Identification of Potential Antiulcer Agents in Centella Asiatica through Molecular Docking and Virtual Screening

INTRODUCTION:

The drug discovery process uses CADD, a contemporary computer approach, to locate and develop a viable lead. Computational chemistry, molecular modelling, rational drug design, and molecular design are all included in computer-aided drug design. The techniques of CADD are being utilized to optimize identified leads, and both academic communities and the pharmaceutical industry are becoming more and more receptive to its application.

The ethnic medicinal herb Centella Asiatica (Linn) is employed by numerous ancient societies and tribal groups throughout the world. It is one of the regional herbs that is said to have a variety of physiological benefits and plays a significant role in the traditional medical system as a tonic for leprosy and skin illnesses.¹ Centella Asiatica chemical components, which include pentacyclic triterpenoids and trisaccharide analogs, have a variety of bioactivities, including antimicrobial activity², anticancer activity³, wound healing activity⁴, neuroprotective activity⁵, immunomodulatory activity⁶, anti-inflammatory activity⁷, hepatoprotective activity⁸, insecticidal activity⁹, and antioxidant activity¹⁰. Omeprazole was employed in this trial as the standard anti-ulcer medication. It is a proton pump inhibitor that has been successfully treating diseases associated with stomach acid secretion for around 15 years¹¹. The purpose of the current investigation was to assess anti-ulcerogenic properties.

Centella Asiatica

Centella Asiatica, a plant belonging to the Apiaceae family, is also referred to as gotu kola, kodavan, Indian pennywort, and Asiatic pennywort. The globe over, it is a little perennial creeping plant that thrives in damp tropical and subtropical climates.  The plants have long petioles that are grouped at the stem nodes and bear scalloped-edged shovel- or spade-shaped leaves. The inconsequential green or pinkish-white blooms are borne in numerous umbels, and the 3-5 mm long pumpkin-shaped seeds are nutlets. Centella Asiatica has been reported to contain both isoprenoids (sesquiterpenes, plant sterols, pentacyclic triterpenoids, and saponins) and phenylpropanoid derivatives (eugenol derivatives, caffeoylquinic acids, and flavonoids).

The herb or its byproducts are being used in viable, topical, and oral medications throughout the world. Internal preparations of the herb were used to treat simple dysentery, stomach ulcers, and syphilitic lesions while topically applied formulations were used to treat infectious skin illnesses, speed up the healing of skin ulcers, and treat injuries^12-21.

Fig.1. Centella Asiatica Plant

Targeted Protein:

A potential target for the components of centella asiatica in their fight against stomach ulcers is the protein 2XZB. Recently, there has been a lot of interest in inhibiting H+/K+ ATPase as a way to regulate gastric pH due to the discovery that it is the main gastric proton pump²². Based on molecular docking analysis and physiochemical parameters, a group of 46 Centella Asiatica analogues that exhibit inhibitory activity against H+, K+-ATPase were examined. It was discovered that in addition to binding affinity, H-bond donor and acceptor fields were crucial for the H+, K+-ATPase inhibition activity of these compounds. In the current research, we conducted an in-silico analysis on a brand-new group of chemicals, specifically a group of Centella Asiatica compounds that serve as PPI inhibitors. Nobody has conducted a docking investigation on these chemicals up to this point. The primary goal of this study is to present the physicochemical characteristics that control the activity of these chemicals. We have reported some new compounds from the series that might have better activity using the Swiss dock model. These novel compounds have undergone docking research, and the outcomes have been contrasted with those of licensed compounds. These compounds’ ADME/T characteristics have also been investigated and verified using Lipinski criteria.

Since H+/K+ ATPase is the main proton pump in the stomach, inhibiting it to regulate stomach pH has garnered a lot of attention. This is especially true since the Centella Asiatica class of anti-ulcer drugs was discovered recently. One of the earliest known inhibitors of the stomach proton pump was omeprazole, which was more effective than picoprazole.

MATERIAL AND METHODS:

Molecular docking studies

PyRx software 0.8, which is free and open-source software that includes AutoDock4 and AutoDock Vina, was used to calculate docking interactions. Understanding how various ligands interact with the receptor’s active site was the aim of the research. The entire molecular docking process was carried out as shown below.

Molecular docking protocol

PyRx 0.8 software was used to determine the manner of binding and interaction of the chosen target proteins with specific ligands. A probable shape and orientation for the ligand at the active site were obtained using docking. A PDBQT file containing the structure of proteins with Hydrogens in all polar residues was created when the protein was fed into the PyRx software program. By creating a grid box with dimensions, the docking site on the protein-ligand was identified. The lowest binding scores led to the best confirmation being selected. Pymol software was used to build the complex of ligand-protein interaction.

