Background

Rhazya stricta Decsne (Apocynaceae family), a traditional herbal medicinal plant from Western and South Asia, has been shown to have multiple pharmacological effects due to the presence of over 100 alkaloids [1,2,3]. The chemical constituents of this plant (R. stricta) may possess biological activities of antifungal, antimicrobial, antioxidant, CNS, hypertension, metabolic, and inflammatory disorders. Rhazimine, an alkaloid isolated from R. stricta leaves, was shown to affect arachidonic acid metabolism in human blood [4]. This alkaloid was shown to be a dual and selective inhibitor of platelet activating factor (PAF)-induced platelet aggregation and arachidonic acid metabolism. Other effects of the lyophilized extract of R. stricta include an antispasmodic effect in rat muscles [5]. In another study, antioxidant effects were observed at higher doses, and it reduced the hepatic and renal concentrations of glutathione (GSH) and increased the ascorbic acid levels, whereas the degree of lipid peroxidation was reduced [6]. A recent study has shown that the basic alkaloid fraction from R. stricta significantly induces one of the chemopreventive enzyme-Nqo 1, through an Nrf 2-dependent mechanism, thereby establishing its role as an anti-tumor agent [7]. In another pharmacological study, the biochemical parameters including blood lipid profile concentrations, liver enzyme activities and kidney functions were analyzed in rats [8]. It was also found that aqueous extract of R. stricta and indole alkaloids caused a significant increase in serum adiponectin levels and resulted in significant improvements in insulin resistance [9]. In another follow up study, we observed indole-alkaloids of R. stricta improved not only the lipid profile and liver function but also led to improvements in the insulin levels in rats, most likely via modulating insulin resistance [10]. Indole-alkaloids of R. stricta had been reported to have anticancer properties [11]. Other studies by our departmental colleagues showed that alkaloid extract of R. stricta leaves inhibited proliferation, colony formation and anchorage-independent growth in various cancer cell lines such as colon cancer, breast cancer and lung cancer [12,13,14].

Understanding the chemical structure, physiochemical, and chemical-informatic properties of these natural product compounds will give clues for further modifications required in their structures responsible for their biological activities. Even though, there have been about 100 chemical entities of indole-based alkaloid constituents of R. stricta which have been reported but their chemical structures are yet to be clustered and identified, and moreover the pharmacological application of any one of these constituents towards human health is yet to be identified. Understanding qualitative correlation of structures to their chemical druggability, IP potential, and their applicability towards a therapeutic area would be worth exploring prior to pre-clinical studies. Availability of this plant (R. stricta), thus its phytochemical constituents largely in Arabian and South Asian region makes it worth studying through computational, synthetic, and biological view point. Indole based alkaloids such as vinblastine and vincristine are well known for their anti-cancer properties. From systematically generated informatics data analysis, one would be able to evaluate the physiochemical properties of the potential therapeutic compounds. These promising molecules which have “desirable pharmacophores” may provide obvious extension to a better targeted therapeutic benefit. Conventional drugs obey set of rules such as Lipinski’s Rule-of-Five (RO5) [15], wherein all orally administered molecules need to have certain physiochemical properties. Calculation of these cheminformatic properties has thus become essential for all projects of new drug discovery which go through oral route of administration. Along with RO5, the new molecules also have to adhere to certain parameters which yield favorable ADMET outcome of an oral drug. We further evaluated these molecules for therapeutic activity, including anticancer, anti-obesity, anti-inflammatory, and anti-bacterial properties. Although these predictions are indicative only, the value of predictions in various target classes and therapeutic areas would be very useful for future experimental studies. Moreover, their metabolic fate with key enzymes such as P450’s is also predicted for probable drug–drug and drug-target (P450) interactions (reviewed in [16, 17]).

Methods

For prediction of various therapeutic potential of these molecules, commercially and publicly available technologies as below were utilized.

  1. a.

    PharmaExpert (http://www.pharmaexpert.ru)—PASS [18]

  2. b.

    Superpred (http://prediction.charite.de)—Predictive Targets [19]

  3. c.

    SwissTargetPrediction (http://www.swisstargetprediction.ch)—Predictive Target [20]

  4. d.

    CDRUG (http://bsb.kiz.ac.cn/CDRUG)—Anti-cancer activity [21]

Schrodinger [22], a scientific software that predicts drug-like properties and liabilities (viz. HERG and CNS), and ACD/Labs [23] for physiochemical and cheminformatics studies were utilized. Details of the molecules, names, structures were obtained from the literature, commercial sources, and knowledge-based web sources. Tables 1 and 2 gives the details of these molecules together with their 2D SMILES notation, respectively.

