Computational Prediction of Pharmacokinetic and Toxicological Properties of Rotenoids Present in Roots of Boerhavia Diffusa L.

Introduction

In traditional Indian medicine as well as in other parts of the world, including Southern America and Africa, Boerhavia diffusa is a well-known medicinal herb. This herb is a perennial from the Nyctaginaceae family. Raktapunarnava, Shothaghni, Kathillaka, Kshudra, Varshabhu, Raktapushpa, Varshaketu, and Shilatika are some of its more well-known names. Punarnava’s name itself means “Rejuvenation.” It has been translated into adaptogenic, immunomodulatory, anti-oxidant, aphrodisiac, and nootropic actions in modern allopathy.^1-4 It is a kind of herbaceous plant that growseither horizontally or vertically in areas like meadows, farms, wastelands, and residential neighborhoods.5 The secondary metabolites found in some plants, including tannins, alkaloids, flavonoids, phenols, steroids, and volatile oils, are recognised to have medicinal properties. Additionally, the use of various plant parts-most commonly their decoctions, infusions, oral administration, and others, has been employed as a common form of treatment for a variety of illnesses.⁶

According to published research, among all the plant’s components, the root of Boerhavia diffusa was most frequently used in traditional medicine to treat jaundice, dyspepsia, enlargement of the spleen, abdominal pain, and also as an antistress agent. An analysis of the phytochemical composition of the roots of Boerhavia diffusa showed the presence of a wide range of chemical compounds, including phenolic glycoside, terpenoids, organic acids, rotenoids, flavone, isoflavone, flavonol, flavonoid glycoside, xanthone, Lignin, purine nucleoside, sterol, sterol ester, ecdysteroid, fatty acid, hydrocarbons.⁷

Lipinski’s Rule of Five, frequently cited as Pfizer’s Rule of Five, is employed to evaluate the potency of medication or determine whether chemical compounds with specific biological or pharmacological activity possess physical or chemical characteristics that render them suitable as orally active medicines in humans. When the molecular weight is larger than 500, there are more than 5H bond donors, more than one 10H bond acceptor, and the computed logP is less than five, the rule of five states that poor penetration or absorption is more likely to exist. However, Lipinski made it clear that the rule of five only applies to substances that aren’t active transporter substrates. To characterise the molecular characteristics crucial to understanding drug pharmacokinetics in the human body, the admetSAR and SwissADME servers are employed.⁸

Based on the author’s knowledge, there is no existing literature describing a computer-based screening study for the analysis of rotenoids in Boerhavia diffusa and the prediction of their ADME (Absorption, Distribution, Metabolism, and Excretion) and toxicity profiles, as revealed by a literature search. Hence, the current work used servers and computer programs to analyse the drug like characteristics, ADME, and toxicity profile of a few phytochemicals from Boerhavia diffusa.

Materials and Methods

Server used: ChemDraw, Molsoft, admetSAR. Phytoconstituents used: Boeravinone(A-N), 10-O-De methylboeravinone C, Coccineone-B, Coccineone-E, 6-O-Demethyl boeravinone H, and 2’ -O-methylabroni soflavone

Investigation of Drug Likeness Score and Physicochemical Properties: To calculate the drug likeness score using Lipinskies Ro5, we have identified and selected about 19 rotenoids from Boerhavia diffusa L. in the current investigation. To determine each phytoconstituent’s drug-likeness, Lipinski’s rule of five was applied. In accordance with Lipinski’s regulation, the data regarding drug-likeness was collected. The data was gathered using Molsoft software and the standard SMILES (Simplified Molecular Line Entry System) from ChemDraw.

Computational and Server Based Prediction of Pharmacokinetic and Toxicological Properties: The pharmacokinetic characteristics of phytoconstituents, such as ADME, are crucial in the drug development process. Therefore, to forecast a number of pharmacokinetic factors, we used the online server admetSAR. In addition to other crucial facets of ADME, admetSAR assessed pharmacokinetic features including plasma protein bindings (PPB), skin permeability, blood brain barrier (BBB) studies, and P-glycoprotein.

