Introduction

Emesis, or vomiting, is a typically unpleasant condition where stomach contents are forcefully expelled through the mouth. It is closely associated with the movement of the gastrointestinal system1. Vomiting is induced by toxins in the gut lumen or by irritation of the stomach through the gastrointestinal tract’s (GIT) mucosal chemoreceptors2,3. Besides ingesting toxins or irritants, several conditions, including food poisoning, gastroenteritis (diarrhea), motion sickness, hangovers, head injuries, intestinal obstruction, appendicitis, post-operative factors, and elevated intracranial pressure, can also lead to vomiting and nausea4. In addition, several adverse reactions to radiation therapy and cancer treatment can cause emesis5. There is evidence that emesis and GI disturbances can be induced by microbes and their secretions6,7,8. However, emesis is a very complex process, initiated by sending emetogenic stimuli to the vomiting center (VC) in the medulla oblongata9. Several important parts, such as the chemoreceptor trigger zone (CTZ), which is situated in the region postrema on the floor of the fourth ventricle and activated by certain blood-borne poisons or medications, play a crucial role in inducing emesis10. Vomiting triggered by the CTZ begins when its receptors detect emetogenic toxins in the blood and cerebrospinal fluid (CSF) and relay this information to the neighboring nucleus tractus solitarius (NTS). Abdominal vagal afferents that identify potentially emetogenic substances (e.g., uremic toxins, apomorphine, cardiac glycosides, and chemotherapeutic agents) in the lumen also terminate here11. The other sites besides the CTZ that relay information to the VC to induce emesis include the GI tract (stimulated by toxins and food consumption), the vestibular system, and the higher centers in the cortex and thalamus12. Electrical stimulation of all of these structures can induce emesis13. A vomiting stomach releases bicarbonate into the body and HCl into the gastric lumen. During vomiting, the body expels HCl while accumulating bicarbonate14. At the onset of vomiting, the lower esophageal sphincter relaxes, the stomach contracts intrinsically, and the vomit passes from the stomach into the esophagus. The abdominal and inspiratory muscles then contract, forcing the vomit to be expelled into the mouth15. The VC carries histamine (H1), neurokinin type 1 (NK1), serotonin 2 (5HT2), and muscarinic receptors, while dopamine (D2), μ (mu)-opioid, and serotonin 3 (5HT3) receptors are prevalent in the CTZ. In addition, after activating the receptor, 5HT3 has a peripheral action in the GIT, along with 5HT4 and D216. In this regard, serotonin (5HT) receptors have been linked with vagal afferent and peripheral neural pathways17. They are stimulated by different stimuli and are responsible for the emetic process18,19. Several types of adrenergic (α2), CB1, and GABAB receptors are also liable for inducing emesis20,21.

At present, various antiemetic drugs are used to treat nausea and vomiting. These can be classified as 5HT antagonists, anti-dopaminergic drugs, antihistamines, anticholinergic drugs, NK1-receptor inhibitors, corticosteroids, and cannabinoids22. Prolonged use of these medications is associated with unfavorable consequences, such as spasms, convulsions, or muscle weakness23,24. Therefore, the search for new and safe medications is the demand of time. Natural products have thus become indispensable in the current treatment approach because of their minimal adverse reactions and practical benefits25. The exploration of novel antiemetic drugs that are obtained from natural sources continues to focus on mechanism-based methods that involve specific molecular and cellular targets. Alkaloids, flavonoids, glucosides, cannabinoids, hydroxycinnamic acids, polysaccharides, diarylheptanoids, phenylpropanoids, terpenes, and saponins are used for finding potential new antiemetic medication drugs26.

Abietic acid (1R, 4aR, 4bR, 10aR)-1,4a-dimethyl-7-(propan-2-yl)-1,2,3,4,4a,4b,5,6,10,10a-octahydrophenanthrene-1-carboxylic acid) is a diterpenoid acid that is found in the resin of some coniferous plants, including pine and spruce. Abietic acid (AA) has different therapeutic activities, including antiviral, antibiotic, antifungal, anticancer, neuroprotective (Alzheimer’s disease), and antioxidant activities27. Moreover, AA prevents stomach secretions, indicating that it might be used as an antiulcer medication28, and has a cytotoxic effect29. In a study conducted by Fernández and coworkers, it was shown that AA possesses potent in vivo anti-inflammatory activity via topical and oral treatment30. There are several in vivo and in vitro models available for assessing the antiemetic activities of a compound or plant extract, one such model is the chick emesis31. In this study, oral administration of copper sulfate (CuSO4⋅5H2O) causes emesis in young chickens (Gallus gallus domesticus). The standard test sample is administered orally 30 min before CuSO4⋅5H2O. Evaluation of the antiemetic activity of the test sample is achieved by contrasting the number of retches with control groups32. On the other hand, the drug research and development process can be sped up and kept less expensive by using the computational drug discovery method. The diversity of data on biological macromolecules has significantly increased, and as a result, computational drug discovery is currently applied to nearly all stages of the process of finding and developing drugs. Additionally, it enables the prediction of pharmacokinetics and binding sites, both of which are vital in determining the mechanistic stages and binding when identifying and developing prospective drug candidates33,34,35. Accordingly, this study aimed to examine the antiemetic effects of AA on copper sulfate-induced emesis in young chickens. Simultaneously, a computational analysis was performed to investigate molecular interactions that may be liable for the observed effect, as well as to assess the pharmacokinetic and toxicological properties of AA.

