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In silico screening and molecular docking study of compounds from Pedalium murex L. with Vasopressin2 receptor target for Autosomal Dominant Polycystic Kidney Disease



Autosomal dominant polycystic kidney disease (ADPKD) is frequently inherited disease. The medicinal plant Pedalium murex (P. murex) Linn, that has anti-inflammatory, antiurolithiatic, and diuretic properties, has a greater tendency to cure urinary defects. P. Murex compounds have been studied in order to find an effective treatment against the Vasopressin 2 receptor (V2R), which is a target for ADPKD. The compound structures were designed using ChemSketch software, which was then optimised for the exploration of pharmacokinetic properties. Finally, AutoDock VINA programme was used to execute molecular docking, and the findings were analysed and visualised in Discovery studio visualizer.


Virtual screening using PyRx software finds seven compounds from P. murex with binding affinities ranging from − 8.6 to − 5.8 kcal/mol, which will be used for further pharmacological characteristics study. Luteolin has a higher druglikeness and an overall drug score of 0.84, indicating as a most suitable compound. Furthermore, luteolin docking and bonding study reveals improved receptor (V2R) H-bonding with Phe105(2.26 and 2.96), Gln119(2.78), and any Lys116(2.16).


Based on affinity score, screening of various compounds from P. murex against the V2R target for the ADPKD showed that the phytocompound luteolin has superior pharmacological characteristics and bonding. Luteolin from P. murex can be used as a possible therapeutic candidate after rigorous in silico investigation.

Graphic abstract


A number of abnormal signalling pathways become triggered in autosomal dominant polycystic kidney disease (ADPKD), resulting in renal cytogenesis [1]. Polycystin-1 (PC1) and Polycystin-2 (PC2) encoded by PKD1 and PKD2 genes that work as a complex in the normal renal architecture, gets affected and become non-functional by binding of Gα-subunit of GPCR at G-protien binding site of PC1 that subsequently activates number of aberrant signalling pathways. The sodium/potassium/chloride co-transporter, i.e. SLC12A1 (encodes NKCC2), which is found in the apical membrane of the thick ascending loop of henle (TAL), plays an important role in renal function and is regulated by the Vasopressin2 receptor(V2R) protein [2]. To regulate the passage of ions into and out of renal cells, the cross talks of SLC12A1 among other renal transporters proteins play important role for normal kidney functions [3]. Vasopressin levels increase in disease, and abnormally high intracellular cyclic AMP (cAMP) levels cause an imbalance in the SLC12A1, a Na:K:Cl co-transporter, resulting in a reduction in calcium levels and chloride secretion from cyst lining [4]. The Vasopressin 2 receptor is impaired as the amount of cAMP increases in a disease state, which affects nephronal reabsorption, resulting in a urinary defect [5]. cAMP plays a central role in the pathogenesis of ADPKD. The tolvaptan drug has several renal and extrarenal side effects [6]. Different amino acids involved in ligand binding have been identified and used in a molecular docking study against a P. Murex compound.

P. Murex (Family: Pedaliaceae) is a commonly known as Large Caltrops or Gokhru (India). Different parts of plant are used for the treatment of different ailments. It has a high proclivity for curing deadly diseases due to its anti-inflammatory, antiurolithiatic, and diuretic properties, as well as a high tendency for curing urinary defects. Complications such as urinary tract disease and gastrointestinal tract disorders have also been benefited [7]. Pharmacologically, P. murex has been investigated for antiulcerogenic, nephroprotective, hypolipidemic, aphrodisiac, antioxidant, and antimicrobial activities. The existence of a significant amount of compounds used for the synthesis of contraceptic drugs has made the plant famous among phyto-chemists [8]. Quercetin, diosmetin, luteolin, hispidulin, ursolic acid, caffeic acid, and various fatty acids are among the other phytochemicals contained in the plant [9].

The recent research has focused on identifying a possible ligand molecule from P. Murex, which can act as a suitable drug candidate. The compounds from P. murex were identified using docking-based screening, drug properties, molecular docking, and further bonding with V2R was identified to finalise the suitable complex for the treatment of ADPKD.


