Garlic phytocompounds possess anticancer activity by specifically targeting breast cancer biomarkers—an in silico study

Tags: Asian Pac J Cancer Prev, AR, breast cancer, nuclear receptors, Cancer, drug discovery, glucocorticoid receptor, androgen receptor, molecular docking, Mol Endocrinol, target proteins, hydrogen bond, BC target proteins, CDOCKER interaction energy, active sites, Nucleic Acids Res, plasma protein binding, compounds, biomarkers, active site, Garlic, Asian Pacific Journal of Cancer Prevention, SAC, Chinese herbal medicines, Mackerell AD, Jr., prostate cancer, Endocrinol, Int J Cancer, J Ethnopharmacol, FALSE FALSE FALSE, J Mol Endocrinol, J Comput Chem, FALSE FALSE FALSE FALSE FALSE FALSE, Preparation, target, stable conformation, potential energy, SACS, allyl compounds, functional residues, FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE, TRUE FALSE FALSE, PDB, binding energy, binding energies, FALSE FALSE, Khalid N, Sangeetha Davis1, 2Amala Cancer Research Centre, mineralocorticoid receptor, progesterone receptor, Kerala Agricultural University, Protein Data Bank, lung cancer, cancer in women, potent compounds, Isobutyl isothiocyanate, Advanced Drug Delivery Reviews, Smith DA, Accelrys Discovery Studio, Kerns EH, ACS Medicinal Chemistry Letters, Epithelial-Mesenchymal Transition, Therapeutic Target, Plant Biotechnology, Cold Spring Harbor, Di L
Content: DOI: Garlic Phytocompounds Possess Anticancer Activity by Specifically Targeting Breast Cancer Biomarkers -an in Silico Study RESEARCH ARTICLE
Garlic Phytocompounds Possess Anticancer Activity by Specifically Targeting Breast Cancer Biomarkers - an in Silico Study Nabarun Roy1*, Sangeetha Davis1, Arunaksharan Narayanankutty2, PA Nazeem1, TD Babu2, PS Abida3, PA Valsala3, Achuthan C Raghavamenon2
Abstract Background: Breast cancer (BC) is a serious lifestyle disease. There are several prognostic biomarkers like nuclear receptors whose over-expression is associated with BC characteristics. These biomarkers can be blocked by compounds with anti-cancer potential but selection must be made on the basis of no adverse side effects. This study is focused on finding of compounds from a plant source garlic. Materials and Methods: Twenty compounds from garlic and five targets considered involved in BC were retrieved from Pubchem database and Protein Data Bank respectively. They were docked using Accelrys Discovery Studio (DS) 4.0. The compounds which showed interaction were checked for drug likeliness. Results: Docking studies and ADMET evaluation revealed twelve compounds to be active against the targets. All the compounds displayed highly negative dock scores which indicated good interactions. Conclusions: The results of this study should help researchers and scientists in the pharmaceutical field to identify drugs based on garlic. Keywords: Breast cancer - nuclear receptor - garlic - discovery studio - docking - ADMET
Asian Pac J Cancer Prev, 17 (6), 2501-2506
Introduction According to World Health Organization (WHO), Breast Cancer (BC) is the most leading cancer in women all over the world (Benson and Jatoi, 2012; Dubey et al., 2015). According to GLOBOCAN report (2012), around 1.67 million cases of BC were reported and it is the second most diagnosed after lung cancer (Ferlay, 2015). In India, BC is the most common type of cancer in women of the urban cities of Delhi, Mumbai, Ahmedabad, Kolkata, and Trivandrum, where over 100,000 new BC cases are diagnosed annually (Khokhar, 2012). The use of biomarkers in this field have relatively helped to understand disease biology and is currently used in clinical practice. BC is generally a hormone dependent cancer, because of the involvement of sex steroid hormones such as estrogen and progesterone and also their respective nuclear receptors (NR) such as estrogen receptor (ER) and progesterone receptor (PR), which are the most important biomarkers for BC (Sever and Glass, 2013; Higa and Fell, 2013; Omoto and Iwase, 2015). There are other NRs which also lead to BC such as androgen receptor (AR), glucocorticoid receptor (GR) and mineralocorticoid receptor (MR) (Xu, 2015; Voutsadakis, 2016). AR is