Materials and methods

Chemical reagents and standards

AA (CAS No. 514-10-3) was purchased from Sigma-Aldrich (USA), while copper sulfate pentahydrate (CuSO4⋅5H2O) was obtained from Merck (India). Reference drugs, ondansetron (OND), domperidone (DOM), hyoscine butyl bromide (HYS), aprepitant (APT), and diphenhydramine (DHM) were purchased from Incepta, Beximco, Opsonin, Beacon, and Eskayef Pharma Ltd., Bangladesh, respectively.

Selection and preparation of test and control groups

Based on a review of the literature, we selected two concentrations of the test sample (lower and higher). We prepared the sample’s mother solution at a concentration of 50 mg/kg by dissolving it in distilled water (DW) and a small amount of Tween 80 (0.5%) used as a co-solvent. The mother solution was then diluted at concentrations of 20 and 40 mg/kg. In contrast, doses of the referral drugs were chosen by converting human doses to animal doses supported by animal dose calculation protocol and literature procedures8,36. The reference drug’s solutions were also prepared by thoroughly mixing them into DW (where a small amount of Tween 80 was used as a co-solvent) at concentrations of 16, 6, 10, 21, and 5 mg/kg for the drugs APT, DOM, DHM, HYS and OND, respectively. Three combined doses of AA (40 mg/kg), DOM, HYS, and OND were also prepared for the co-treatments.

Experimental animals

Young chicks (Gallus gallus domesticus) of both genders, with a weight range of 40–45 g, 2 days old, were purchased from Provita Feed and Hatcheries Ltd. at Road-3, House-270, Baridhara DOHS, Dhaka Division, 1206 Bangladesh. All chicks were kept at the pharmacology lab of Bangabandhu Sheikh Mujibur Rahman Science and Technology University, Gopalganj, for the present study. The chicks were given free access to regular food and water. They were maintained at 27 ± 2 °C with a 12-h dark/light cycle under controlled illumination before the test started. After 12 h of fasting, the antiemetic test was carried out. This study was approved by the Department of Pharmacy and the Ethical Committee of Bangabandhu Sheikh Mujibur Rahman Science and Technology University (#bsmrstu-phr-17PHR049-01). In addition, all methods were carried out in accordance with relevant guidelines and regulations, and all methods were reported in accordance with ARRIVE guidelines (https://arriveguidelines.org).

In vivo protocol

The procedures outlined by Akita et al.32 were used to conduct the study with a few minor modifications. The chicks were divided into eleven groups of six each. Before receiving the treatments, each bird was retained in a sizable, clear plastic container for 10 min. Using DW, the test sample (AA) was prepared in two different doses (20 and 40 mg/kg), which were then administered orally. The reference drugs APT, DOM, DHM, HYS, and OND were orally given at doses of 16, 6, 10, 21, and 5 mg/kg b.w. The lower dose (20 mg/kg) of AA did not exhibit any significant synergistic or antagonistic effects in the combination therapy; therefore, the three reference medicines, DOM, HYS, and OND, were combined with AA at a dose of 40 mg/kg. Then, animals were orally given these combined doses to assess their synergistic or antagonistic effects. The other two referral drugs were omitted for combination therapy due to their inadequate antiemetic properties when given alone to the animals. DW with a small amount of tween 80 (0.5%) was used as a control group (vehicle). It was given orally at a dose of 150 mL/kg b.w. Each chick specimen had a 30-min treatment period before having emesis caused by the oral gavage of CuSO4⋅5H2O at a dose of 50 mg/kg of b.w. The latency period is the duration of time between the administration of the CuSO4⋅5H2O treatment and the occurrence of the first retch, then, the total number of retches within 10 min of receiving CuSO4⋅5H2O treatment and the latency were carefully noted. Compared to the vehicle group, we calculated the percentage reduction in retches and prolongation in latency according to the following formula:

$$\text{\% increase in latency}=\frac{{\text{M}}-{\text{N}}}{{\text{M}}}\times 100,$$
$$\text{\% decrease in retches}=\frac{{\text{C}}-{\text{D}}}{{\text{C}}}\times 100,$$

where M: is the mean of latency in seconds in standard and test groups, N: is the mean of latency in seconds in the vehicle group, C: is the mean of retches in the vehicle group, and D: the mean of retches in the standard and test groups.

Statistical analysis

The values of the antiemetic efficacy are expressed as the mean and standard error of the mean (SEM). The Graph Pad Prism (version 6.0) is a statistical computer application that was used to estimate the variations’ statistical significance which was determined at a 95% confidence limit. p values of < 0.05 are considered significant, whereas p values of p < 0.0001 are very significant.

In silico analysis

Homology model and preparation of receptors

Based on published research, we selected nine receptors to perform molecular docking and ligand-receptor visualization. We developed a homology model because the human 5HT3 receptor’s 3D structure wasn’t available in the RCSB Protein Data Bank37. Human 5HT3 receptor homology modeling was achieved using the SWISS-MODEL38. The UniProt database (http://www.uniprot.org) was used to retrieve the protein’s sequence, and the NCBI BLAST program was employed to conduct a BLAST analysis to determine the best template39. The GMQE40 and a Ramachandran plot using ProCheck41 methods were used to evaluate the 5HT3 homology modeling structures. D2 (PDB ID: 6LUQ)42, D3 (PDB ID: 3PBL)43, H1 (PDB ID: 3RZE)44, M1 (PDB ID: 6WJC), M2 (PDB ID: 5ZK8), M3 (PDB ID: 4U15), M4 (PDB ID: 7V6A), M5 (PDB ID: 6OL9)45, and NK1 (PDB ID: 6HLO)46 were obtained from the RCSB Protein Data Bank (https://www.rcsb.org/). After collecting receptors, the PyMol software program (v2.4.1) was used to remove any extraneous molecules, such as lipids, heteroatoms, and water molecules, from the protein sequence to optimize the receptors and prevent docking interference. Finally, using the SwissPDB Viewer software program and the GROMOS96 force field, the receptors’ shape and energy were optimized. The PDB file was then saved for use in molecular docking.