Selection of Data Set and Preparation of Ligand

The 45 compounds listed in table 1 were chosen from a series of novel structures of Asiaticoside B, Madecassic acid, Brahminoside B, Castillicetin, Centillosaponin B, Centillosaponin C, Asiaticoside E, Asiaticoside F, Asiaticoside G, and Centelloside E (SDF File), which were taken from the US National Library of Medicine PubChem official site (https://pubchem.ncbi.nlm.nih.gov/#query=centella%20asiatica). The Universal Force Field (UFF) carried out energy minimization. The chemical makeup of Centella asiatica analogs and the structures of model drugs are revealed in fig. 2.

Fig:2. Selected chemical compounds of Centella asiatica analogs.

Preparation of Protein Molecule

The newly discovered protein gastric H+/K+ATP6ase structure file was got from the RCSB Protein Data Bank and stored in the PDB format (PDB ID: 2XZB) (https://www.rcsb.org/structure/2XZB). As soon as the PDB file for protein gastric H+/K+ATP6ase is loaded in the discovery studio client, the crystal structure of the ligand-binding domain of the 2XZB protein is displayed in a 3D window with a bound ligand and crystallographic fluids. The water molecules in question are not visible in the Hierarchy view. The protein structure has been cleansed and is now exposed to polar hydrogen atoms. In order to save the file in the PDB structure, the related ligand has been removed, and the ligand’s binding site can be predicted from the current pose.

Fig.3. Gastric H⁺/K⁺ATPase (PDB ID: 2XZB)

The protein preparation process included a few phases.

• Orders for bond assignments
• Atoms of polar hydrogen are added.
• Removal of metal bond.
• At pH 7.0, hydrogen bonding was optimized.
• Reorienting the water, -OH group, and amino acids resolved overlapping problems in the hydrogen bond network.
• By deciding the “Review and modify” tab, only the necessary portion of the protein under research was maintained, and the remainder was removed.
• The co-crystallized ligand’s potential protonation states were then generated by selecting the generate states option. To address any issues, the ligand’s structure was examined.
• Finally, the structure was refined with the aid of constrained minimization²³.

Generation of Receptor Grid

The active site receptor grid was located using glide docking, a method that used a ligand linked to the X-ray crystal structure of a protein. Grid-based molecular docking has been employed to assist the ligands in binding in a few possible conformations. Glide molecular docking has also employed the scaling aspect of 0.25, the partial charge cutoff of 1 for the Van Der Waals radius, and other parameters2⁴.

GLIDE MOLECULAR DOCKING STUDY

Following the preparation of the ligands, protein, and grid on the biological target’s catalytic site, molecular docking was carried out. Glide molecular docking makes use of a method of computational modeling to evaluate binding postures. An empirical scoring formula called the G-score is the result of the more current glide systematic approach, which produces rapid, distinctive molecular docking. The ligand-protein interaction energies that make up the calculated binding energy are represented in Kcal/mol. It also calculated the outcome’s root mean square deviation (RMSD), internal energy, H-bond, stacking interactions, and desolvation energy. The XP visualizer was employed to carefully examine the ligand-protein interaction. Most of the chosen ligands, including the reference molecules, were docked with the X-ray crystal structure using glide^25-27.

RESULTS:

The docking simulation techniques was carried out with Centella asiatica constituents on H^+/K⁺ATPase as the protein target by using PyRx software. The comparison of the fitness function score and ligand binding location were the two parameters that were utilized to determine which protein was best docked. The pharmacological activity that the docking score predicts indicates the range of binding energy that is needed to attach a ligand to the receptor. Additionally, it helps to improve the interaction between ligand receptors.

Evaluation of In-Silico Study

Once the docking score was established, the outcomes of the docking study were evaluated using the conformation of the ligand-protein interaction. The compounds that bound to the target receptor protein most effectively had the best interaction profiles and highest dock scores.

The best binding affinity Kcal/mol were predicted for Centella Asiatica constituents are Asiaticoside B (-17 Kcal/mol), Madecassic acid (-14.6 Kcal/mol), Brahminoside B (-10.4 Kcal/mol), Castillicetin (-10.3 Kcal/mol), Centellosaponin B (-10.3 Kcal/mol), Centellosaponin C (-10.0 Kcal/mol), Asiaticoside E (-9.9 Kcal/mol), Asiaticoside F (-9.9 Kcal/mol), Asiaticoside G (-9.9 Kcal/mol), Centelloside E (-9.9 Kcal/mol) and Omeprazole (-7.3 Kcal/mol).