expressed in 89% of ER positive BC cases (Conzen, 2008; Garay and Park, 2012). GR is expressed in about 60% of BC and gets associated with 70% of ER positive tumors (Abduljabbar et al., 2015; Kach et al., 2015). Sometimes, MR may replace GR in terms of the laters' activity because of similar structures of both the two (Kingsley et al., 2002; Leo et al., 2004). These biomarkers in total are the prognostic factors which led to the detection and diagnosis of BC. There is always a demand for herbal drugs in the market as they display low side effects, as compared to commercially available drugs. Garlic (Allium sativum L.) is a herbal crop containing compounds with medicinal properties, and is in discussion for decades for its usefulness in curing cancer, diabetes, blood pressure etc (Suleria et al., 2015). Huang et al. (2015) observed the antitumor effect of garlic compound on human triplenegative BC cells. In some other in vitro studies, garlic compounds and extract was found to inhibit human BC cell lines MCF-7 and MDA-MB-231 in a dose and time dependent manner by inducing cell cycle arrest and apoptosis (Ghazanfari et al., 2011; Tsubura et al., 2011; Modem et al., 2012; Zhang et al., 2014; Bagul et al., 2015). As the clinical study of all these compounds is time consuming, so in this study, an in silico tool `molecular
1Distributed Information Centre, 3Centre for Plant Biotechnology and Molecular Biology, Kerala Agricultural University, 2Amala Cancer Research Centre, Thrissur, Kerala, India *For correspondence: [email protected]
Asian Pacific Journal of Cancer Prevention, Vol 17, 2016 2501
Nabarun Roy et al
docking' was used to predict the binding mode and efficiency of garlic compounds with the targets of BC. Molecular docking is an efficient bioinformatics technique which can be used for finding out potent compounds acting against specific targets/ biomarkers of specific disease, without spending much time as like in a normal drug discovery pipeline (Ferreira et al., 2015). Materials and Methods Identification and retrieval of phytocompounds /ligands Identification of phytocompounds from garlic was done from Dr. Duke's database (http://www.ars-grin. gov/duke/) containing facts on the medicinal activity of phytocompounds in humans (Barlow et al., 2012). Three dimensional structure of identified twenty compounds were retrieved from PubChem database (https://pubchem. as ligands in .sdf format (Kim et al., 2016). Preparation of ligands and their filtration Preparation of the retrieved compounds/ ligands was done using `Prepare ligand' protocol in DS 4.0, which removed duplicates, enumerated tautomers/isomers, added hydrogen bonds and minimized energy using CHARMm (Chemistry at Harvard Macromolecular Mechanics) force field (Brooks et al., 2009). The prepared ligands were filtered by Lipinski's Rule of five and Vebers' protocol (Ro5 & VP) that sets the criteria for drug like properties and focuses on drugs' bioavailability (Veber et al., 2002; Lipinski, 2004). Ro5 & VP was used to screen the compounds on the basis of molecular weight (MW, 500 daltons), no. of hydrogen bond donors (HBD, 5) and hydrogen bond acceptors (HBA, 10), no. of rotatable bonds (RB, 10), logP value (5) and polar surface area (PSA, 140 Е2). The filtered ligands were then forwarded for molecular docking with BC target proteins. Target protein identification and retrieval Successful molecular target proteins involved in BC metastasis, such as ER, PR, AR, GR and MR were selected from Therapeutic Target Database (TTD- http://bidd.nus. and Potential Drug Target Database (PDTD- for purpose of molecular docking studies (Qin et al., 2014; Chen et al., 2015). Their three dimensional X ray crystallographic structures were downloaded from Protein Data Bank (PDB- and saved in .pdb format (Rose et al., 2015). All the structures were selected on the basis of the presence of one or more active site for binding with ligands and high active side residue count. The PDB IDs of the retrieved targets were 1ERR (ER), 3D90 (PR), 1E3G (AR), 1M2Z (GR) and 2AB2 (MR). Preparation of protein molecules and active site identification `Prepare protein' protocol of DS 4.0 corrected the Protein Structures by inserting missing atoms, adding hydrogen atoms, modelling loop regions and side chains, removing water molecules, natural ligands and