Collection and preparation of ligands

Based on the literature, we chose several well-known and commercially available antiemetic medications as reference ligands to compare the binding energy and molecular interaction with our test ligand (AA), with the focus on different emesis-causing receptors, to understand the root cause of the antiemetic mechanism. Afterward, the following were collected using the PubChem chemical database in SDF format (https://pubchem.ncbi.nlm.nih.gov/): several receptors, molecular docking, and prediction of pharmacokinetic features of the 3D conformers of abietic acid (Compound CID: 10569), aprepitant (Compound CID: 135413536), diphenhydramine (Compound CID: 3100), domperidone (Compound CID: 3151), hyoscine (Compound CID: 3000322), and ondansetron (Compound CID: 4595). Then, using the Chem3D 16.0 computer application, which is used for performing molecular docking and anticipating pharmacokinetics, the 3D conformers of the chemical agents were minimized, stored as SDF files, and transformed into MOL files, respectively. Finally, using the Gaussian View program (v5.0), all the ligands were optimized. Displayed in Fig. 1 are the chemical structures of AA and standard drugs.

Figure 1
figure 1

Chemical structures of abietic acid and reference drugs.

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Molecular docking study

Molecular docking was conducted using the PyRx software tool to predict the active binding energy of the drugs toward the active sites of receptors. For successful docking, the grid box dimensions were set at 85 × 80 × 75 Å along the x-, y-, and z-axes, respectively, and the calculation required 2000 steps47,48. The docking potential result is saved in ‘CSV’ format, and the ligand–protein complex is collected in PDB format to collect the ligand in PDBQT format. The interactions between ligand-receptors and the receptor’s active site were seen using the computer programs PyMol (v2.4.1) and Discovery Studio Visualizer (v21.1.020298). Then, the types of bonds, the number and length of hydrogen bonds, and each ligand-receptor interaction’s amino acid residues are documented.

Prediction of drug-likeness and pharmacokinetics

Drug-likeness is a qualitative assessment used to evaluate a molecule’s potential to be discovered and developed into an orally administered drug. A structural or physicochemical investigation was conducted to show similarities between the compounds and existing medications that were advanced enough in the research phase to be considered potential treatment options49. A chemical agent’s pharmacokinetics and drug-likeness may be calculated using a variety of web servers and applications. In this investigation, with the help of SwissADME, we discussed numerous criteria for evaluating the physicochemical characteristics of the test compound (http://www.swissadme.ch/index.php).

Toxicity prediction

To predict various toxicity parameters of any compound, ProTox-II online servers can be used. The ProTox-II web server is used to assess the safety profile of a chemical or compound by analyzing multiple toxicity endpoints, for instance, hepatotoxicity, carcinogenicity, mutagenicity, acute toxicity, immunogenicity, and cytotoxicity50. To evaluate the toxicity parameters, the Canonical SMILES were entered into the ProTox-II server (http://tox.charite.de/protox_II), which was collected from PubChem. The toxicity parameters of the selected compounds are listed in Table 1.

Table 1 Different treatments and their doses were investigated in animals.
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Results

In vivo investigation

In our experiment, animals in the control (vehicle) group exhibited their first retching at 7.50 ± 0.92 s, whereas animals in the reference groups showed an elevated latency compared to the control group. Animals given DOM showed the highest latency (63.16 ± 3.99 s) among the selected reference drugs in this test. Values of the onset of retching for other reference groups are 8.17 ± 2.05, 9.16 ± 1.98, 11.83 ± 1.37, and 14.83 ± 2.27 s for APT, DHM, HYS, and OND, respectively. On the other hand, animals in the test groups (AA) exhibited a significant dose-dependent elevation in latency compared to the control group. Animals belonging to the AA-40 group exhibited the highest latency (98.00 ± 2.44 s) among all the test groups, while the other test group (AA-20) revealed 29.16 ± 3.77 s. The combination therapies demonstrated that AA notably increased latency when the animals were co-treated with the reference drugs compared to the reference drugs alone. The latency of the DOM + AA-40, OND + AA-40, and HYS + AA-40 groups is 72.83 ± 3.25, 42.33 ± 2.09, and 30.66 ± 3.21 s, respectively. The latency obtained from all treatment groups is illustrated in Fig. 2.

