Repurposing statins as a potential ligand for estrogen receptor alpha via molecular docking

Khandelwal Alisha, Sharma Tripti

School of Pharmaceutical Sciences, Siksha ‘O’ Anusandhan Deemed to be University,

Bhubaneswar - 751003, Odisha, India.

*Corresponding Author E-mail: triptisharma@soa.ac.in

ABSTRACT:

Computational drug repurposing is the strategy for drug development which remarkably reduces the cost and development time. Research suggests that breast cancer development in women have been associated with cholesterol and its transporters. Cholesterol lowering drugs can be repurposed as potential therapeutic agents to prevent high cholesterol in estrogen receptor positive- breast cancer. The objective of this study was to carryout in-silico molecular docking of HMG-CoA reductase inhibitors (statins) with estrogen α receptor (3ERT) to repurpose the statins as breast cancer inhibitors. Molecular docking studies were performed to explore the mechanism of interactions between the statins and human estrogen α receptor. Docking results revealed that statins bind to the hydrophobic pocket of the estrogen α receptor with high binding affinity. The docking scores were compared with the standard drug 4- hydroxy tamoxifen. The study helped to compare the interactions amongst different statins with the receptor and the energy values produced were ranging from -8.5 to -5.5 kcal/mol. Molinspiration web servers was used to calculate the physiochemical properties and ADMET of the statins. Simvastatin showed better interaction amongst the docked statins with best protein ligand interactions, it was found to exhibit higher docking score of -8.5 kcal/mol. Therefore, we conclude that statins can be employed as an alternative drug for treatment of breast cancer.

KEYWORDS: Molecular docking, HMG-CoA reductase inhibitors, Estrogen α receptor, Breast cancer.

INTRODUCTION:

Breast cancer is the second most prevalent malignancy in women around the world. According to 2019 breast cancer statistics report more than 2,68,600 new cases of breast cancer were diagnosed in women¹. Steroid hormone estrogen or 17β-estradiol is responsible for development of mammary gland and is one of the major risk factor for breast cancer. Estrogen receptor alpha (ERα) is target for ER-positive breast cancer and about 70% of breast cancer expresses ERα receptor².

Statins reduces blood cholesterol by competitive inhibition of HMG-CoA reductase, the rate limiting step in the mevalonate pathway³. Apart from lipid lowering effects, statins also produce vasoprotective and cardioprotective effects⁴.

Statins are reported to reduce tumor cell growth and proliferation by inducing cell cycle arrest, inducing apoptosis and by negative impact on the tumor vasculature through suppression of angiogenesis⁵. Many clinical studies have demonstrated influence of statins on liver cancer⁶, colorectal⁷, lungs^8,9, prostate^10,11,12 and breast cancer^13,14,15.

Drug repurposing is a drug discovery strategy for identification of a novel clinical use for an existing, approved or investigational drug. Since most of the drug interacts with multiple targets, these interactions could result in toxicities or side effects. The resulting side effects can be a new medical indication of the drug and used for treating other diseases¹⁶. The objective of this study was to evaluate the binding interactions of statins against ERα receptor through molecular docking.

MATERIAL AND METHODS:

Retrieval of target protein:

The X-ray crystal structure of human estrogen alpha receptor complex with 4-hydroxytamoxifen (4-HT) (PDBID:3ERT) at 1.9Å resolution was retrieved from protein data bank (PDB) (https://www.rcsb.org/structure/3ert¹⁷. WHATIF server was used to repair the protein 3ERT. Hydrophobicity graphs were generated by Discovery Studio. Binding site analysis of 3ERT was performed using CASTp web server¹⁸.

Retrieval of ligands:

3D structures of eight statins Lovastatin (LS), Simvastatin (SS), Atorvastatin (AS), Pitavastatin (PTS), Cerivastatin (CS), Fluvastatin (FS), Rosuvastatin (RS), Pravastatin (PS) and standard drug 4-HT were retrieved from NCBI Pubchem compounds in SDF format and saved as mol file using Marvinsketch. (Table -1). ADMET properties of the selected compounds were predicted by molinspiration webserver.

Molecular docking:

Molecular docking of the ligands to the active binding site of the protein was performed using Autodock vina in PyRx virtual screening tool [19,20]. Protein pdb file (3ERT.pdb) was converted to pdbqt format file (3ERT.pdbqt) by removing water, adding hydrogen atom, kollman charges to the protein. The grid centre was positioned on the active site of the receptor 3ERT. The grid point for autogrid calculation was set to be X= 22.56, Y=-5.40, Z=21.93 with active site residue at the centre of the grid box. The Lamarckian Genetic Algorithm (LGA) was used to run docking simulations. Nine best poses are generated in the library after running vina wizard for selected 3ERT protein with each prepared ligand concurrently. The scoring, based on the docked energy of all the ligands were ranked version and the docking score obtained were then compared with 4-HT (Table 2). The ligands and protein were then submitted to swissdock for redocking. Protein ligand interactions were analyzed by Discovery Studio 4.5 and Chimera.

RESULTS AND DISCUSSIONS:

All the statins were found to strongly inhibit by occupying the active sites in the target protein 3ERT.