Results

The plant Boerhavia diffusa L. has a variety of phyto constituents and has been shown to have a wide range of pharmacological and biological effects. In the present computational screening investigation, we have selected: Boeravinone (A-N), 10-O-Demethylboeravinone C, Coccineone-B, Coccineone-E, 6-O-Demethyl boeravi none H, and 2’ -O-methylabronisoflavone. The hydrogen bond acceptor, molecular weight, drug-likeness, LogP value, and hydrogen bond donor property score of chosen phytoconstituents are shown in Table 1.

For defining the molecular characteristics crucial to a drug’s pharmacokinetic behaviour in the human body, including their ADME, the admetSAR was utilised. In the process of developing new drugs, pharmacokinetic properties like ADME of phytoconstituents are crucial. AdmetSAR assesses pharmacokinetic attributes like plasma protein binding (PPB), skin permeability, P-glycoprotein, blood-brain barrier (BBB) research, human intestinal absorption, buffer solubility, and toxicity prediction. Boeravinone (A N), 10-O-Demethylboeravinone C, Coccineone-B, Coccineone-E, 6-O-Demethylboeravinone H, and 2’-O-methylabronisoflavone’s admetSAR profiles are shown in Table 2.

Discussion

Boerhavia diffusa is a perennial herb primarily found across India and is documented to possess rejuvenating properties. According to the literature, it possesses various secondary metabolites responsible for various pharmacological or medicinal responses. An attempt has been made in the current study to carry out computational prediction of the pharmacokinetic and toxicological characteristics of a few Boerhavia diffusa’s rotenoids. We have selected Boeravinone (A N), 10-O-Demethylboeravinone C, Coccineone-B, Coccineone-E, 6-O-Demethyl boeravinone H, and 2’ -O-methylabronisoflavone. ChemDraw software was used to draw structures and then assemble the canonical SMILES. The use of the Molsoft server was made to establish the drug-likeness of chosen rotenoids. The admetSAR (Structure Activity Relationship) server was utilised to determine pharmacokinetic characteristics and toxicity.

Known as Lipinski’s rule of five, sometimes referred to as Pfizer’s rule of five, it is utilized to evaluate drug  likeness and determine whether chemical substances possess physical or chemical properties aligned with their distinct biological or pharmacological actions, rendering them suitable for oral administration in humans. When the molecular weight is larger than 500, there are more than 5H bond donors, more than one 10H bond acceptor, and the computed logP is less than five, the rule of five states that poor penetration or absorption is more likely to exist. However, Lipinski made it clear that the rule of five only applies to substances that aren’t active transporter substrates. To characterise the molecular characteristics crucial to understanding drug pharmacokinetics in the human body, the admetSAR, and SwissADME servers are employed.⁸

The information gathered throughout the study included the pharmacokinetic and toxicological characteristics of several rotenoids, as well as their drug likeness score. Among the selected rotenoids, 2’-O-methylabronisoflavone showed the highest drug likeness score. However, many other rotenoids also were also found to be better drug like candidates.

Conclusion

The present in-silico research found that the assisted prediction and server-based research were crucial and instructive in gathering information about drug candidates, pharmacokinetics, and the harmfulness of bioactive substances from Boerhavia diffusa L. Future work on Boerhavia diffusa L will benefit from the data collected from SwissADME and admetSAR. Among the selected rotenoids, 2’-O-methylabronisoflavone showed the highest drug-likeness score. However, many other rotenoids also were found to be better drug-like candidates. 

Conflicts of Interest

The authors have declared that no conflict of interest is linked with this work.

Acknowledgement

The authors express sincere gratitude to the Principal of the Government College of Pharmacy, Bengaluru, for the continuous support and guidance.