Figure 2
figure 2

Latency observed in test samples, controls, and combinations [Values are the mean ± standard error of the mean (S.E.M.) (n = 6)]. aCompared to the control (vehicle), bcompared to the APT; ccompared to the DOM; dcompared to the DHM; ecompared to the HYS; fcompared to the OND; gcompared to the AA-20; hcompared to the AA-40; icompared to the DOM + AA-40; p < 0.05 (OND vs AA-20, AA-20 vs AA-40 + OND); p < 0.01 (OND Vs AA-40 + HYS); p < 0.001 (HYS vs AA-20, HYS vs AA-40 + HYS); p < 0.0001 (Vehicle vs DOM, vehicle vs AA-20, vehicle vs AA-40, vehicle vs AA-40 + DOM, vehicle vs AA-40 + HYS, vehicle vs AA-40 + OND, APT vs DOM, APT vs AA-20, APT vs AA-40, APT vs AA-40 + DOM, APT vs AA-40 + HYS, APT vs AA-40 + OND, DOM vs DHM, DOM vs HYS, DOM vs OND, DOM vs AA-20, DOM vs AA-40, DOM vs AA-40 + HYS, DOM vs AA-40 + OND, DHM vs AA-20, DHM vs AA-40, DHM vs AA-40 + DOM, DHM vs AA-40 + HYS, DHM vs AA-40 OND, HYS vs AA-40, HYS vs AA-40 + DOM, HYS vs AA-40 OND, OND vs AA-40, OND vs AA-40 + DOM, OND vs AA-40 + OND, AA-20 vs AA-40, AA-20 vs AA-40 + DOM, AA-40 vs AA-40 + DOM, AA-40 vs AA-40 + HYS, AA-40 vs AA-40 + OND, AA-40 + DOM vs AA-40 + HYS, AA-40 + DOM vs AA-40 + OND).

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The highest number of retches (66.83 ± 3.58) was noticed in the vehicle group in this test. A remarkable reduction in the number of retches in animals treated with reference drugs such as APT, DOM, DHM, HYS, and OND was observed as compared to the vehicle, where DOM exhibited the lowest (10.00 ± 1.46) retches among the selected reference drugs, even across all the treatment groups. The values of the number of retching for APT, DHM, HYS, and OND are 58.66 ± 6.03, 51.00 ± 4.87, 46.33 ± 3.70, and 34.00 ± 2.26, respectively. In the case of the test sample, there was a significant dose-dependent decrease in the number of retches, and the animals in the AA-20 and AA-40 groups displayed 20.33 ± 2.04 and 11.66 ± 2.52 retches, respectively. In the combination groups, the lowest number of retches exhibited was in the OND + AA-40 group (15.50 ± 1.76). The total number of retches for all treatment groups is shown in Fig. 3.

Figure 3
figure 3

Number of retches observed in the test sample, controls, and combination [Values are mean ± standard error of the mean (SEM) (n = 6)]. aCompared to the control (vehicle), bcompared to the APT; ccompared to the DOM; dcompared to the DHM; ecompared to the HYS; fcompared to the OND; gcompared to the AA-20; hcompared to the AA-40; p < 0.05 (Vehicle vs DHM, DOM vs AA-40 + HYS, DHM vs OND, OND vs AA-40 + DOM, AA-40 vs AA-40 + HYS); p < 0.01 (vehicle vs HYS, HYS vs AA-40 + HYS, OND vs AA-40 + OND); p < 0.001 (DOM vs OND, DHM vs AA-40 + HYS, OND vs AA-40); p < 0.0001 (vehicle vs DOM, vehicle vs OND, vehicle vs AA-20, vehicle vs AA-40, vehicle vs AA-40 + DOM, vehicle vs AA-40 + HYS, vehicle vs AA-40 + OND, APT vs DOM, APT vs OND, APT vs AA-20, APT vs AA-40, APT vs AA-40 + DOM, APT vs AA-40 + HYS, APT vs AA-40 + OND, DOM vs DHM, DOM vs HYS, DHM vs AA-20, DHM vs AA-40, DHM vs AA-40 + DOM, DHM vs AA-40 + OND, HYS vs AA-20, HYS vs AA-40, HYS vs AA-40 DOM, HYS vs AA-40 + OND).

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Animals belonging to the AA-20 and AA-40 groups showed an increase in percentage of latency compared to the vehicle group, which was 74.27 and 92.34%, respectively. Findings indicated that the latency period is elevated with the increase in doses in the test groups. However, animals treated with combined therapies also showed a significant elevation in the latency percentage; among the several combination treatments, DOM + AA-40 exhibited the highest latency percentage of 89.70%. In the case of a percentage decrease in retches, treatment with the test compound demonstrated a dose-dependent percentage decrease in retching. The highest percentage decrease in retching was observed in the DOM group (85.03%), though the drug’s combination therapy with AA showed a reduction in retching (75.56%). Our findings showed that the percentage decrease in retching for other combination groups are 58.10 and 76.80% for the HYS + AA-40 and OND + AA-40 groups, respectively. The percentage decrease in retching and the rise in the latency period for each treatment group are displayed in Table 2.

Table 2 Percentage increase in latency and reduction of retching in emetic animals of test and/or control groups.
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In silico study

Homology modeling of human 5HT3 protein

Findings from the homology modeling show that the desired sequence and the template sequence of 4PIR (PDB ID), an X-ray crystallographic structure of the mouse 5HT3 receptor, have similar sequences. The target protein sequence shares 95% coverage and 86.95% identity with the template sequence, which also has a 58% sequence similarity. With a QMEAN of − 3.91 and a GMQE score of 0.72, the homology model of human 5HT3 was developed, suggesting high quality and consistency. To verify the accuracy and reliability of the residues’ Psi and Phi angles, the Ramachandran plot was designed. The plot revealed 1.81% Ramachandran outliers and 91.65% Ramachandran preferences in Fig. 4.

Figure 4
figure 4

(i) The Swiss Model-built 3D structure of the human 5HT3 receptor, (ii) Ramachandran plot of the homology model 5HT3 protein for all non-glycine/proline residues.