Table 1 Chemical structures and names of Rhazya stricta compounds
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Table 2 SMILES codes for Rhazya stricta compounds
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Results and discussion

Physiochemical and cheminformatic studies

ACD/Laboratories informatics modules generated physiochemical and cheminformatics data of R. stricta indole and non-indole alkaloids. For all the selected 78 molecules in this study, it was observed that less than 20% of the molecules are having molecular weights >450, while most molecules range around 300–350, indicating their viability for additional medicinal chemistry amenable nature. Most of these molecules are also moderately to highly soluble—mainly due to the high value of pKa (leading to solubility at neutral pH). Additionally, many of these indole/non-indole molecules are also less lipophilic (~75% of them have logP ~3 to 4). Alkaloids that violate Lipinski’s Rule-of-5 are either due to molecular weight or logP, are tetrahydrosecamine; presecamine; beta-sitosterol; ursolic acid; stigmasterol; oleanolic acid; secamine; bis-strictidine; 3,14-dehydrorhazigine; 16-hydroxyrhazisidine; rhazisidine; rhazigine; dihydrosecamine; dihydropresecamine; tetrahydropresecamine; decarbomethoxy-15,17-tetrahydrosecodine;16s,16′-decarboxytetrahydro-secamine. Figures 1 and 2 give the plots of molecular weight and LogP (lipophilicity) of individual compounds, accordingly. Since most of the molecules have a basic nitrogen and sometimes, may be more than one, leading to a larger pKa at physiological pH—thus leading most molecules are highly to moderately soluble at physiological pH. Very few compounds and non-indole alkaloids have no basic nitrogen leading to highly insoluble compounds in water at physiological pH. As the acidity goes up (leading towards pH 1), most compounds become largely soluble. A qualitative and quantitative (computational) estimate of solubility of these compounds are given in Tables 3 and 4, respectively.

Fig. 1
figure 1

Variation of Molecular weight of compounds of Rhazya stricta

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Fig. 2
figure 2

Variation of LogP of compounds of Rhazya stricta

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Table 3 Qualitative assessment of Rhazya stricta compounds with respect to Lipinski’s Rule-of-5 and solubility
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Table 4 Predicted solubility and pKa (acid and base) of various Rhazya stricta compounds
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QUIKPROP calculations

Predicted Quikprop properties for potential cardiac liabilities such as HERG, and CNS liabilities (Blood–Brain-Barrier) and drug-like nature of these molecules indicate that many of these molecules are well within the boundaries of accepted hit-, and lead-like nature. QuikProp calculations were performed using Schrodinger’s Maestro for various alkaloids of R. stricta. These predictions not only give Rule-of-5 data, but also predict the cardiotoxicity predictions (HERG) and CNS penetration potential (logBBB) properties. More importantly, it also gives the prediction regarding cell-permeability (Caco2). All these models are well validated in literature, and most of them perform well within the reproducible results for training datasets. Results indicate that many of the molecules have decent permeation through Caco2 cell lines (>300), while the polar surface area (PSA) is not too high (>120) for oral absorption. For HERG toxicity prediction, below −5 (i.e. −6, −7 etc.) is not considered to be safe. Hence, those molecules whose logHERG values are well below -5 (such as geissoschizine, presecamine, tetrahydrosecamine) may exhibit cardioliability. The human intestinal absorption is also predicted, and it appears for most molecules, these values are larger. Any %HIA prediction >90% is expected to be well absorbed, and their polar surface area (PSA) is also a direct correlation to it. Those molecules whose molecular weights are >500 exhibit rule-of-5 violation and this violation goes beyond 1 to a maximum of 3. Those molecules appear structurally much larger and like dimers. Table 5 gives computed Quikprop computed values of various alkaloids of R. stricta. Table 6 also indicates various other physiochemical parameters including surface tension, parachor etc. of R. stricta indole and non-indole analogs.