We check the anti-ulcer effect of selected compounds; we have selected protein gastric H+/K+ATP6ase (PDB ID: 2XZB) from the protein data bank (rcsb.org) and subjected to molecular docking studies. Omeprazole was taken as a standard tested drug. From these in silico studies, we have found that compound Asiaticoside B showed highest binding score (-17.00 kcal/mol) by there are no π-π interactions with amino acid and hydrogen bond interaction with ILE A:814, TRY A:925, TRY A:928 and ASN A:128, followed by compound madecassic acid (-14.60 kcal/mol) by π-π interaction with Asp A:851 and ARG A:840, TRY A:1032 & hydrogen bond interactions ARG A:844, ASP A:851, ARG A:949, ASP A:1028, GLU A:1030, PRO A:857 and PRO A:845 with reference to omeprazole -7.20 kcal/mol (by interacting Asp 851 and ARG A:846, TRY A:1033, LYS A:762, PRO A:845, GLU A:374 and ARG A:775). The docking score of compounds is shown in Table 1 and 2D and 3D interactions of compounds 1, 2, and Omeprazole are shown in Fig. (4)

Table1. Chemical Constituents of Centella Asiatica analogs and their docking score.

Sl.No	Compound	Compound Pubchem Id	Docking Score	Rmsd/ ub	Rmsd/ lb
1	Asiaticoside B	91618002	-17	0	0
2	Madecassic acid	51531966	-14.6	0	0
3	Brahminoside	101504860	-10.4	0	0
4	Castillicetin	102394640	-10.3	0	0
5	Centellasaponin B	101140416	-10.3	0	0
6	Centellasaponin C	101103167	-10.0	0	0
7	Asiaticoside E	102212085	-9.9	0	0
8	Asiaticoside F	53317001	-9.9	0	0
9	Asiaticoside G	53320941	-9.9	0	0
10	Centelloside E	101568838	-9.9	0	0
11	Scheffuroside F	101675278	-9.9	0	0
12	Rutin	5280805	-9.9	0	0
13	Asiaticoside	108062	-9.8	0	0
14	Naringin	442428	-9.8	0	0
15	Asiaticoside D	102212084	-9.7	0	0
16	Centellasaponin D	101103168	-9.6	0	0
17	Centelloside D	56964357	-9.6	0	0
18	Madecassoside	45356919	-9.4	0	0
19	1,5-dicaffeoylquinic acid	122685	-9.3	0	0
20	Centellasaponin A	21633803	-9.3	0	0
21	Campesterol	173183	-9.2	0	0
22	Corosolic acid	6918774	-9.1	0	0
23	Ursolic acid	64945	-8.9	0	0
24	Asiaticoside C	101103169	-8.9	0	0
25	Catechin	9064	-8.8	0	0
26	Brahmic acid	73412	-8.8	0	0
27	3-epimaslinic acid	25564831	-8.8	0	0
28	Asiatic acid	119034	-8.7	0	0
29	Arjunolic acid	73641	-8.7	0	0
30	Cryptochlorogenic acid	9798666	-8.7	0	0
31	Centellasapogenol	15508087	-8.5	0	0
32	3,4-Dicaffeoylquinic acid	5281780	-8.5	0	0
33	Terminolic acid	12314613	-8.4	0	0
34	1,3-Dicaffeoylquinic acid	6474640	-8.4	0	0
35	Sitosterol	222284	-8.3	0	0
36	Bicyclogermacrene	5315347	-8.2	0	0
37	Castilliferol	10526707	-8.2	0	0
38	Patuletin	5281678	-8.2	0	0
39	Quetcetin	5280343	-7.9	0	0
40	Epicatechin	72276	-7.7	0	0
41	Germacrene B	5281519	-7.7	0	0
42	Chlorogenic acid	1794427	-7.6	0	0
43	Stigmasterol	5280794	-7.6	0	0
44	Pomolic acid	382831	-7.6	0	0
45	α -Humulene	5281520	-7.4	0	0
46	Omeprazole	4594	-7.2	0	0

MOLECULAR DOCKING ANALYSIS

A computational ligand-protein docking method was used to analyze the structural complex of the 2XZB (PROTEIN) with Centella Asiatica constituents like Asiaticoside B, Madecassic acid, Brahminoside B, Castillicetin, Centellosaponin B, Centellosaponin C, Asiaticoside E, Asiaticoside F, Asiaticoside G, Centelloside E (LIGANDS). The docking process was finally completed by PyRx using the Auto-dock vina option based on the scoring algorithm. A “grid point” value is assigned to the interaction energy of the elements of Centella Asiatica with 2XZB. At each stage of the simulation, the ligand and protein’s interaction energy was calculated using atomic affinity potentials generated on a grid, while the other parameters were left at their default values.