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Molecular docking

A molecular docking approach was used to predict the possible binding energy between ligand and protein. Our in silico study revealed that the test ligand (AA) shows the highest docking score (− 10.2 kcal/mol) toward the M4 receptor among the selected emesis-inducing receptors, whereas the referral ligand HYS exhibited a reduced docking score for the test ligand against the same receptor. The test ligand also showed a higher docking score than HYS toward the other subtypes (M1, M2, and M5) of mAChRs except M3 (Table 3). AA also demonstrated higher binding affinity toward 5HT3 and H1 receptors, and the docking scores are − 8.1 and − 8.5 kcal/mol, respectively. While the selected referral ligands OND and DHM expressed binding affinity of − 6.9 and − 6.3 kcal/mol with the 5HT3 and H1 receptors, respectively, In the case of the dopamine receptor, the selected antagonist DOM elicited higher docking scores than AA toward its emesis-inducing subunits D2 and D3, and the values are − 9.6 and − 9.9 kcal/mol, respectively. This study also revealed that APT binds with the NK1 receptor by showing a remarkable binding interaction of − 12.7 kcal/mol, while AA exhibited a lower binding interaction of − 8.8 kcal/mol. The docking scores of all the drugs and test ligands used against the specified receptors are displayed in Table 3.

Table 3 Docking value (kcal/mol) of abietic acid and reference drugs against specified receptors liable for inducing emesis.
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Prediction of non-bond interactions between protein–ligand complexes

Findings from the in silico study demonstrated that ligands interact with receptors by establishing a variety of bonds, including hydrogen bonds (HB) (both conventional HB and carbon HB) and other types of bonds, including alkyl, pi-alkyl, sigma, pi-pi T-shaped, pi-sulfur, pi-cation, and pi-pi stacked bonds. For the 5HT3 receptor, AA showed a higher docking value of − 8.1 kcal/mol, while the standard drug OND revealed a docking value of − 6.9 kcal/mol. AA binds with the 5HT3 receptor by forming one hydrogen bond residue (HB), namely ILE98, in addition to showing several hydrophobic bonds (HP) with amino acid residues of PRO113, LYS25, PRO89, VAL95, and TYR114. In contrast, OND did not bind with the 5HT3 receptor through HBs but formed numerous numbers of HP bonds with specific amino acid residues of LEU260, LEU259, VAL237, LEU234, and VAL264. DOM exhibits strong antagonistic action against the D2 receptor with a docking score of − 9.6 kcal/mol by generating 4 HBs, namely THR433, SER430, HIS414, and ASP114. AA exhibited a docking value of − 9.2 kcal/mol and formed one HB, DOM also interacted with the D3 receptor by showing a higher docking value of − 9.9 kcal/mol with three HBs of VAL111, ASP110, and CYS181, whereas AA displayed one HBs with a certain amino acid residue of SER366 and a binding affinity of − 9.2 kcal/mol.

Due to the interaction between the DHM and H1 receptor, which displayed a docking score of − 6.3 kcal/mol with no HBs, it formed several HP bonds, including particular amino acid residues of PHE116, PHE119, PRO202, ILE120, and ALA151. On the contrary, two HBs are formed, including ILE148 and SER68 amino acid residues, and they also obtained a greater binding energy of − 8.5 kcal/mol after docking AA with the H1 receptor. On the other hand, the binding scores of AA for the M1, M2, M3, M4, and M5 receptors were − 7.7, − 8.7, − 7.6, − 10.2, and − 8.9 kcal/mol, respectively. It is obvious that AA exhibited the highest binding affinity against the M4 receptor among all emesis-inducing receptors. Interaction is established between the AA and M4 receptors by the formation of one HB with a particular amino acid residue of PHE186 and four HP bonds, namely ASP432, TYR439, PHE186, and TRP435. In contrast, the standard drug HYS demonstrated docking values against M1, M2, M3, M4, and M5 receptors of − 6.7, − 7.7, − 9.1, − 8.9, and − 8.8 kcal/mol, respectively. However, two HBs are formed due to the interaction between the HYS and M4 receptors with the amino acid residues of TYR92 and ASP432. Additionally, HYS formed three HP bonds with specific amino acid residues of TYR439, PHE186, and TRP435. The highest level of docking value (− 12.7 kcal/mol) occurs from the interaction between the APT and NK1 receptor. It also revealed four HBs with the amino acid residues of ASN89, TRP184, GLN165, and HIS265. Furthermore, APT exhibited numerous numbers of HP bonds. Moreover, AA showed two HB namely HIS265 and THR201 and several HP bonds after binding with the NK1 receptor. The number of HBs, ligands, receptors’ bond types, HB lengths, amino acid residues, and the interacted ligand-receptor pockets are represented in Table 4 and Fig. 5.

Table 4 Amino acid residues, number of hydrogen bonds, and hydrogen bond length of non-bond interactions between the selected ligands and receptors.
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Figure 5
figure 5figure 5

3D and 2D view of protein–ligand interaction and their binding sites with related amino acid residues.

