Anticancer activity of secondary metabolites from Bauhinia tomentosa Linn. leaf – An in silico approach

Introduction and Aim: Plants and plant derived products are used for human healthcare since the dawn of human civilization. About 80% of modern drugs are from natural origin. Many dreadful diseases like cancer are treated using drugs of natural origin. In the present study, a medicinal plant B. tomentosa Linn. leaves were investigated for its anticancer activity using A549 (Human Adenocarcinomic Alveolar Basal Epithelial Cells) cell lines. The active components were identified using GC-MS (Gas Chromatography- Mass Spectrophotometry) analysis. The aim of the present study was to identify potential lead compounds against various protein targets that are involved in lung carcinogenesis using molecular docking approach. Materials and Methods: 3D structures of compounds reported from GCMS analysis of B. tomentosa were built using Chemsketch software. All the compounds analyzed exhibited antioxidant, anticancer, antimicrobial, anti-inflammatory, and chemo preventive properties. Docking studies were performed using Molegro virtual docker (MVD). Results: The docking studies revealed that the ligands either activate or inhibit the selected target proteins appropriately. This shows that the phytochemicals of B. tomentosa leaf was found to have appreciable anticancer activity. Conclusion: The presence of various bioactive phytoconstituents justifies the use of the leaf for various ailments by traditional practitioners.


INTRODUCTION
ung cancer is the third most common cancer worldwide. Cancer is the cause of more than 20% of the mortality worldwide (1). Most of the anticancer drugs that are currently used in chemotherapy are cytotoxic to normal cells also and hence leads to adverse side effects. Even therapeutically effective doses of cytotoxic drugs may produce severe irreversible reactions in normal tissues and become toxic to the cancer subjects.
Plants and plant derived products are used for human health care since the dawn of human civilization. Ayurveda and other plant-based remedies are a part of cultural heritage of India. About 80% of modern drugs are from natural origin. Many dreadful diseases like cancer are treated using drugs of natural origin. In the present study, the medicinal plant B. tomentosa Linn. Leaves were investigated for its anti lung cancer activity. To identify the anticancer activity, MTT assay, DNA fragmentation assay was done in earlier studies (2). The ethanol extract was then subjected to various gene and protein expression studies to demonstrate its role on both nucleic and epigenomic regulations in previous studies. From the results of the above studies, it was observed that the active components of EBT have anticancer activity. To identify the bioactive compounds, GC-MS analysis was done. Hence for lead compounds identification, in silico approach was followed.
The aim of the present study is to identify the potential lead compounds against various protein targets that are involved in lung carcinogenesis using molecular docking approaches and subjecting the identified molecules for ADME (Absorption, Distribution, Metabolism and Excretion) analysis. This work will help to identify the compounds, which may be used for therapeutic purpose.

Methodology
All the computational analysis was carried out using Molegro Virtual Docker (MVD) 5.0Å.
Protein structure X-ray crystal structure and Solution NMR structure of the following proteins were retrieved from Protein Data Bank and the details of their resolution (

Protein Preparation
The target protein structures were prepared after careful removal of hetero atoms and water molecules and its electrostatic surface was generated.

Ligand Preparation
EBT (Ethanol extract of Bauhinia tomentosa) was subjected to GC-MS analysis to identify the bio constituents in earlier studies (3

Docking
MolDock scoring system is employed by MVD and it is based on a new hybrid search algorithm, called guided differential evolution. The guided differential evolution algorithm combines the differential evolution optimization technique with a cavity prediction algorithm. Differential evolution (DE) was introduced by Storn and Price in 1995 (4) and has previously been successfully applied to molecular docking. The use of predicted cavities during the search process, allows for a fast and accurate identification of potential binding modes (poses).
The intact protein structure was loaded on to MVD platform for docking process. Potential binding sites (also referred to as cavities or active sites) has been identified using the built-in cavity detection algorithm of MVD.
The search algorithm is taken as Moldock SE and numbers of runs are taken 10 and max iterations were 2000 with population size 50 with an energy threshold of 100. At each step least 'min' torsions/translations/rotations were tested and the one giving lowest energy was chosen. After the docking simulation was over, the poses which were generated were sorted by rerank score. The Rerank Score uses a weighted combination of the terms used by the MolDock score mixed with a few addition terms (the Rerank Score includes the Steric (by LJ12-6) terms which are Lennard-Jones approximations to the steric energythe MolDock score uses a piecewise linear potential to approximate the steric energy (5). The docking was subjected towards the amino acid residues which were found to be part of interaction between HTSPs and VOPs. The grid resolution was set at 0.3 Å. The maximum interaction was set at 1500 and maximum population size 50.

RESULTS
The GC-MS analysis of EBT identified 14 bioactive components. Out of 14 compounds, 8 compounds were found to have potential biological activity. Hence docking analysis of these 8 compounds was done in the present study. All the eight ligands were docked with these 6 proteins targets using MVD.