(e)

(d)

Table 1: 2D Structure of HMG-CoA reductase inhibitors (statins)

Sr. No	Compounds	Compound CID	2-D structure
Sr. No	Compounds	Compound CID	2-D structure
1	Lovastatin	53232
2	Simvastatin	54454
3	Atorvastatin	60823
4	Pitavastatin	5282452
5	Cerivastatin	446156
6	Fluvastatin	446155
7	Rosuvastatin	446157
8	Pravastatin	54687

Table 2: List of docking interactions between the ligands

Compound names	Docking score (Pyrx) (kcal mol^-1)	Re docking (swissdock) (kcal mol^-1)	Interacting residues
Lovastatin (LS)	-6.7	-8.49	Met 343, Leu 387, Met 388, Trp 383, Arg 394, Met 421, Leu 525.
Simvastatin (SS)	-8.5	-9.36	Leu 346, Met 388, Arg 394, Met 421, Ile 424, Leu 525.
Atrovastatin (AS)	-5.7	-7.89	Ile 326, Pro 406, Trp 393, Glu 322, Gly 390, Arg 394, Pro 324, Glu 442.
Pitavastatin (PTS)	-5.9	-7.71	Glu 323, Ile 326, Glu 353, Trp 393, Arg 394, Glu397, Pro 406, Phe 445, Lys 449.
Cerivastatin (CS)	-5.5	-7.32	Glu 323, Pro 324, Pro 325, Ile 326, Trp 393, Arg 394.
Fluvastatin (FS)	-6.9	-8.08	Met343, Ala 350, Glu353, Leu387, Leu 525
Rosuvastatins (RS)	-5.7	-7.26	Glu 323, Glu 353, Arg 394, Trp 393, Lys 449, Pro, Ile 326, Glu 397
Pravastatin (PS)	-6.9	-8.47	Leu 346, Met388, Arg394, Glu 353, Phe 404, Met 421, Leu 525
Tamoxifen	-9.0	-10.23	Ala45, Asp 46, Leu 49, Trp 78, Leu 220, Tyr 221, Lys 224, Cys 225, Val 228, Leu 231, Leu 234

Table 3: Drug likeness property (Lipinski’s rule of five) of statin

Compound names	Lipinski’s Properties					LV	MR	TPSA(Å)	%ABS
Compound names	HBD (≤10)	HBA (≤10)	MW (g/Mol) (≤ 500 g/mol)	logP (≤5)	n	LV	MR	TPSA(Å)	%ABS
Lovastatin (LS)	1	5	404.55	4.34	7	0	113.92	72.84	83.87
Simvastatin (SS)	1	5	404.55	4.52	7	0	116.05	72.84	83.87
Atrovastatins (AS)	4	7	560.67	4.91	12	1	164.63	110.09	71.03
Pitavastatin (PTS)	3	5	421.47	3.91	8	0	117.82	90.65	77.72
Cerivastatin (CS)	3	6	459.56	4.45	11	0	127.82	99.88	74.54
Fluvastatin (FS)	2	4	409.50	4.44	8	0	119.66	62.46	87.45
Rosuvastatins (RS)	4	10	483.52	0.64	10	0	119.75	161.15	53.40
Pravastatin (PS)	4	7	424.53	2.15	11	0	114.04	124.29	66.12
Tamoxifen(4HT)	0	2	371.52	6.06	8	1	119.72	12.47	104.69

Statins interacts with the amino acid residue of the protein by hydrogen bonding, vanderwaal interactions and π-alkyl interactions. Statins are reported to affect tumor cells directly by suppressing cancer proliferation, inducing apoptosis, antiangiogenic effects, anti-invasive and anti-metastaic effect. Lipophilic, high potency statins are found to be more effective at suppressing tumor cell growth²¹. This difference in antitumor activity of the statins may be accounted due to the difference in their physiochemical properties; lipophillic statins are more likely to cross the cellular membrane and hence more active. Statins are also found to enhance caspase 3 like activity and DNA fragmentation in MCF-7 cells leading to inhibition of proliferation of the cells²².

CONCLUSION:

Estrogen plays vital role in breast cancer development and estrogen receptor α is mainly responsible for breast cancer initiation and progression. There is a need for promising strategies for the design and synthesis of new therapeutic ligands which could selectively bind and inhibit estrogen dependent proliferation in estrogen α receptor. In this study we applied drug repurposing approach to find new ligands against estrogen α receptor, which can minimize the cost and risk associated in the development of new chemical entity. Lipophillic statins are found to be more active than hydrophilic statins.

According to the results obtained anti-cancerous drug 4-HT can be replaced by lipophilic statin SS due to least binding energy and higher absorption as compared to other statins. Lead modification of SS can be performed by bio-isosteric replacements and scaffold hopping. Further this needs proper investigation through experimental activity in an MCF-7 cell line to confirm the role of SS against breast cancer.

ACKNOWLEDGEMENT:

Authors are grateful to Dr. S.C. Si Dean SPS, for encouragements. Special thanks are due to honorable President, Prof. M.R. Nayak of the University for providing necessary facilities.

CONFLICT OF INTEREST:

The author(s) declares no conflicts of interest.

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Received on 12.04.2020 Modified on 08.06.2020

Research J. Pharm. and Tech. 2021; 14(7):3757-3762.

DOI: 10.52711/0974-360X.2021.00650