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Estimation of in silico pharmacokinetics and drug-likeness (ADME)

Drug-likeness is an important characteristic of a drug candidate and involves developing a chemical substance into a medication and assessing its pharmacokinetics. The in silico ADMET method play key roles in drug discovery and development. A high-quality drug candidate should not only have sufficient efficacy against the therapeutic target, but also show appropriate ADMET properties at a therapeutic dose. Hydrogen bond donors (HBD), molecular weight (MW), hydrogen bond acceptor (HBA), molar refractivity (MR), and Log P are the primary parameters used to assess drug-likeness. According to the in silico ADMET results, all the drugs used have MW less than 500 Dalton without APT. According to Lipinski’s rule of five, a drug candidate must follow the values of HBD (≤ 5) and HBA (≤ 10) to be developed as a therapeutic, moreover, the APT contains 12 HBA, which breaks Lipinski’s rule of five. Results also demonstrated that HYS and OND are soluble in water, whereas others are comparatively soluble in water. Only APT is partially absorbed by GIT; other drugs are highly absorbed. Results also showed that AA has all the pharmacokinetics and physiochemical properties to be a drug-like compound. The compound also followed the Egan, Ghose, and Veber rules to assure drug-likeness but violates the Lipinski rules because its MLOGP is less than 4.15. Other parameters, for instance, P-gp substrate, TPSA, CYP2C19 inhibitor, BBB permeability, and bioavailability score of AA and reference drugs are given in Table 5 and a graphical representation in Fig. 6.

Table 5 The pharmacokinetics and physicochemical characteristics of Abietic acid and reference drugs are predicted by SwissADME.
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Figure 6
figure 6

Summary of physiochemical, toxicological, and pharmacokinetics properties of selected compounds. [The colored zone is the suitable physicochemical space for oral bioavailability; SIZE: 150 g/mol < MV < 500 g/mol; INSOLU (Insolubility): − 6 < log S (ESOL) < 0; LIPO (Lipophilicity): − 7 < XLOGP3 <  + 5.0; INSATU (In saturation): 0.25 < Fraction Csp3 < 1; POLAR (Polarity): 20 Å2 < TPSA < 130 Å2; FLEX (Flexibility): 0 < num. rotatable bonds < 9].

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In silico toxicity of the selected compounds

Toxicological assessment of small molecules is crucial in predicting their acceptability for use in animal and human models. The toxicity parameters of a drug candidate can be predicted using the online server Protox-II. According to our in silico toxicity assessment, DOM, HYS, and AA are categorized into toxicity class 4 (harmful if swallowed, 300 < LD50 ≤ 2000). On the other hand, OND and DHM fall into toxicity class 3 (toxic if swallowed, 50 < LD50 ≤ 300). In the case of organ (liver) toxicity, our findings predict that all the referral drugs are inactive, whereas AA expressed a positive result (active). Results of the risk assessments of the selected compound were also carried out by using toxicity end point estimation, where HYS, DHM, and AA exhibited no toxicity in the cases of carcinogenicity, immunotoxicity, mutagenicity, and cytotoxicity, but the prediction showed a positive result (active) for the drugs DOM and OND in the cases of immunotoxicity and mutagenicity, respectively, and the other mentioned toxicity parameters are inactive for these two drugs. The different toxicity parameters and their status or values for our selected chemical compounds are given in Table 6.

Table 6 Prediction of different toxicity parameters of Abietic acid and selected referral drugs using Protox-II online tools.
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Discussion

Orally consumed poisonous CuSO4 can trigger a particular vagal-induced vomiting reaction and can injure the mucous membranes in the GIT since CuSO4 is effective as an oxidizing and corrosive agent51,52. The GIT’s visceral afferent nerve fibers are stimulated by peripheral processes, which subsequently transmit the stimulation toward the VC, causing the act of vomiting53,54. The principal mediator of emesis is a CTZ in the medulla that is located outside the blood-brain barrier (BBB). It works by triggering a second region of VC55. Once initiated, vomiting proceeds in two stages, including retching and ejection. A VC or a central pattern generator may be in the area postrema, and the nearby NTS controls the muscles that are responsible for that series of events56. In addition, emesis is caused by local neuronal release of 5HT in the area postrema, triggering different subtypes of 5HT such as 5HT3 and 5HT4 receptors57. Several other receptors, such as H158, mAChRs (M1–M5)59, NK160, and different subtypes (D2 and D3) of dopamine receptors are also involved in the emetic process18, which have a significant impact on stimulating CTZ for inducing emesis.

