Molecular Docking Studies of potential anticancer agents from Ocimum basilicum L. against human colorectal cancer regulating genes: An insilico approach

 

Balakrishnan Purushothaman^1,2*, Nagarasan Suganthi ², Arunachalam Jothi³, Kumaran Shanmugam¹

¹Department of Biotechnology, Periyar Maniammai Institute of Science and Technology, Thanjavur – 613403, Tamilnadu, India.

²Tan Bio R and D Solution, Periyar Technology Business Incubator, Vallam, Thanjavur – 613403, Tamilnadu, India.

³Department of Bioinformatics, School of Chemical and Biotechnology, SASTRA University,

Thanjavur – 613 401, Tamilnadu, India.

 

ABSTRACT:

Colorectal cancer (CRC) ranks third in cancer deaths all over the world. Mortality and incidence rates of CRC in India is constantly increasing due to change in food habits, life style etc., Ocimum basilicum has been reported for constituents like eugenol, germacrene, gurjunene, menthol and β-elemene with anticancer properties. As an initiative, these chemical constituents were studied against human colorectal biomarkers such as KRAS, NRAS, BRAF (Oncogenes); PIK3CA, P53, DCC (Tumor suppressor genes) through molecular docking. Autodock 4.2 software was used to understand the drug-biomolecular interactions; binding mechanism of drug (ligand) and receptor (target); binding energy and bond length. The mutant type proteins of these markers were analyzed with specific to their expression codons against these O. basilicum constituents. Our results revealed that constituents of O. basilicum have excellent binding energies against colorectal cancer genes.

 

 

 

INTRODUCTION:

Colorectal cancer is (CRC) one of the deadly diseases which ranks three for men and second for women among all cancers in the world and due to the 608000 deaths, it ranks fourth common cause of death^[1]. In India, CRC ranks 8^th in colon and 9^th in rectal cancer for men and 9^th in colon cancer for women^[2]. There are numerous research going on continuously but till now the molecule to eradicate cancer is yet to be identified.  Nowadays, cancer research focuses on the development of new approaches to eradicate cancer cells without affecting normal cells.

 

For this approach, we need the help of the drugs from natural products to treat cancer without affecting the normal cells^[3]. Among the natural sources drugs from the plants is the finest because of the low side effects, easy availability and cost-effective. The drugs form the plants have been used to treat various diseases and disorders for more than thousand year in the recorded human history.^[4]; this is because of the naturally occurring chemical constituents present in them. The major group of secondary metabolites like terpenoids, alkaloids, phenolics, and flavonoids have been reported for therapeutic activity like anticancer, anti-microbial, anti-diabetic, and anti-oxidant etc., and there are thousands of research evidence for the bioactivity of drugs from the plants^[5]. But the identification, extraction, and purification of the active ingredient from the plant are difficult. In order to eradicate such problems, computational biology can be a promising area.

 

Advancement of the computational biology, biological studies through the computational tools are nowadays increased, this is not only due to the cost-effective but also to speed up of the process^[6]. Finding the active ingredient/s (AI) from the plant is a tedious task, rational drug design (RDD) provides an alternative choice; but it involves in a number of methods, among that docking is one of the best methods because of the process of fitting of receptor and ligand in 3D space and finding the active site in it^[7]. In addition to that, the identification of the molecular bonding of ligand (API) and the receptor (Protein) plays a major role in the selection, extraction, and purification of the AI from the plant^[8]. There is a number of docking tools are available, Auto dock 4.2 is one of the most advanced automatic docking tools for grids generation, docking score calculation, and conformers evaluation^[9].

 

For the last few years, our research group has focused on the discovery of drugs from indigenous plants like Allium sativum^[10], Solanum trilobatum^[11], Adhatoda vasica^[12], Leucas aspera^[13], Nigella sativa^[14], Ficus racemosa^[15], and Eclipta alba^[16]. In the present study, we have focused on the lead optimization of the AI present in the Ocimum basilicum^[17] acting against the colorectal adenocarcinoma regulating genes using Auto Dock 4.2. Although, common cancer therapy research only concentrates on the regulating genes mysfunction and its ability to affect the molecular mechanisms. But, we focused on mutant codons in which these genes gets mutated, it might results on the enhanced cancer therapy by targeting only when the gene gets mutated.

 

MATERIALS AND METHODS:

Protein retrieval and preparation:

The X-ray 3D structures of colorectal biomarkers such as KRAS- G12D codon, NRAS- Q61K codon, BRAF- V600E codon (Oncogenes); PIK3CA- E545K codon, P53- R249S codon, DCC- T3151 codon (Tumor suppressor genes) were retrieved from Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank(PDB) (Table 1). Excess water molecules and chains were detached from the protein structure using Discovery studio visualizer. Hydrogen bonds, polar bonds, kollaman charges are added using Autodocktools and docking parameters are generated.

 

Table 1: PDB ID’s of colorectal cancer biomarkers with expression codons.

S.NO	Genes	Mutant codon	PDB ID Name
1.	KRAS	G12D	5US4
2.	NRAS	Q61K	2RGB
3.	BRAF	V600E	4R5Y
4.	PIK3CA	E545K	4QPS
5.	P53	R249S	3D05
6.	DCC	T3151	3QRJ

 

Ligand retrieval and preparation:

The 3D conformers of lead Ocimum basilicum leaf essential oil compounds such as eugenol, germacrene, gurjunene, menthol and β-elemene were retrieved from PubChem. Torsion tree root was detected and the number of torsions was set at 1-6, aromaticity criterion added and the cutoff angle was set at 7.5 using Auto Dock tools and docking parameters are generated (Table 2).