Table 5 Quikprop calculation (for physiochemical properties) of Rhazya stricta compounds
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Table 6 Surface related and ring-related properties of Rhazya stricta compounds
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Predicted therapeutic area applications

PASS—prediction of activity spectra for substances

This web-based predictive server from Way2Drug, has variety of annotators of substances for their probability of active or inactive towards few targets. Out of all services and products of them, we utilized PASS method of predictions. More than 100 activities are predicted with their probability of activities and in-activities. Some of them include kinase inhibitors, GPCR antagonists, and some specific targets like adrenergic receptors, and their kinase inhibitors. We considered the probability of active (Pa) >0.3 (i.e. >30%), and should be greater than probability of inactive (Pi). Given these conditions, we observed many alkaloids have indicated Pa >0.8 in certain conditions (such as, anthrine has predicted Pa at 90% towards β-adrenergic receptor kinase inhibitor, 5-HTA release stimulant). Majority of them also is predicted to be substrate to CYP3A4 and CYP2D6 indicating their metabolic instability (Pa ~ 0.5, 0.4, respectively). Several such predictions for all 78 alkaloids has been computed—leaving predictions to be validated, experimentally. Similarly, dihydrocorynantheol and corynantheol were also predicted to be 5-HT release stimulants, and have been projected to be chemosensitizers. Eburnamenine is predicted to be a Nootropic agent at 90% Pa, while eburnamine is predicted to be a CNS (anti-depressant and mood disorder management agent at >96% Pa). Strictosidine is predicted to be an antiprotozoal at 86% Pa, β-sitosterol is anti-hypercholesterolemic agent with Pa ~98%, rhazidigenine (rhazidine) is an antidyskinetic at 60% Pa, secamine is a H1F1A expression inhibitor at 83% Pa (but a non-pharmaceutically acceptable molecule due to high MW and many RO5 violations). A similar observations is also made for 16-hydrorhazisidine (72% Pa for H1F1A expression inhibitor). Strictamine is predicted to be gluconate 2-dehydrogenase acceptor with 70% Pa, and 1,2-dehydroaspidospermine (which is a small molecule) has been predicted to be analeptic with 77% Pa. Dihydrosecamine is predicted to be a H1F1A expression inhibitor with 77% Pa, and rhazidigenine-N-oxide is predicted to be a cognition disorder agent with 64% Pa. Decarbomethoxy-15,20,16,17-tetrahydrosecodine is a small molecule with ~70% Pa for antidyskinetic and antineuronic agent, 1,2-dehydrospidospermidine-N-oxide is predicted to be 87% as analeptic.

Anticancer activity through CDRUG

This set of predictions using the structures and SMILES codes of the alkaloids, annotates the anti-cancer activity by predicting “Mean logGI50”. Most molecules that have Mean LogGI50 values lower than −5 are considered to have anti-cancer activity. It is interesting to know that all the molecules of R. stricta alkaloids (indole/non-indole) have predicted mean logGI50 values ranging between −4.95 and −6.50—indicating they all may have anti-cancer activities. There are about 10 compounds that have predicted logGI50 values less than −6, which indicate strong anti-cancer activity. Table 7 shows the predicted mean LogGI50 values of all the compounds considered in the present study.

Table 7 Predicted mean LogGI50 of Rhazya stricta compounds whose values lower than −6.0 are highlighted in italics may exhibit anti-cancer activity
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SuperPred—predicted target interactions

From this server studies on R. stricta alkaloids, we observed that many of these molecules may interact with CYP2D6 or CYP3A4 as substrates. The indication of these results mean that their target may be unknown, but they do modify the drug metabolism, and affect drug–drug interactions.

SwissTarget prediction

While predictions from this web-server may suggest each molecule have certain target activity, they almost correlate well with the PASS server prediction—which gives additional probability of prediction for each molecule to be active or inactive against the target of interest.

Overall from the calculated cheminformatics studies and web-server predictions, we understand that few molecules like anthrine, condylocarpine, dihydrocorynantheol etc. have predicted GIC50 values in sub µM concentrations, while they also have predicted drug–drug activity towards CYP3A4, and CYP2D6 enzymes. Most molecules turnout to be modulators of membrane receptor ligands while some have predicted cholinesterase, CNS (5HT2x), adenosine (A2A/A2B) activity. Moreover, all molecules have predicted activity towards certain targets (Pa > 30%).

Conclusions

Table 8 indicates the top 10-best naturally occurring indole alkaloids of R. stricta that were predicted to be having decent anti-cancer activity and other good physiochemical properties together with cheminformatics properties—these molecules are antirhine, 3-epi-antirhine, condylocarpine, eburnamine, eburnamonine, taberonine, ursolic acid, stigmasterol, olenaolic acid, (+)-vincadiformine, (−)-vincadiformine, (−)-16R,21R-omethyleburmanine, 15-hydroxy-vincadifformine, and dihydroburnamenine.

Table 8 Key details of top molecules with predicted targets for anti-cancer and anti-obesity, probable rule-of-5, predicted LogGI50 with predicted H-, and p values
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