Docking with Caspase 3
The docking score and the rerank score of all the eight ligands for caspase 3 was shown in Table 3. It was found that phytol docks better than the other ligands based on the moldock and rerank score.

Docking with Caspase 9
The docking score and rerank score of all the 8 ligands for Caspase 9 was depicted in Table 4   The docking results for the selected ligands with Bcl 2 was shown in Table 5. The lead compound was found to be DL-Alpha tocopherol to dock with Bcl 2 with a least moldock score of -107.042. Inspite of having the least score it did not form hydrogen bonds with Bcl 2. The best docked compound with Bcl 2 was ethyl iso-allocholate. It has a least moldock and rerank score of -102.904 and -80.757 respectively. It forms 4 hydrogen bonds with Lys17, Met16, Glu13 and Arg12 (Figure 7.1 -7.3). The next hydrogen bond forming ligand was cholest-8-en-3-beta-OH acetate. It forms 2 hydrogen bonds with His 20 and Tyr 21 and has a moldock score of -98.4304 and rerank score of -62.5763. Though urs-12-n-28-ol, phytol and 1-octadecyne has appreciable docking score of around -101.973, -102.904 and -85.7513 respectively, they did not form any hydrogen bonds with Bcl 2. The remaining two ligands pentacosenoic acid and spirost-8-en-11-one has positive docking score of 2132 and 1667 respectively and it does not dock with the protein at all. Hence, it does not form any hydrogen bonds with Bcl 2.

Docking with BAX
The docking score and rerank score for all the eight ligands with BAX was summarized in The remaining two ligands namely spirost-8-en-11one, 3-OH-(3beta,5 Alpha,14 beta,20 beta,22 beta,25r) and pentacosenoic acid has positive moldock score and rerank score and hence they docked less with the protein target BAX.
Cholest-8-en-3-Beta-ol, acetate, Urs-12-en-28-ol and phytol also has appreciable docking score of -121.809, -112.703 and -105.542 respectively. But these compounds do not form any hydrogen bond with the BAX protein.   Table 7. Almost all the compounds were in the acceptable range of Lipinski's rule of five, indicating their potential for use as drug-like molecules (6).

DISCUSSION
Lung cancer is a malignant tumor characterized by uncontrolled cell growth in lung tissues. The major risk factor (85%) associated with its pathogenesis is tobacco smoking (7). About 10-15% is because of genetic factors and air pollution (8). Like other cancers, lung cancer is initiated by either the activation of oncogenes or the inactivation of tumor suppressor genes. Mutations of these genes by various carcinogens induce the development of cancer (9).
The genes like K-Ras and EGFR (Epidermal Growth Factor Receptor) plays an important role in lung carcinogenesis. Mutations in the K-Ras protooncogene causes about 10-30% of lung adenocarcinomas (10). Mutations in EGFR are common in non-small lung carcinoma and thus it provides the basis for treatment with EGFR inhibitors (11). Damage to Bcl2 gene has been identified as a cause for number of cancers including lung, breast, prostate, and melanoma cancer. It is also a cause of resistance to cancer treatments. Over expression of Bcl2 may increase the risk of cancer. The apoptotic regulator BAX induces apoptosis and hence drugs that activate BAX hold promise an anticancer treatment by inducing apoptosis in cancer cells. The caspases play an essential role in apoptosis. Caspases 3 and 9 are executioner and initiator of apoptosis respectively in humans and mouse (12). The deficiency or inactivation of these caspases has been identified as a cause for tumor development (13).
The present in silico molecular docking study was done to identify the lead compounds present in EBT. For the study, the 3D structures of these six proteins like EGFR, K-Ras, Caspase 3, Caspase 9, BAX and Bcl2 were downloaded from PDB database, and the docking was done by using MVD. When a ligand binds with a protein, it can either activate or inhibit the proteins. In the present study, the docking studies led to the identification of lead molecules which might play an important role in the activation or inhibition of the protein involved.
From the results, it was evident that proteins like EGFR, K-Ras and Bcl 2 were inhibited or inactivated upon binding with the lead ligands of EBT. Pro apoptotic proteins like BAX, Caspase 3 and Caspase 9 might be activated by the binding of lead molecules of EBT. Similar results have been observed by Gayathri Gunalan et al (14) in the docking studies of B. variegata secondary metabolites for anticancer activity.

CONCLUSION
The GC-MS analysis revealed the presence of fourteen secondary metabolites in ethanol extract of the leaves of B. tomentosa. Thus, the presence of various bioactive compounds justifies the use of the leaf for various ailments by traditional practitioners.
The docking studies revealed that the ligands either activate or inhibit the selected target proteins appropriately. However, isolation of individual secondary metabolites and subjecting it to elucidate their biological activity will be more beneficial. Thus, the ethanol extract of B. tomentosa has appreciable anti-cancer activity towards A549 cells.
Further separation and purification of individual ligands followed by various analyses might pave way for the identification of new anticancer drugs for the treatment of lung cancer.