Fig. 4. 2D and 3D binding interaction of Centella Asiatica analogs with 2XZB protein

ADME Prediction:

Physiochemical, Pharmacokinetics, and drug-likeness calculation of several physiochemical features and pharmacokinetics signifiers were predicted through the online web tool SWISS DOCK.

Table 2: Physiochemical and Pharmacokinetics Properties of Compound Asiaticoside B

Formula	C48H78O20
Molecular weight	975.12g/mol
Num. heavy atoms	68
Num. aromatic. heavy atoms	0
Fraction Csp3	0.94
Num. H-bond acceptors	20
Num. H-bond donors	13
Molar Refractivity	235.72
TPSA	335.44 Ų
Num. rotatable bonds	10
GI absorption	Low
BBB permeant	No
P-gp substrate	Yes
CYP1A2 inhibitor	No
CYP2C19 inhibitor	No
CYP2C9 inhibitor	No
CYP2D6 inhibitor	No
CYP3A4 inhibitor	No
Log Kp (skin permeation)	-13.03cm/s

Table 3: ADME Properties of anti-ulcer agents and Drug likeness analysis of designed Centella Asiatica Constituents (1a-2t)

Comp Code			Physicochemical Properties					Lipinski’s Rule	%Absd	N viole	N rotf
		Ligand	MWa	TPSAb	logPc	HA	HD
1a	Asiaticoside B		975.12	335.44	1.91	13	20	No	89.42	10	3
1b	Madecassic acid		504.70	118.22	3.20	5	6	Yes	89.42	2	1
1c	Brahminoside		756.66	295.73	3.02	10	18	No	89.42	11	3
1d	Castillicetin		464.38	177.89	1.83	6	10	Yes	89.42	5	1
1e	Centellasaponin B		828.98	276.52	3.66	11	16	No	86.23	8	3
1f	Centellasaponin C		959.12	315.21	2.60	12	19	No	86.23	9	3
1g	Asiaticoside E		812.98	256.29	2.70	10	15	No	86.23	8	3
1h	Asiaticoside F		943.12	294.98	2.09	11	18	No	89.42	10	3
1i	Asiaticoside G		975.12	335.44	3.99	13	20	No	89.42	11	3
1j	Centelloside E		975.11	315.21	3.60	12	19	No	89.42	10	3
1k	Scheffuroside F		959.12	315.21	3.05	12	19	No	73.61	10	3
1l	Rutin		610.52	269.43	1.58	10	16	No	73.61	6	3
1m	Asiaticoside		959.12	315.21	3.05	12	19	No	73.61	10	3
1n	Naringin		580.53	225.06	2.38	8	14	No	82.44	6	3
1o	Asiaticoside D		943.12	294.98	2.96	11	18	No	82.44	9	3
1p	Centellasaponin D		959.12	315.21	3.73	19	12	No	0.25	3	10
1q	Centelloside D		829.98	276.52	2.60	16	11	No	13.60	3	8
1r	Madecassoside		975.12	335.44	1.87	20	13	No	-6.72	3	10
1s	1,5dicaffeoylquinic acid		516.45	211.28	1.11	12	7	No	36.10	3	9
1t	Centellasaponin A		959.12	315.21	4.01	19	12	No	0.25	3	10
1u	Campesterol		400.68	20.23	4.92	1	1	Yes	102.02	1	5
1v	Corosolic acid		472.70	77.76	3.39	4	3	Yes	82.17	1	1
1w	Ursolic acid		456.70	57.53	3.71	3	2	Yes	89.15	1	1
1x	Asiaticoside C		1001.1	321.28	4.06	20	11	No	-1.84	3	12
1y	Catechin		290.27	110.38	1.47	6	5	Yes	70.91	0	1
1z	Brahmic acid		504.70	118.22	3.20	5	6	Yes	68.21	2	1
2a	3-epimaslinic acid		472.70	77.76	3.55	3	4	Yes	82.17	1	1
2b	Asiatic acid		488.70	97.99	3.20	4	5	Yes	75.19	2	0
2c	Arjunolic acid		488.70	97.99	3.23	4	5	Yes	75.19	2	0
2d	Cryptochlorogenic acid		354.31	164.75	1.01	6	9	Yes	52.16	5	1
2e	Centellasapogenol		488.70	97.99	1.86	4	5	Yes	75.19	2	0
2f	3,4-Dicaffeoylquinic acid		516.45	211.28	1.25	7	12	No	36.10	9	3
2g	Terminolic acid		504.70	118.22	2.25	5	6	Yes	68.21	2	1
2h	1,3-Dicaffeoylquinic acid		516.45	211.28	1.11	7	12	No	36.10	9	3
2i	Sitosterol		414.71	20.23	4.79	1	1	Yes	102.02	6	1
2j	Bicyclogermacrene		204.35	0.00	3.34	0	0	Yes	109	0	1
2k	Castilliferol		432.38	137.43	2.67	4	8	Yes	61.58	5	0
2l	Patuletin		332.6	140.59	2.02	5	8	Yes	60.49	2	0
2m	Quetcetin		302.24	131.36	1.63	5	7	Yes	63.68	1	0
2n	Epicatechin		290.27	110.38	1.47	5	6	Yes	70.91	1	0
2o	Germacrene B		204.35	0.00	3.27	0	0	Yes	109	0	1
2p	Chlorogenic acid		354.31	164.75	0.96	6	9	Yes	52.16	5	1
2q	Stigmasterol		412.69	20.23	5.01	1	1	Yes	102.02	5	1
2r	Pomolic acid		472.70	77.76	3.60	3	4	Yes	82.17	1	1
2s	α -Humulene		204.35	0.00	3.27	0	0	Yes	109	0	1
2t	Omeprazole		345.42	96.31	1.64	5	1	Yes	75.88	0	5

