2.2.  Prediction of activity spectra for substances (PASS) analysis
PASS is an online web tool hosted at http://195.178.207.233/PASS/index.html (Ahmad, 2019). Based on the structure–activity relationship with a known chemical entity, PASS analysis server predicts biological activities of chemical compounds. The tool predicts the pharmacological behavior, mechanism of action and side effects such as mutagenicity, carcinogenicity, embryotoxicity and teratogenicity. In the present study, PASS analysis was performed using OSIRIS Property Explorer version 4.5.1. (http://www.openmolecules.org/propertyexplorer/index.html)

2.2.1.  Lipinski’s rule of five
The druglikeness of WS phytoconstituents was also assessed using Lipinski’s rule of five (Ertl et al., 2000; Lipinski et al., 1997; Veber et al., 2002). The parameters of druglikeness such as MW ≤500, logP ≤5, number of hydrogen bond donors (NOHNH) ≤5 and hydrogen bond acceptor sites (NON)≤10, topological polar surface area (TPSA) (≤140 Å2), and number of rotatable bonds (≤10) were determined. In the present study, the druglikeness of selected WS phytoconstituents was analyzed using Molinspiration (http://www.molinspiration.com/cgi-bin/properties) and compared to that of standard reference drugs.

2.2.2.  Veber rule
For oral bioavailability, membrane permeability is an important factor. Polar surface area and number of rotatable bonds are two critical considerations for a compound to behave as a potential drug candidate. With a reduction in polar surface area, permeation increases and with the increase in number of rotatable bonds permeation decreases significantly (Veber et al., 2002). The following two criteria should be met by a potential drug candidate in order to obey Veber rules:≤10 rotatable bonds;
Polar surface area ≤140Å2 (or 12 or fewer H-bond donors and acceptors).

2.2.3.  Ghose filter
Receptor binding, cellular uptake and bioavailability of drug molecules is strongly influenced by molecular lipophilicity and molar refractivity. Both of them signify hydrophobic and dispersive (van der Waals) interactions (Ghose & Crippen, 1987) of a drug molecule and are employed in 3D-QSAR studies to evaluate the drug-like character of molecules under study (Viswanadhan et al., 1990, 1991). The following are the qualifying parameters for a putative drug candidate as per Ghose filter:clogP range between -0.4 and 5.6, with an average value of 2.52;
MW range between 160 and 480, with an average value of 357;
Molar refractivity range between 40 and 130, with an average value of 97;
Total number of atoms between 20 and 70, with an average value of 48.
The above parameters should be kept in mind for testing hypothetically proposed compounds before any in vitro and in vivo experimentation (Ghose, 1987; Ghose et al., 1999).

2.2.4.  Leadlikeness
According to Teague et al. (1999) compounds with MW in the range 250–350, a XLOGP3 value of <3.5 and <7 rotatable bonds satisfy the criteria for leadlikeness.

2.2.5.  Egan rule
It is defined as compounds having TPSA > 131.6 Å or log p > 5.88 have drug-like character and properties (Egan et al., 2000).

2.2.6.  Muegge rule
It states that compounds having MW between 200 and 600, XLogP between −2 and 5, TPSA < 150, no. of rings < 7, no. of carbon atoms >4, no. of heteroatoms > 1, no. of rotatable bonds < 15, no. of H-bond acceptors < 10, no. of H-bond donors < 5 are found to obey Muegge rule and behave as potential drugs (Muegge et al., 2001).