APT is a highly selective antagonist of the NK1 receptor used to manage and treat chemotherapy-induced and postoperative nausea and vomiting61. Our findings showed that APT exhibits a lower efficacy to reduce the emetic symptoms of the animals as the number of retches and onset of the retching period were comparatively close to those of the vehicle group. The referral drug DOM is widely used for the treatment of nausea and vomiting because it is a selective systemic antagonist of dopamine D2 and D3 receptors, which reduces the activity of these receptors at the CTZ in the brain to alleviate the emetic symptoms62. Our findings from the in vivo investigation demonstrated that the animals given DOM revealed 10.00 ± 1.46 retches, while the animals belonging to the vehicle group showed 66.83 ± 3.58 retches, indicating the drug’s notable emesis diminishing capability. Additionally, DOM remarkably elevated the latency period (63.16 ± 3.99 s) compared to the control group (7.5 ± 0.92 s), which is also evidence of the drug’s remarkable antiemetic properties. In this context, histamine plays an essential role in sending signals from the GI system related to food allergies and histamine seafood poisoning to the brain, leading to vomiting63,64. Antihistamine drugs such as DHM play an important role in minimizing the emetic process by antagonizing the H1 receptor23,65. In our study, DHM-treated animals exhibited comparatively lower efficacy than other treatment groups and failed to manage CuSO4⋅5H2O-mediated emesis. In the case of the 5HT3 receptors, they are implicated in the process of causing vomiting through interpreting information from the digestive system. These receptors significantly influence the enteric nervous system’s ability to control bowel movements and peristalsis66. 5HT3 antagonists like OND hinder the activity of the receptor and alleviate vomiting. In this in vivo test, the OND and HYS-treated animal groups reduced the number of retches compared to the vehicle group to 34.00 ± 2.26 and 46.33 ± 3.70, respectively. Furthermore, the OND and HYS-ingested groups also showed an elevated latency period of 14.83 ± 2.27 and 11.83 ± 1.37 s, respectively. All these findings indicate the potent antiemetic features of drugs. In this respect, the test compound (AA) also has significant capability to alleviate the emetic condition, as the animals treated with AA demonstrated an incredibly reduced number of retches and an elevation in the onset of retching. These results show that AA exhibits better antiemetic activity than the referral drugs APT, DHM, HYS, and OND to mitigate CuSO4⋅5H2O induced-emesis in the in vivo experiment, as animals given AA expressed a lower number of retching and an elevated onset period. In addition, findings revealed that AA shows a dose-dependent antiemetic response. The higher dose of the test compound showed longer latency (98.00 ± 2.44) than the referral drug DOM, and the number of retching was also comparatively similar (10 ± 1.46 and 11.66 ± 2.52 for DOM and AA-40, respectively). These findings indicate remarkable potency compared to DOM to mitigate the emetic process.

A synergistic effect was observed in this study by the combination drug therapy, which resulted in fewer retches and a longer latency period in chicks67. In our in vivo experiment, the combined group of (OND + AA-40) exhibited a significant percentage decrease in retches and an increase in latency period of 76.80% and 82.28%, respectively in comparison to the vehicle group. However, AA increases the antiemetic effect of DOM and HYS in the combination groups by showing a lower number of retching and elevated latency compared to the compound administered alone into the experimental animals. Depicted in Fig. 7 is the Suggested anti-emetic mechanism of the standard medications and test compound, AA.

Figure 7
figure 7

The suggested anti-emetic mechanism of the test compound (abietic acid) compared to the selected standard drugs. [This Fig illustrates the anti-emetic mechanisms of APT, DOM, HYS, and OND, as well as a probable anti-emetic mechanism of AA, based on their affinity for binding to the muscarinic, D2, D3, 5HT3, and NK1 receptors. In this case, AA acts as an inhibitor of D2, D3, 5HT3, M4, and NK1 receptors, while DOM, APT, OND, and HYS inhibit D2, NK1, 5HT3, and muscarinic receptors, respectively. The vomiting center (medulla oblongata) is kept from being triggered when these stomach receptors are blocked, preventing muscular contraction, GIT contraction, and the outcome of no emesis].

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The molecular docking approach attempts to predict the most effective orientation of a compound to its macromolecular target (receptor) when these molecules are bonded together to form an enduring complex8,68. Recently, computational investigations have made it possible to create, screen, and develop medication candidates in a novel way. This cuts down on expenses related to animals and laboratories as well as overall evaluation time69. Molecular affinity is employed to estimate the level of binding (interaction) between a ligand and a targeted protein70. Findings from our in silico study revealed that the test ligand AA exhibits comparatively higher affinity than the selected referral ligands against different types of receptors that are liable for stimulating emesis, such as H1, 5HT3, and various subtypes of muscarinic receptors (M1–M5). The M4 receptor, which is an essential part of the cholinergic system, can control the release of several neurotransmitters, including dopamine, in the brainstem’s CTZ, which evokes emesis71. Among several emesis-inducing muscarinic subtype receptors, the tested ligand (AA) exhibited the highest binding value (− 10.2 kcal/mol) against the M4 receptor and blocked the receptor activity. On the other hand, HYS yielded a binding score of − 8.9 kcal/mol toward the M4 receptor. Among several muscarinic subtypes’ receptors, M3 receptors are activated by acetylcholine, which is under systematic control. These receptors are abundant in smooth muscle and the GIT and are responsible for the contraction of the GI and gallbladder smooth muscles72,73. The M4 receptors are in the cortex and hippocampus among other parts of the brain, but they are most noticeable in the striatum, where it is hypothesized that they regulate dopamine production and locomotor activity74,75. The ligand (e.g., the neurotransmitter acetylcholine), which binds to the active site of the M4 receptor, starts the receptor activity. In this case, the number of amino acid residues that compose the binding site of the M4 receptor has not yet been fully identified, but this study has found some significant residues.