^aMW: molecular weight, ^bTPSA: total polar surface area, ^cmiLogP: molinspiration partition coefficient, ^d%Abs: %Abs = 109 − (0.345 × TPSA), ^enviol: number of violations, ^fnrotb: number of rotatable bonds, H_A: number of hydrogen bond acceptors, H_D: number of hydrogen bond donors.

Table 4: List of amino acid binding with H⁺/K⁺ATPase

SL.NO	LIGAND	INTERACTING AMINO ACIDS	Number of amino acids
	Asiaticoside B	Asparagine, Aspartic acid, Tyrosine, Isoleucine, Glycine, Cysteine	6
	Madecassicacid	Tyrosine, Arginine	2
	Brahminoside B	Tryptophan, Tyrosine, Leucine, Threonine, Alanine, Cysteine, Asparagine,	7
	Castillicetin	Leucine, Cysteine	2
	Centellosaponin B	Glutamic acid, Cysteine, Valine, Asparagine, Aspartic acid,Glutamine, Isoleucine, Leucine	8
	Centellosaponin C	Tyrosine, Arginine, Lysine, Proline, Phenyl alanine, Glutamic acid	7
	Asiaticoside E	Tyrosine, Alanine, Aspartic acid, Asparagine,	4
	Asiaticoside F	Aspartic acid, Arginine, Lysine, Tyrosine, Glutamic acid	5
	Asiaticoside G	Tryptophan, Aspartic acid, Asparagine	3
	Centelloside E	Glutamine	1
	Omeprazole	Asparagine, Aspartic acid, Phenyl alanine, Proline, Glutamic acid, Leucine, Tyrosine	7

Table 5:  Toxicity Profile of Anti-ulcer Agents

Ligand	Acute Toxicity	Carcinogenicity (Mouse)	Mutagenicity	Carcinogenicity (Mouse TD50)
Asiaticoside B	Not Probable	0	0	0
Madecassic acid	Not Probable	0	0	0
Brahminoside	Not Probable	0	0	0
Castillicetin	Highly Probable	0.217	0.418	95
Centellasaponin B	Not Probable	0	0.0598	0
Centellasaponin C	Not Probable	0	0.063	0
Asiaticoside E	Not Probable	0	0.0683	0
Asiaticoside F	Not Probable	0	0	0
Asiaticoside G	Not Probable	0	0.0686	0
Omeprazole	Not Probable	0	0.18	0

The chances of the created chemicals successfully interacting with their target organisms are high. With the help of Swiss ADME tools (skin permeation), calculations were done for intestinal absorption (percent absorbed) and permeability of the Log Kp. Every chosen compound interacts with cytochromes as a substrate or as an inhibitor. The compounds are likely liver-toxic, thus more research will be necessary to determine the hepatotoxic dose level. Because all of the suggested compounds display favorable ADME and toxicity characteristics, they can all be considered plausible lead candidates.