 

Molecular docking:

PDBQT files, docking parameter files and grid parameter files were generated by setting grid box dimension as 60x60x60. Default parameters were set and no. of runs were set as 10. LamarckianGA(4.2) genetic algorithm was used throughout the docking procedure. Cygwin was used for the molecular docking coding and binding energies was evaluated for all the 10 runs. Binding interactions also include polar bonds, hydrogen bonds (H-bond), van der Waals force (vdW) and electrostatic interactions. Binding energies represents the possibilities of ligand interaction with the receptor protein. i.e, the interaction between the ligand atom and the receptor amino acid residue^[18].

 

Table 2: PubChem ID's of Ocimum basilicum chemical constituents.

 

RESULTS AND DISCUSSION:

Table 3: Binding energies of eugenol against colorectal cancer biomarkers.

                                              a)                                                    b)                                                             c)

Fig 1: the Docked complex of eugenol against colorectal cancer biomarkers– BRAF (a), NRAS (b), P53 (c)

 

                    a)                                                                                                   b)

c)                                                                                                                           d)

Fig 2: The Docked complex of Germacrene against colorectal cancer biomarkers – a) BRAF, b) KRAS, c) NRAS, d) DCC

 

Table 4: Binding energies of Germacrene against colorectal cancer biomarkers.

S. No	Mutant codon receptor	Binding energy
1.	BRAF- V600E	-6.55
2.	KRAS - G12D	-6.03
3.	NRAS- Q61K	-6.69
4.	PIK3CA- E545K	-2.05
5.	DCC- T3151	-6.88
6.	P53- R249S	-4.16

 

Table 5: Binding energies of Gurjunene against colorectal cancer biomarkers.

S. No	Mutant codon receptor	Binding energy
1.	BRAF- V600E	-6.67
2.	KRAS - G12D	-5.34
3.	NRAS- Q61K	-5.70
4.	PIK3CA- E545K	-4.93
5.	DCC- T3151	-7.17
6.	P53- R249S	-4.65

Table 6: Binding energies of Menthol against colorectal cancer biomarkers.

S. No	Mutant codon receptor	Binding energy
1.	BRAF- V600E	-6.33
2.	KRAS - G12D	-6.29
3.	NRAS- Q61K	-7.47
4.	PIK3CA- E545K	-4.49
5.	DCC- T3151	-6.11
6.	P53- R249S	-7.93

 

Table 7: Binding energies of β- elemene against colorectal cancer biomarkers.

S. No	Mutant codon receptor	Binding energy
1.	BRAF- V600E	-6.64
2.	KRAS - G12D	-3.34
3.	NRAS- Q61K	-7.60
4.	PIK3CA- E545K	-4.23
5.	DCC- T3151	-6.75
6.	P53- R249S	-3.66

 

a)                                                                                                                   b)

Fig 3: The Docked complex of Gurjunene against colorectal cancer biomarkers – a) BRAF, b) DCC

 

a)                                                                             b)                                                                             c)

d)                                                                                                                 e)

Fig 4: The Docked complex of Menthol against colorectal cancer biomarkers – a) BRAF, b) KRAS, c) NRAS, d) DCC, e) P53

 

a)                                                                             b)                                                                                     c)

Fig 5: The Docked complex of β- elemene against colorectal cancer biomarkers – a) BRAF, b) NRAS, c) DCC

 

All the retrieved chemical constituents were evaluated to determine its ability to interact with colorectal cancer mutant codon genes namely KRAS, NRAS, BRAF (Oncogenes), PIK3CA, P53, DCC (Tumor suppressor genes) in respect to high affinity using Autodock 4.2 software. The interacted complexes showed good binding energy and strong affinities. Total interaction energy comprises all interactions such as H-bonds, van der Waals force (vdW), polar bonds and electrostatic interactions. The mean binding energies of O. basilicum chemical constituents against human colorectal cancer regulating genes were tabulated in the above tables (Table: 3-7) and the docked complex (binding energy ranging below -5, i.e. below -5 represents strong affinity) were shown in Fig: 1-5. These results represent that all the selected five constituents have a potent effect on CRC genes with least binding energies (i. e, a suitable drug for that target protein). The total free binding energy was calculated by the formula,

 

Free Energy of Binding (kcal/mol) = Final Intermolecular Energy + Final Total Internal Energy

+Torsional Free Energy - Unbound System's Energy

 

CONCLUSION:

This study reveals that the studied compounds from the Ocimum basilicum L. leaves have strong anticancer potential against colorectal cancer mutant codon genes. BRAF- V600E codon mutant (oncogene) highly inactivated by all the chemical constituents with strong binding affinities. Moreover, all the chemical constituents have good binding energies against CRC mutant type genes. Detailed invitro and in vivo screenings have to be done for the better improvement of treating colorectal cancer carcinogenesis.

 

CONFLICT OF INTEREST:

There is no conflict of interest among the authors.

 

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Received on 28.02.2019           Modified on 15.03.2019

Accepted on 05.04.2019         © RJPT All right reserved