Compounds from P. murex have been identified, designed, optimised, and screened using docking to determine the most suitable natural compound that can inhibit V2R. Because its functionality is affected as a result of improper signalling, which affects the renal transporters as previously discussed, the V2R protein is a possible target protein in ADPKD.

Receptor structure identification

The sequence of the vasopressin V2 receptor isoform 1 (Homo sapiens) is retrieved from NCBI’s GenBank. The structure of the vasopressin V2 receptor isoform 1 (Homo sapiens) is predicted by Swiss-Model, an automated modelling server, by using the best template identified by the sequence alignment based on the expected value and scores. The atom coordinate file of the template structure is retrieved from PDB (Protein Data Bank) database. Predicted structure is then visualised, and energy is minimised using SwissPDBViewer (SPDBV), a structure visualization and analysis tool [10]. Further, properties of the receptor are identified and validated by PROCHECK structure validation tool.

Binding/active site identification

In order to identify amino acids involved in receptor binding, a SCFBIO Tool ( was used for the prediction of putative active site. The amino acids Val115, Lys116, Gln119, Met123 have been involved in the receptor binding and responsible for key functionality as per literature search [11, 12]. By targeting these amino acids, an aberrant signalling can be reduced or stopped. The active site/binding site dimensions were selected according to amino acids involved in receptor binding.

Compounds screening

The compound from P. murex was retrieved from the PubChem database ( and the chemical structure was drawn by ChemSketch software (ACD/Labs Version 2020.2.1) [13]. Further, open babel software (Version 3.1.1) has been used to convert molecular file formats of compounds [14]. The library of ligand molecules was then subjected to virtual screening based on docking using PyRx software [15]. PyRx classified the ligands according to their binding affinity, which represents the highest potential interaction with the receptor. The molecules with the lowest binding affinity (Kcal/mol) were chosen for further investigation of drug properties.

Drug properties identification

The pharmacological properties of the ligand molecules were identified by OSIRIS properties explorer [16,17,18]. The lipinski’s rule, molecular weight, H- bond acceptor, H-bond donor, clogp, druglikeness and drug score were analysed. The above-mentioned software was also used to investigate their mutagenic, tumorigenic, irritating, and reproductive effects. The compounds were then studied for molecular weight, clogp, topological polar surface area (TPSA), solubility, H-donor, H-acceptor, druglikeness, and total drug score. The software employed the logarithm of the partition coefficient between n-octanol and water, log(Coctanol/Cwater), to calculate compound hydrophilicity. Because high values imply poor absorption, substances with a clogp value of less than 5.0 have a high possibility of being well absorbed.

Drug absorption, including intestinal absorption, bioavailability, and blood–brain barrier penetration, has been identified by topological polar surface area (TPSA). It is a valuable measure for predicting drug transport characteristics. A compound’s water solubility has a considerable impact on its absorption and distribution characteristics. Low solubility is usually associated with poor absorption; therefore, the overall goal is to avoid poorly soluble compounds.

Docking verification and analysis

The shortlisted ligand molecule based on the drug properties and docking potential is again verified by AutoDock VINA. In addition, the discovery studio visualizer is used to visualise and analyse the shortlisted docked complexes [19]. AutoDock VINA is a versatile molecular docking software that offers nine different docked ligand molecule modes with the receptor. The optimal mode with the lowest binding energy was chosen and studied for various bonding distances and interactions with the binding site residues.


The V2R amino acids that have a proclivity for binding ligand molecules were found through the literature search mentioned earlier (Fig. 1). Dissociation of polycystin complex (PC1 and PC2) subsequently leads to the aberrant increase in the level of cAMP. The pathogenic activation of the Vasopressin2 receptor causes an abnormal increase in vasopressin levels, as well as an increase in cAMP levels. Cyclic AMP (cAMP)-driven mechanisms are central to the pathogenesis of ADPKD. It affects the functionality of SLC12A1 renal transporter, i.e. a regulator of Na:K:Cl co-transporter. The vasopressin V2 receptor isoform 1 (Homo sapiens) sequence was obtained from NCBI’s GenBank (accession number: NP_000045.1), and homology modelling was performed using Swiss-Model with the best match template selected from a BLAST search against the (Protein Data Bank) PDB database, and energy was minimized by steepest Descent and Conjugate gradient methods. PROCHECK analysed the expected model and found 91 per cent core value.

