Most common malignancy faced by women around the world today is breast cancer. Estrogen receptor alpha has been identified and play a major role in stimulating the growth of breast cancer. So in the present analysis, our focus has been on natural compounds which do not exhibit any toxicity and have significant estrogen receptor alpha inhibition activity. Several reports proposed that polyphenolic chemicals present in many plant foods, and hence these compounds have several chemo preventive properties against breast cancer. So by using molecular docking, we screened the selected natural compounds and investigated their binding affinity against the selected protein. As a result, we predict the novel therapeutic inhibitors against estrogen receptor alpha for the treatment of breast cancer.
Keywords: Breast cancer; Estrogen receptor alpha; In-Silico; Docking-virtual screening; ADMET
Breast cancer is the well-known cancer type caused to the females around the world and it constitutes the major cause of mortality in several developing countries including India. Present day‟s breast cancer is a rising public health problem [1-3]. General risk factors for breast cancer include age, hereditary, diet, family history, heavy drinking, lack of exercise, radiation exposure, life style etc [4]. Estimated new cases of breast cancer in the United States for the year 2017 is 252,710 while recorded breast cancer deaths are 40,610 [5]. More economically developed and industrialized countries, and the economical fatality differentials have been deliberate extensively screening, and low developing countries suffer the highest mortality victims as a cause of breast cancer [6]. So overall an expected 14 million new breast cancer cases occur each year [7]. Based on the above reports the life style changes are the major factors to the development of breast cancer [8]. Daily intake of fruits and raw vegetables, which are rich in antioxidants, can decrease the risk of cancer [9].
Estrogen exposure is the major risk factor for breast cancer, so overall 50-60%of breast cancers are estrogen receptor (ER) positive. Generally, estrogen is a female sex hormone and it is important for reproductive development [10-12]. The estrogen receptor originates in two subtypes: Estrogen receptor alpha (ERα) and Estrogen receptor beta (ERβ). ER alpha is mainly present in the mammary gland [13]. The targeted therapeutics of estrogen receptor has clearly been success in the medication of breast cancer [14]. Therefore the prediction of possible estrogen receptor positive drug plays a very crucial role in the future appliance. In this present analysis, our research found out the appropriate natural products with the high binding affinity with the breast cancer target protein and which can be used for the treatment of breast cancer. Natural plant products have been used to prevent various diseases and these bioactive compounds can be proved and play a positive role to decrease the breast cancer risk [15]. The most important and useful Isoflavone are genistein and it is first discovered in 1899 [16]. Genistein acts as a chemotherapeutic agent against various types of cancers and it is a major flavonoid found in legumes, particularly soya beans and soya products like textured vegetables. Isoflavones as a good therapeutic option in breast cancer chemoprevention [17]. Genistein derivatives have excellent anti-cancer isoflavone agents against breast cancer. The selected analogues have outstanding antitumor activity and good pharmacokinetic and ADMET properties. Based on its properties, these natural compounds were chosen for our study. And we aimed to predict the best inhibitors by using insilico screening and analysis of molecular docking against the active site of
The three-dimensional structure of Human estrogen receptor alpha (figure 1) with PDB: 3ERT for docking studies was selected from the protein data bank [18] (http://www.rcsb.org/pdb) serves as a target model for screening. The complexes bound to the protein molecule, the water molecules and all the heteroatoms were removed, that are not needed for docking. Hydrogen atoms were added for the receptor structure.
For screening the compounds PubChem database was used. The PubChem database is a public open repository for the biological activity of small molecules. The chemicals structures were downloaded in SDF (structure data format) from PubChem database (http://www.pubchem.ncbi.nlm.nih.gov). The chemical structure of ligand is shown in figure 2. A total of 18 compounds were selected for docking studies all the selected compounds can show inhibitory effects towards
Molecular docking is one the most important method in structure based drug design. Docking was performed using Auto dock Vina in PyRx interface, an open source software [20]. The grid box was generated around the active site residues with grid center, X-Axis - 22.396 Å,Y-Axis – 5.6441 Å, Z-Axis – 21.9877Å and grid dimensions x – 48.25 Å, y - 55.54 Å, z-56.032.Å.
Lipinski‟s rule of five also called as Pfizers‟s rule of five to evaluate the drug likeness, the rule was prepared methodically by Christopher A. Lipinski in 1997 [21]. As per “Rule of 5”, the drug-like molecules have the number of hydrogen bond acceptors ≤10, number of hydrogen bond donor‟s is not more than 5, Partition coefficient log P less than (≤5) and molecular mass less than 500 daltons [22]. The pharmacokinetic properties and ADMET (absorption, distribution, metabolism, elimination, toxicity) analysis were predicted using insilico methods. In this study Data Warrior is used for the calculation of drug-likeness and ADMET analysis. (http://www.openmolecules.org/datawarrior). Data Warrior is an open source visualization and data analysis program. It is a versatile tool and it calculates the various physicochemical properties directly from chemical structures [23].
