds. The molecular docking analysis provided valuable insights into the binding modes and affinities of the bio-active compounds towards PPB2. The docking results of bioactive molecule Norvibutrinol had strong affinity to the target protein PPB2 indicating to interact with the active sites of the protein and modulate its enzymatic activity. The amino acid residues interactions SER 483, THR 498, SER545, TYR 544 and THR 500 were observed included hydrogen bonding, hydrophobic contacts, and π-π stacking interactions, which are critical for stabilizing the ligand-protein complex Fig. 15 & Table 3.

Synthetic drugs

3.1.13 Ceftriaxone

The Centres for Disease Control and Prevention advise treating simple cases of N. gonorrhoea with Ceftriaxone due to the emergence of drug-resistant strains of the gonorrhoea-causing bacteria. In this docking study the interaction between PPB2 targets and commercially available drug Ceftriaxone had a lower docking score (-7.292) and amino acid residues like SER 362, LYS 361, SER 545 and THR 500 involved. And among the 13 bioactive molecules were identified from K. africana extract had a better glide docking XP score and glide energy when compare than conventional drug Fig. 16 & Table 3.

The 13 most important phytochemicals from K. africana were selected for the molecular docking study with the PBP2 target protein of N. gonorrhoeae. Among all the selected phytocompounds they should the best activity compared to the standard drugs. Drug likeness major phytocompounds of K. africana is nontoxic in nature and follows the drug likeness rule. Furthermore, interestingly in this study, we found that the docked complexes the hydrogen bond commonly observed between target and the ligand amino acid residues is THR500, THR498, SER545, TYR422, SER483, SER310. Additionally, LYS313, THR347, LYS361, GLN3445 ASN364 also involved in the formation of hydrogen bond with the ligand clearly shows that the compounds are highly selective towards the target. The hydrophobic bond was commonly formed with the amino acid residue TYR544 and TYR422 depicts that the compounds are having high binding affinity towards the target. Additionally, 6-hydroxyluteolin Glide XP docking score is -10.225, Glide XP energy (Kcal/Mol) -35.841, Glide XP -51.155 and MM-GBSA bind score − 78.215 (Kcal/Mol) is a potential plant-based drug for treating N. gonorrhoeae infection. Furthermore, this study needs to be validated by in vitro and in vivo analysis.

Author Contribution

P.M: Writing – Original draft, Conceptualization. S. V Software, Methodology, Conceptualization. P.D: Validation, Methodology. M.J: Conceptualization, Supervision

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GC–MS analysis of phytoconstituents from Kigelia africana (Lam.) Benth., and molecular docking interactions of bioactive molecules with target Penicillin-Binding Protein 2 (PBP2)

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Abstract

Figures

1. Introduction

2. Materials and methods

2.1. Collection of Plant

2.1.1 Preparation of K. africana bark extract

2.1.2 Preliminary phytochemical analysis

2.1.3 GCMS-analysis Bark extract of K.africana

2.2 In silico analysis

2.2.1 Biological Dataset

2.2.2 Protein optimization

2.2.3 Ligand optimization

2.2.4 Molecular docking

2.2.5 MM-GBSA

2.2.6 ADMET analysis

3. Results and Discussion

3.1. Phytoconstituents of methanol extract of K. africana bark

3.1.1 GC-MS analysis of methanol extract of K. africana bark

3.1. In silico analysis and validation

3.1.1 6-Methoxymellein

3.1.2Kigelinone

3.1.3 6-hydroxyluteolin

3.1.4Atranorin

3.1.5Balaphonin

3.1.6Caffeic acid

3.1.7 Ferulic acid

3.1.8 Luteolin

3.1.9 p-Coumaric acid

3.1.10 2-acetylfuro-1,4-naphthoquinone

3.1.11 Kojic acid

3.1.12 Lapachol

3.1.13 Norvibutrinol

3.1.13 Ceftriaxone

Conclusion

Declarations

Author Contribution

References

Additional Declarations

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