Fig. 1
figure 1

Vasopressin2 receptor signalling in autosomal dominant polycystic kidney disease. Dissociation of polycystin complex (PC1 and PC2) and binding of Gα subunit of GPCR with PC1 subsequently leads to the aberrant increase in the level of cAMP. The pathogenic activation of the Vasopressin2 receptor causes an abnormal increase in vasopressin levels, as well as an increase in cAMP levels. Cyclic AMP (cAMP)-driven mechanisms are central to the pathogenesis of ADPKD. It affects the functionality of SLC12A1 renal transporter, i.e. a regulator of Na:K:Cl co-transporter

Active site prediction

SCFBio Tools ( predicted the V2R active site and correlated the results with the literature reference. For the binding site identification, chosen amino acids with putative roles in functionality and aberrant signalling were investigated. The selected cavity points of the predicted site of docking were − 11.372, − 4.173, 101.662, and the cavity volume is 457 Å cubic (Cavity5 = LRNVAGWHFPSMYITC). Based on the selected amino acids, the cavity dimensions further used for docking-based screening.

Ligand designing and virtual screening

ChemSketch (ACD/Labs Version 2020.2.1) was used to design the structure of natural P. murex compounds, which were stored in.mol2 format, and all of the chemical structures were translated from.mol2 to.pdb format using Open Babel Software (Version 3.1.1). PyRx software was used to screen a library of lignad molecules in pdb format for docking-based screening with V2R as the target protein. In the configuration file for the PyRx software’s AutoGrid engine, the grid box dimension (Ả) X = − 11.8561 Å, Y = 4.4132 Å, Z = 122.1596 Å was used. Compounds with binding energy ranging from − 8.6 to − 5.8 kcal/mol were selected for further analysis (Table 1).

Table 1 Compound screening from Pedalium murex L

Pharmacokinetic properties of the selected ligands

The ADMET analysis of the selected compound reveals that diosmetin and hispidulin shows 0.83 and 0.77 overall drug score with molecular weight 300 g/mol. Among the other natural compounds investigated, luteolin had the lowest molecular weight 286, clogp 1.99, solubility − 2.56, druglikeness score 1.9, and overall best drug score of 0.84. Due to the druglikeness, cLogp, solubility, molecular weight, and toxicity risks, the drug score displays a compound’s overall frequency to qualify as a drug candidate. Furthermore, the examination reveals no toxicity and follows the Lipinski rule as shown in Table 2.

Table2 Properties of the selected compounds as a drug candidate

On the basis of ADMT analysis, diosmetin, hispidulin and luteolin docking are again verified by AutoDock VINA with the same grid dimension and visualized in UCFS Chimera [20]. For the bonding and interaction analysis, complexes were subjected to discovery studio visualized for the bonding interaction analysis. Diosmetin shows H- bonding with GLN-96, Vanderwall interaction with Cys192 and Pi-Alkali bonding with Ala98 & Pro95 amino acids of V2R, whereas luteolin shows H-bonding with Phe105, Gln-119 and Lys-116 and Pi-Alkali bonding with Cys192, Ala98, Pro95. The hispidulin only shows vanderwall Arg106 and Pi-Alkali interaction with Ala98, Pro95 and Cys192 as shown in Table 3. Luteolin form conventional H-bonding with the amino acids is involved in the ligand binding within the predicted active site (Fig. 2). Further, luteolin docking with V2R is again verified, and interaction pattern is studied as shown in Fig. 3, and further bonding analysis reveals better receptor (V2R) H-bonding with Phe105(2.26 and 2.96 Å), Gln119(2.78 Å) and Lys116(2.16 Å) residues involved in receptor binding (Fig. 4).