Human estrogen receptor alpha has been used as an important therapeutic target for Breast Cancer. The 3- Dimensional Structure of Human estrogen receptor alpha retrieved from Protein Data Bank PDB Code: 3ERT determined by X-Ray crystallography at a resolution of 1.90Å as shown in figure 1.
The selected compounds were tested for „rule of 5‟the results showed that all the compounds can satisfy Lipinski rule. The toxicity prediction and pharmacokinetic properties were predicted among all the 18 Compounds using Data Warrior. The data warrior results of toxicity analysis and pharmacokinetic properties were shown in table 1. The log P values and solubility were calculated for pharmacokinetic properties while mutagenicity, tumorigenicity, reproductive effect and irritation effect were predicted for Toxicity analysis. The results revealed that poor solubility is accompanying with bad absorption, and aqueous solubility substantially affects the absorption and distribution characteristics. The Data Warrior results displayed that among 18 compounds, PubChem CID: 5393152, CID: 5280863, CID: 5280443, CID: 11987653, have high mutagenic action, and five compounds i.e., CID:3764, CID: 10062691, CID: 656936, CID: 11987653, CID: 254171 showed high reproductive effect. Based on the results from data warrior the selected 18 compounds is predicted to have better log P, and good drug-likeness and less toxicity parameters as illustrate table 1.
PubChem Total C log P C log S H- H- ligand Id molecular acceptors donors 5284648 270.239 1.6272 -2.727 5 3 10062691 272.255 2.3791 -2.889 5 3 25271556 250.304 2.7827 -5.491 4 2 656936 226.230 3.17 -3.961 3 2 688857 240.257 2.8471 -3.232 3 1 5320693 268.267 2.9571 -3.466 4 1 5393152 254.240 2.5273 -3.379 4 2 5280863 286.238 1.8359 -2.787 6 4 439246 272.255 2.1557 -2.64 5 3 5391140 254.240 2.6814 -3.152 4 2 5281607 254.240 2.6814 -3.152 4 2 114829 256.256 2.5014 -2.936 4 2 5280443 270.239 2.3357 -2.856 5 3 3764 268.267 2.2486 -3.337 4 1 44201362 250.304 2.7827 -5.491 4 2 11987653 274.271 1.6034 -3.021 5 3 5280373 284.266 1.9029 -3.041 5 2 254171 224.211 0.7476 -2.037 5 2 Drug Mutagenic Tumorigenic Reproductive Irritant
In this regard, we identified four PubChem compounds i.e., PubChem CID: 25271556, CID: 5284648, CID: 5320693, CID: 5391140 might be chosen as new inhibitors for estrogen receptor alpha and these four compounds having anti-cancer properties and have the high estrogen receptor binding capability. The structural analogues of the above mentioned compound CID: 5284648 having good binding energy value is -8.9 kcal/mol. This was shown interacts with Arg394, Glu353. CID: 25271556 contain binding energy value is -8.6 kcal/mol this was shown interact with His 524, Gly 420. CID: 5320693 contain binding energy value is -8.4 kcal/mol, this compound was found to interact with Arg 394, Glu 353. CID: 5391140 contain binding energy value is -8.2 kcal/mol this compound was found to interact with Arg 394 results will be elucidated in table 2 and the receptor and ligand interactions as shown in figure 3. These results may be used for generation of novel drugs against estrogen receptor alpha.
In conclusion, we suggested novel therapeutic inhibitors by using a computational method structured based virtual screening, Molecular docking. The receptor-ligand interactions play a very prominent role in Drug energy value we chosen the best ligand-receptor interactions. Protein for human estrogen alpha has been taken, and new potential drugs have been recognized and these newly identified drugs can be used against Breast cancer. Pharmacokinetic properties and toxicity analysis calculated in Data warrior, most of these compounds are not suitable as drug candidates. Finally four compounds i.e., PubChemCID: 5284648, CID: 25271556, CID: 5320693 and CID: 5391140shows good binding energies and in ADMET analysis these analogues have excellent pharmacokinetic and drug-likeness properties. Hence, these four compounds having anti-cancer activity and these analogues could be used for designing therapeutic lead molecules. Further analysis is needed to investigate the interactions of the above selected ligands with estrogen receptor alpha can be used for in vivo and in vitro experiments.
MK is thankful to university grants commission, New Delhi for financial support in the form of UGC– BSR (RFSMS) Senior Research Fellowship. Y.S. is thankful to Human Resource Development for Health Research, New Delhi (F.No.V.25011/542-HRD/2016-HR).
The authors declare that they have no competing interests.