Based on our in silico study, and due to the binding of the tested ligand and reference medications with various receptors, numerous identical amino acid residues are formed, including THR433, VAL91, PHE410 for D2, VAL86, LEU89, VAL107, ILE183, PHE106 for D3, TYR404 for M1, TYR426 for M2, PHE186, TYR92, TRP435, TYR439 for M4, and HIS265, ILE113, PHE264, PHE268 for NK1. This signifies that they interact with the identically highlighted amino acid residues to form a coupling at the same area on the receptors. The highest docking score for the experimental ligand (AA) toward the M4 receptor is caused by the formation of one HB bond and multiple additional hydrophobic bonds. On the other hand, the standard drug HYS formed a lower number of hydrophobic bonds than the experimental ligand. Our findings also showed that the HB distance of AA is 2.24 Å, whereas it is 2.87 Å and 2.77 Å for HYS, which indicates that AA binds more closely to the receptor than HYS. Therefore, we anticipate that PHE186, TYR92, TYR439, and TRP435 are the key residues which implicated in the antagonizing action of AA against the M4 receptor. However, the solitary tract nucleus (STN) and the CTZ of the central nervous system have elevated concentrations of 5HT3 receptors76. It triggers nausea and vomiting by activating the appropriate emetic receptors on the vagal afferents77. The 5HT3 antagonists (e.g., ondansetron) prevent 5HT from activating both centrally in the CTZ and peripherally on GI vagal nerve terminals. This hindrance exerts potent antiemetic activity78. Our in silico investigation also revealed that AA exhibited a higher binding affinity against the 5HT3 receptor compared to the standard medication OND, the binding affinity is − 8.1 kcal/mol and − 6.9 kcal/mol, respectively. The tested ligand interacts with the 5HT3 receptor by forming one HB of ILE98 amino acid residue and several hydrophobic bonds with specific amino acid residues of PRO113, LYS25, PRO89, VAL95, TYR114 whereas, OND did not form any HB. Therefore, our findings show that AA exhibits potential antiemetic activity by blocking both the muscarinic and 5HT3 receptor pathways.

Drug-likeness is a fundamental guideline in the context of drug development and discovery, and it provides qualitative predictions about the probability that a chemical compound would be used in an oral medication in terms of sufficient bioavailability. It identifies the drug’s nature-related pharmacokinetics by assessing the drug’s physicochemical characteristics8,22,79. Lipinski’s rule of five is broadly used in predicting pharmacokinetics and drug-likeness. According to Lipinski’s rule of five, a drug candidate ought to have a MW of 500 g/mol or less, five or fewer HBD, ten or fewer HBA, and a lipophilicity (LogPo/w) of no more than five80. All ligands are predicted to have superior pharmacokinetic characteristics and are within the range of becoming medicines under Lipinski’s criterion. Our chosen test ligand meets each requirement of Lipinski’s rule of five and establishes improved pharmacokinetic characteristics.

For the development of secure and reasonably priced drugs, in silico toxicology studies are essential and critical81. Evaluating the effectiveness of possible medication candidates is the main goal of toxicology studies regarding the process of developing new drugs. The ultimate objective is to interpret animal responses to determine the risk to human subjects82,83,84. Toxicology testing is also crucial for determining any possible adverse effects that compounds may have. For instance, persistent chemical exposure in humans typically results in genotoxicity, immunotoxicity, carcinogenicity, and developmental and reproductive toxicity85,86. Results from this investigation showed that AA does not exhibit immunotoxicity, mutagenicity, carcinogenicity, or cytotoxicity-related toxic effects. However, it did show toxic effects in terms of hepatotoxicity. Due to its ability to antagonize muscarinic acetylcholine and 5HT3 receptors, our findings demonstrated that AA exhibits significant antiemetic activity against the CuSO4⋅5H2O-induced emesis. The synthetic antiemetics that are now on the market have been shown in several trials to exhibit a multitude of adverse effects, including diarrhea or constipation, lethargy, malaise, headache, visual changes, lightheadedness, and dry mouth87,88. In contrast, alternative antiemetic medications, particularly those made of natural ingredients, showed comparatively fewer adverse effects and effective therapeutic advantages89,90.

Studies utilizing specific laboratory animals give crucial information on the positive and negative effects of novel drug candidates as well as potential biopharmaceutical issues91. Consequently, each pre-clinical investigation supports medical researchers in assessing the potential of biologically active compounds for clinical trials. This study showed limitations such as a lack of clinical trials and results based on the behavioral representation of the animals. The probable antiemetic mechanism of AA in this study is based on the in silico and in vivo studies, and it does not present any actual antiemetic mechanism. Taken together, our findings revealed that AA exhibits a potent antiemetic effect in experimental animals by reducing the number of retching and elevating the latency of emesis. The in-silico investigation manifested the reasons behind the antiemetic effects of AA, possibly through the interaction of AA with 5HT3 and different subunits of muscarinic receptors.

Conclusions

In conclusion, findings from this investigation indicated that AA exhibits remarkable dose-dependent anti-emetic activity with a diminishing retching of 11.66 ± 2.52 and an elevating latency period of 98.00 ± 2.44 s for 40 mg/kg in CuSO4⋅5H2O-induced emetic animals compared to the vehicle group of 66.83 ± 3.58 and 7.50 ± 0.92 s, respectively. On the other hand, the emetic symptoms were also notably attenuated in the experimental animals treated with the selected standards (DOM, HYS, and OND), but the efficacy of APT and DHM is comparatively low. In addition, findings from the in silico investigation show that AA successfully meets all the parameters of drug-likeness, and the molecular docking study revealed that the ligand AA has a greater binding affinity against muscarinic receptors, particularly the subtype M4 with a docking score of (− 10.2 kcal/mol) and 5HT3 with a docking score of (− 8.1 kcal/mol) compared to selected standards for these receptors, with docking scores of HYS (− 8.9 kcal/mol) and OND (− 6.9 kcal/mol) for M4 and 5HT3, respectively. Our results also showed that AA exhibits a synergistic effect when given with the selected referral drugs targeting various receptors liable for initiating emesis. The toxicological study also revealed that AA shows no toxic characteristics except hepatotoxicity. However, more investigations are suggested to identify the actual toxic mechanisms of AA. Furthermore, investigations are also required to establish a proper dose for humans through clinical trials and to investigate the exact mechanisms of action of AA in relieving vomiting and nausea brought on by several different reasons.