Table 3 Types of bonding and interacting amino acids of V2R with top five compounds
Fig. 2
figure 2

Comparative study of luteolin, diosmetin and hispidulin and luteolin interaction with V2R target. a Luteolin good overall drug score (0.84) with no toxicity. c Diosmetin shows 0.83 overall drug score d Hispidulin shows 0.77 overall drug score. b shows conventional H-bonding with PHE105, GLN-119, LYS-116

Fig. 3
figure 3

Luteolin docking with V2R and cavity properties.. a PyMol docked view. b cavity H-bond view. c Cavity hydrophobicity view. d Cavity ionizability view. e Show good solvent accessibility. f Aromaticity View

Fig. 4
figure 4

Interaction representation of V2R with luteolin. H-bonding Van der Walls Interaction Pi-Cation Pi-Pi Stacked Alkali Pi-Sulphur . Conventional H-bonding with bond distance PHE105, GLN-119, LYS-116


Compounds from medicinal plant P. murex were analysed and docked with V2R in order to identify the best complex that can be further analysed in vitro study. P.murex has nephroprotective activity [21]. cAMP plays a key role in the pathogenesis by affecting the serum vasopressin level and SLC12A1 functionality leading to urinary defects in the ADPKD patients [22]. V2R docking-based screening of compounds drug properties reveals that diosmetin, hispidulin and luteolin show better drug properties, whereas luteolin with molecular weight 286 g/mol shows best properties as compared to other compounds. Furthermore, as compared to diosmetin and hispidulin, luteolin forms Pi-Alkali bonding (Cys192, Ala98, Pro95) and conventional H-bonding with Phe105(2.26 Å and 2.96 Å), Gln119(2.78 Å) & Lys116(2.16 Å), the key amino acids having potential role in pathogenesis according to literature reference and predicted active site. Luteolin has anti-inflammatory and anticancer properties linked to the activation of apoptosis, as well as the inhibition of cell proliferation, metastasis, and angiogenesis [23]. Luteolin may restore renal dysfunction, histological damage from renal injury, oxidative stress, neutrophil aggregation, inflammatory reaction, apoptosis, and endoplasmic reticulum stress, according to research on rats [24]. Luteolin derived from P. Murex can be used as a possible drug candidate based on the in silico study. In addition, the above-mentioned finding will be confirmed by in vitro studies.


Molecular docking-based screening of compounds from P. Murex with V2R target reveals that amino acids having potential role in the cystogenesis show interaction with receptor. Three of the compounds, diosmetin, hispidulin, and luteolin, exhibit improved pharmacokinetic and therapeutic characteristics. However, based on the number of parameters and overall drug score, luteolin was found as the best appropriate ligand when compared to others. The best pharmacological features and the most persistent receptor bonding observed in luteolin were reviled by type of bonding interaction. As a result, luteolin-based medicines may be a viable choice for treating ADPKD.

Availability of data and materials

Data presented in a coherent way in the result section.



Vasopressin 2 receptor


Autosomal dominant


Polycistic kideney disease


G-protein coupled receptor


Absorption, distribution, metabolism and excretion


Protein data bank


Root mean square distribution


Cyclic adenosine monophosphate


Thick ascending loop of henle


Solute carrier family 12 member 1


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Authors are duly thankful to Maharaja Agrasen University, Solan (H.P) and Lyallpur Khalsa College, Jalandhar, India for providing the laboratory facility in the Department of Biotechnology, School of Basic and Applied Science, MAU, Solan (H.P.) and Bioinformatics Lab, Post Graduate Department of Biotechnology, Lyallpur Khalsa College, Jalandhar, India.


The present study was carried out without any financial support from any funding agency.

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GR as a Ph.D. fellow did this complete research work including screening and docking. SKG has supervised this work. AK and GS helped in the manuscript editing. HL given valuable suggestions. All authors read and approved the manuscript.

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Correspondence to Shiv Kumar Giri.

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Ram, G., Kumar, A., Hemlata et al. In silico screening and molecular docking study of compounds from Pedalium murex L. with Vasopressin2 receptor target for Autosomal Dominant Polycystic Kidney Disease. Beni-Suef Univ J Basic Appl Sci 10, 63 (2021).

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  • Polycystic kidney disease
  • Drug likeness
  • Binding affinity