hetero atoms and minimizing energy to avail a stable conformation by using CHARMm forcefield. The energy minimized structure was used as the template for molecular docking. `PDB site records' of DS 4.0 were used to identify the active sites. This method look for poseview software molecular interactions of protein target Crystal Structure and inhibitor displayed in PDB (Stierand and Rarey, 2010). A grid receptor sphere was generated, including the selected binding active site and incorporating all the critical functional residues. Molecular interaction and binding Molecular docking was performed between the prepared BC target proteins and identified garlic phytocompounds by `CDOCKER' protocol of DS 4.0. (Wu et al., 2003). The pose which contained the least difference between CDOCKER energy and CDOCKER interaction energy was considered as best interaction, along with the lowest binding energy calculation as the scoring function (Oda et al., 2007). Number of hydrogen bonds between the targets and the ligands were also recorded. The optimal distance between two atoms connected by a hydrogen bond is set to 1.9 Е with a tolerance of 0.5 Е (Stierand and Rarey, 2010). Pharmacokinetic evaluation In silico tool `ADMET descriptors' provided by DS 4.0 can help in the evaluation of pharmacokinetic parameters and assess the quality of the molecule in terms of absorption, distribution, metabolism, excretion and toxicity after human ingestion (Tian et al., 2015). This technique reduces the cost and chance of clinical failures of new drugs. The parameters calculated by this descriptor included human intestinal absorption, aqueous solubility, blood brain barrier (BBB), hepatotoxity, CYP2D6 inhibition and plasma protein binding (PPB) (Usha et al., 2014). Results and Discussion Preparation of garlic compounds and BC target proteins The garlic compounds (allyl compounds and flavonoids) which were used for the in silico study are enlisted in Table 1. After preparation, all the ligands were subjected to filtation by Ro5 & VP, where none of them violated the rule. However, compounds such as L--Glutamyl-S-allyl-L-cysteine (GSAC) and myricetin were found to possess a PSA higher than 140 Е2, which indicated low absorption and poor permeability of the molecule across cell membranes. Preparation of the target proteins led to removal of all the non-standard residues from the structures. The potential energy, Vander-Waals energy and electrostatic energy were reduced, when the protein structures were subjected to energy minimization. Many active sites were found present in the crystallographic structures, out of which the best active site was selected looking at the PDB site records for preparing the receptor grid. The energy minimized stable (prepared) structure of PR along with its unprepared 3D structure is shown in Figure 1a and 1b.
2502 Asian Pacific Journal of Cancer Prevention, Vol 17, 2016
DOI: Garlic Phytocompounds Possess Anticancer Activity by Specifically Targeting Breast Cancer Biomarkers -an in Silico Study
Binding ability of garlic compounds with BC target proteins Twelve compounds from garlic showed good interaction with the BC targets (Table 2). A very less difference was found between CDOCKER and CDOCKER interaction energy (around 2 Kcal/mol). The binding energies of the compounds from garlic with the BC targets was found to be ranging from -66.84 Kcal/mol to -168.57 Kcal/mol. The lowest score (-168.57 Kcal/mol)
was shown by kaempferol while interacting with PR at the residues GLN725, ARG766 and CYS891 of active site 1 with hydrogen bond lenghts 2.2 Е, 1.7 Е and 2.4 Е respectively (Figure 2). PR is an NR, the alteration of functions of which lead to co-expression with ER and lead to dangerous forms of BC (Diep et al., 2015). ER is the most important prognostic biomarker in BC
Fig 1(a)
Fig 1(b)
Fig 1(a) Figure 1. a): 3D Structure of Progesterone Receptor (b): Prepared Structure of Progesterone Receptor Protein Ready for Docking
Figure 3. Interaction of Garlic Compound Taurine with Active Site Residues of Estrogen Receptor
Figure 2. Interaction of Garlic Compound Kaempferol Figure 4. Interaction of Garlic compound SACS with with Active Site Residues of Progesterone Receptor Active Site Residues of Androgen Receptor
Table 1. Compounds from Garlic Selected for the Study and their Characteristics
Sl. No.