DISCUSSION:

An issue with world health is peptic ulcer disease (PUD). With higher recurrence rates, its etiology is complex and multifactorial. To stop the recurrence of stomach ulceration, hyperacidity, and other conditions, novel methods are required. The purpose of the current study is to examine the protective properties of MBO in peptic ulcer disease. This research study’s objective was to investigate the anti-ulcer potential of MBO by molecular docking, physicochemical properties investigation, and confirmation of its pharmacological effects at the molecular level utilizing various molecular techniques.

The bioactivity score offers details on the drug binding cascade that is utilised to create a new functional medicine with a higher binding selectivity profile and fewer side effects. All chosen anti-ulcer medications underwent toxicity profile evaluation and are included in Table 5. Except for Castillicetin, all of the medications were determined to be unlikely to cause toxicity.

Molecular docking, which forecasts the principal binding mechanism of a ligand with a target protein having a known 3D structure, is an essential tool in structure-based computer-assisted drug design. The suggested Centella Asiatica Constituents are effectively docked into the target protein’s active site using PyRx software (PDB ID: 2XZB). With the target protein, the desired substances Asiaticoside B, Madecassic acid, Brahminoside, and Omeprazole form effective hydrogen bonds. Furthermore, as shown in Table 4, the formation of hydrogen bonds between the molecules TYR and ARG is well known. The selected compound forms the most effective binding site on the protein that interacted with the same as binding site on the protein the tested standard drug of omeprazole and the target protein were revealed by docking experiments.

Designing novel pharmacological substances requires an understanding of physicochemical characteristics. These molecule-specific characteristics, such as molecular weight, HBA, HBD, rotatable bonds, TPSA, number of heavy atoms, and molar refractivity, can be used to assess the drug similarity profile. For the substances listed in Table 2 of Asiaticoside B, these parameters were calculated.

Docking scores of selected compounds Asiaticoside B is also better than omeprazole, its Centella Asiatica Constituents predicting that compounds will be more active. In post docking analysis it was observed that compound Asiaticoside B, Madecassic acid, Brahminoside, Castillicetin, Centellasaponin B, and Centellasaponin C are binding to the active site in almost same pose as omeprazole. According to docking score poses of compounds Asiaticoside B, Madecassic acid, Brahminoside, are energetically better than the possess of compounds Castillicetin, Centellasaponin B, Centellasaponin C and Omeprazole as shown in Fig.4  

Absorption, penetration via the skin, distribution, metabolism/biotransformation, and excretion were among the expected pharmacokinetic parameters. It is well established that the intestinal estimated permeation method (BOILED-Egg) may accurately anticipate results for intestinal absorption and passive cerebral infusion. The white part of this predicted model reflects passive stomach absorption, whereas the yellow section shows passive cerebral permeability for molecules, respectively.

The BOILED-EGG curve is displayed in Figure 6. This approach allows for the prediction of the drugs’ GI absorption (HIA) and BBB penetration. Both the GI absorption zone (HIA) and the BBB penetration zone (yolk) are present. Any component identified in the gray zone is not indicative of GI absorption or BBB penetration. Swiss adme also failed to demonstrate that it is a P-gp substrate because, as shown in Figure 6, it is not susceptible to the P-gp efflux mechanism, which is exploited by many cancer cell lines to build drug resistance.

As shown in table 2, Asiaticoside B has minimal GI absorption and no BBB penetration, which is clear from this prediction finding. A medicine that can be administered orally or transdermally can be predicted and identified using the skin permeability model. According to the model, a molecule is said to have less skin permeability if its log Kp value is more negative. Asiaticoside B was determined to have the lowest level of skin permeability.

Since cytochrome P450 enzymes play an important role in drug removal through metabolic transformation, the interaction between molecules and these isoenzymes is crucial. By decreasing the solubility and causing the drug or its byproducts to accumulate, inhibition of these isoenzymes may have unintended undesirable side effects. CYP2C9, CYP2D6, CYP1A2, and CYP3A4 are not inhibited by the substance Asiaticoside B, according to prediction. Asiaticoside B has no inhibitory effect on the isoenzyme CYP2C19 molecule.

CONCLUSION:

The in-silico characteristics of Centella Asiatica constituents were investigated. According to the ADME study, all produced compounds can be regarded as lead molecules. All constituents were investigated using molecular docking and virtual screening. The docking score for compound Asiaticoside B is -17 Kcal/mol. More binding affinity is indicated by a higher negative score, which also indicates the most potent inhibitor.

The parietal cells found in the stomach secrete gastric acid. With the cytoplasmic hydrolysis of ATP, the H+/K+-ATPase pump in parietal cells transfers hydrogen ions in the stomach. Ulcers are brought on by the proton pump’s hyperactivity, which also causes excessive acid secretion. Potential targets include the stomach proton pump, whose blockage reduces acid production and eventually leads to ulcer healing. In practice, proton pump inhibitors (PPIs) are used to treat ulcers, but their use is restricted due to their negative side effects. Swiss ADMET was examined in this study using an in vitro H+/K+-ATPase inhibitory assay, which revealed that it considerably lowers the amount of ATP hydrolysis by the gastric ATPase, indicating proton pump inhibitory action comparable to the common medication omeprazole, an irreversible proton pump inhibitor. Additionally, the molecular docking study’s findings showed that compound 1a showed an energy value of -17.00 Kcal/mol against the H+/K+-ATPase pump, compared to the conventional medicine omeprazole’s energy value of -7.2 Kcal/mol. Accordingly, proton pump inhibition may be the cause of the anti-ulcer activity, as shown by molecular docking and physicochemical analysis.

The ADME examination of these compounds shows that they are suitable for drug-likeness. These substances can be absorbed efficiently through the skin and digestive systems. The outcomes of the testing show that Asiaticoside B compounds have potent inhibitory effects on gastric ulcers.

CONFLICT OF INTERESTS

The authors declare no conflict of interest.

REFERENCES:

1. Saurabh A, Mishra AS, Gupta S. A review on medicinal plants which may be effective in the treatment of ulcer or which show anti-ulcer activities. International Journal of Pharma Professional’s Research (IJPPR). 2021;12(1):1-0.
2. Roy AJ, Maut C, Gogoi HK, Ahmed SI, Kashyap A. A review on herbal drugs used in the treatment of peptic ulcer. Current Drug Discovery Technologies. 2023 May 1;20(3):4-15.
3. Hamid IS, Widjaja NM, Damayanti R. Anticancer activity of Centella asiatica leaves extract in benzo (a) pyrene-induced mice. Int J Pharmacogn Phytochem Res. 2016 Jan;8(1):80-4.
4. Khotimah H, Setiawan A, Rita C I, Ali A. In silico studies of natural compounds of Centella asiatica as anti-aging and wound healing agents. Int Conf Sci Tech 2021;2353(1):030031-9.
5. Gray N E, Magana A A, Lak P, Wright K M, Quinn J, Stevens J F, Maier C S, Soumyanath A.Centella Asiatica-phytochemistry and mechanisms of neuroprotection and cognitive enhancement. Phyochem Rev 2018;17(1):161-94.
6. Al-Mamun A, Ahammad I, Ahmed SS, Akter F, Hossain SI, Chowdhury ZM, Bhattacharjee A, Das KC, Keya CA, Salimullah M. Pharmacoinformatics and molecular dynamics simulation approach to identify anti-diarrheal potentials of Centella asiatica (L.) Urb. against Vibrio cholerae. Journal of Biomolecular Structure and Dynamics. 2023 Mar 14:1-4.
7. Thakral S, Yadav A, Singh V, Kumar M, Kumar P, Narang R, Sudhakar K, Verma A, Khalilullah H, Jaremko M, Emwas AH. Alzheimer’s disease: Molecular aspects and treatment opportunities using herbal drugs. Ageing Research Reviews. 2023 May 22:101960.
8. Awuchi CG, Saha P, Amle VS, Nyarko RO, Kumar R, Boateng EA, Kahwa I, Boateng PO, Asum C. A Study of Various Medicinal Plants used in Ulcer Treatment: A Review. Journal for Research in Applied Sciences and Biotechnology. 2023 Mar 15;2(1):234-46.
9. Noor A, Qazi N G, Nadeem H, Khan A, Paracha R Z, Ali F, Saeed A. Synthesis, characterization, antiulcer action and molecular docking evaluation of novel benzimidazole- Pyrazole hybrids. Chem cent J 2017;11(85)1-13.
10. Silva L M, Allemab A, Mendes D A G B, Santos A C, Andre E, Souza L M, Cipriani R T. Ethanolic extract of roots from Arctinum lappa L accelerates the healing of acetic acid-induced gastric ulcer in rat:involvement of the antioxidant system. Food Chem Toxicol 2013;51:179-87
11. Huang J, Zhou X, Gong Y, Chen J, Yang Y, Liu K. Network pharmacology and molecular docking analysis reveals the mechanism of asiaticoside on COVID-19. Annals of Translational Medicine. 2022 Feb;10(4).
12. Rani K, Tyagi M, Singh A, Shanmugam V, Shanmugam A, Pillai M, Srinivasan A. Identification of annotated metabolites in the extract of Centella asiatica. Journal of Medicinal Plants Research. 2019 Mar 10;13(5):112-28.
13. Sharifi-Rad M, Fokou P V T, Sharopov F, Martorell M, Ademiluyi A O. Anti-ulcer agents:from plant extracts to phytochemicals in healing promotion. mol 2018;23(7):1-37.
14. Awuchi CG, Saha P, Amle VS, Nyarko RO, Kumar R, Boateng EA, Kahwa I, Boateng PO, Asum C. A Study of Various Medicinal Plants used in Ulcer Treatment: A Review. Journal for Research in Applied Sciences and Biotechnology. 2023 Mar 15;2(1):234-46.
15. Sahoo S. Screening of Phytochemicals and In silicoApproach through Drug Design of Centella. Biol Res. 2019;7(1):1114.
16. Al-Mamun A, Ahammad I, Ahmed SS, Akter F, Hossain SI, Chowdhury ZM, Bhattacharjee A, Das KC, Keya CA, Salimullah M. Pharmacoinformatics and molecular dynamics simulation approach to identify anti-diarrheal potentials of Centella asiatica (L.) Urb. against Vibrio cholerae. Journal of Biomolecular Structure and Dynamics. 2023 Mar 14:1-4.
17. Kuna L, Jakab J, Smolic R, Raguz Lucic N, vcer A, smolic M. Peptic ulcer disease: a brief                                      review of conventional therapy and herbal treatment options. J Clin Med 2019;8(2):1-19.
18. Sharma P, Mishra R, Vakil B. Virtual screening and Docking analysis of novel flavonoidanalogues as antipsoriaticagents. Int J Curr Res Rev 2017;10(3):19-27.
19. Kambale EK, Quetin-Leclercq J, Memvanga PB, Beloqui A. An Overview of Herbal-Based Antidiabetic Drug Delivery Systems: Focus on Lipid-and Inorganic-Based Nanoformulations. Pharmaceutics. 2022 Oct 8;14(10):2135.
20. Zheng HM, Choi MJ, Kim JM, Cha KH, Lee KW, Park YH, Hong SS, Lee DH. Centella asiatica leaf extract protects against indomethacin-induced gastric mucosal injury in rats. Journal of medicinal food. 2016 Jan 1;19(1):38-46.
21. Narayanan M, Reddy K M, Marsicano E. Peptic ulcer disease and helicobacter pylori infection. Mol Med 2018;115(3):219-24.
22. Gadekar R, Singour P K, Pawar R S, Patil U K. A potential of some medicinal plants as an antiulcer agent. Pharmacogn Rev 2010;4(8):136-4.
23. Kumar, S.; Singh, J.; Narasimhan, B.; Shah, S.A.A.; Lim, S.M.; Ramasamy, K.; Mani, V. Reverse pharmacophore mapping and molecular docking studies for discovery of GTPase HRas as promising drug target for bis-pyrimidine derivatives. Chem. Cent. J., 2018, 12(1), 106. http://dx.doi.org/10.1186/s13065-018-0475-5 PMID: 30345469
24. Sharma, V.; Sharma, P.C.; Kumar, V. In silico molecular docking analysis of natural pyridoacridines as anticancer agents. Adv. Chem., 2016, 2016, 1-9.
25. Mehta J, Rolta R, Salaria D, Awofisayo O, Fadare OA, Sharma PP, Rathi B, Chopra A, Kaushik N, Choi EH, Kaushik NK. Phytocompounds from Himalayan medicinal plants as potential drugs to treat multidrug-resistant Salmonella Typhimurium: An in-silico approach. Biomedicines. 2021 Oct 5;9(10):1402.
26. Huang J, Zhou X, Gong Y, Chen J, Yang Y, Liu K. Network pharmacology and molecular docking analysis reveals the mechanism of asiaticoside on COVID-19. Annals of Translational Medicine. 2022 Feb;10(4).
27. Mehta J, Rolta R, Salaria D, Awofisayo O, Fadare OA, Sharma PP, Rathi B, Chopra A, Kaushik N, Choi EH, Kaushik NK. Phytocompounds from Himalayan medicinal plants as potential drugs to treat multidrug-resistant Salmonella Typhimurium: An in-silico approach. Biomedicines. 2021 Oct 5;9(10):1402.