Compound name
1 Allicin
3 Allyl mercaptan
4 Apigenin
5 E-Ajoene
6 Ferulic acid (FA)
7 Isobutyl isothiocyanate
8 Kaempferol
10 Methyl Propyl Disulfide
11 Myricetin
12 pCA
13 Phloroglucinol
14 Quercetin
15 S-allyl cysteine (SAC)
16 S-allyl mercapto cysteine
17 Sinapinic acid
18 Taurine
19 Thiacremonone
20 2-Vinyl-4H-1,3-Dithiin
Pubchem ID
MW (500 daltons)
5280443 270.23
5386591 234.4
5280863 286.23
91820320 290.33
5281672 318.23
5280343 302.23
9794159 193.28
HBD (5) HBA (10) AlogP (5)
RB (10)
PSA (140 Е2) 61.58 104.05 38.79 89.82 86.88 69.59 46.06 112.88 162.3 50.6 153.34 60.36 60.69 135.94 93.07 120.97
78.81 93.22 85.66 50.6
Asian Pacific Journal of Cancer Prevention, Vol 17, 2016 2503
Nabarun Roy et al Table 2. Dock scores of Garlic Phytocompounds with the BC Target Proteins
Sl. No. 1 2 3 4 5 6 7 8 9 10 11 12
Garlic phytocompound SACS SAC p CA Phloroglucinol Kaempferol Isobutyl isothiocyanate Quercetin GSAC SAMC FA Taurine Apigenin
(-) CDOCKER energy (Kcal/mol) 23.66 32.8 37.22 27.55 28.57 28.82 32.58 24.89 32.77 27.96 28.05 36.24 39.25 41.24 40.85 20.53 20.84 46.31 40.72 49.19 35.47 22.79 26.54 30.61 28.52 50.51 19.42
(-)CDOCKER Interaction energy (Kcal/mol) 25.89 32.85 37.79 28.23 30.36 29.05 33.38 26.27 35.95 28.77 30.89 37.03 40.16 41.51 42.85 21.12 21.46 48.68 42.81 51.53 35.56 24.11 28.01 31.31 29.79 51.99 20.01
Binding Energy (Kcal/mol) -78.41 -85.07 -142.12 -91.24 -87.73 -83.84 -101.26 -93.06 -83.71 -104.83 -97.13 -149.31 -157.08 -168.57 -88.97 -84.73 -117.64 -154.66 -69.37 -91.56 -114.88 -100.84 -66.84 -96.95 -88.12 -114.45 -73.81
Interacting residues GLU353, ARG394 LEU718, GLN725 ARG752, GLN711 ASN564 ARG817, GLN776, LEU810 GLN725 (2), ARG766 MET745, GLN711 (2), ARG752 ASN564 GLU353 ARG766, GLN725 ARG817 (2), GLN776 ARG766, LEU718, GLN725 ARG752 GLN725, ARG766, CYS891 THR877 GLU353, ARG394 ASN705 GLN725, CYS891 GLU353 ARG817 (2), GLN776, LEU810 ARG752 (2), MET745, GLN711 ASN564 ASN564 ARG817, GLN776 GLU353 GLN725, ARG766, CYS891 ASN564
Table 3. ADMET Properties of Docked Compounds from Garlic
Sl. No.
p CA
Isobutyl isothiocyanate
10 FA
11 Taurine
12 Apigenin
Solubility level (2-4) 5 5 4 4 4 4 4 5 4 4 5 4
BBB level (2-4) 4 4 3 3 3 2 4 4 3 3 4 3
Hepatotoxic Prediction (False-non toxic) FALSE FALSE FALSE TRUE TRUE TRUE True False FALSE FALSE TRUE TRUE
Absorption level (0-1) 3 3 0 0 0 0 1 3 0 0 3 0
diagnosis, the alteration of the function of which lead to over-expression in around 80% of BC cases (Contro et al., 2015; Lumachi et al, 2015). This target also showed good interaction with garlic phytocompounds such as taurine, (SACS) p-coumaric acid (pCA), isobutyl isothiocyanate. It was seen that the critical residues such as GLU353 and ARG394 of active site 1 interacted very properly with the compounds of garlic. The lowest binding score was shown by taurine (Table 2; Figure 3). AR is expressed in BC more frequently than ER and PR (Park et al., 2010; Fioretti et al., 2014). It was found that garlic compounds responded well in interacting with this target while binding with critical residues ARG752, GLN711, MET745, THR877 and ASN705 from active site
1. The interaction of SACS with AR is shown in Figure 4. Garlic compounds also interacted with GR and MR with good binding scores. The residues such as ASN564 of active site 4 from GR and ARG817, GLN776, LEU810 of active site 2 from MR were found to be the most active to bind with the garlic phytocompounds. Evaluation of drug likeliness ADMET properties of the garlic compounds which interacted with all the BC targets are enlisted in Table 3. The ADMET parameters were found supported by the Ro5 & VP. 4 compounds are having very poor intestinal absorption i.e. SACS, SAC, GSAC and taurine, because of presence of more no. of hydrogen bond donors and
2504 Asian Pacific Journal of Cancer Prevention, Vol 17, 2016
DOI: Garlic Phytocompounds Possess Anticancer Activity by Specifically Targeting Breast Cancer Biomarkers -an in Silico Study
hydrogen bond acceptors (Honorio et al., 2013). The same compounds were also found to be highly soluble in water, due to the lower logP value of the compounds (Table 1), which depicted lower lipophilicity (Kujawski et al., 2012). Some compounds of the flavonoid group showed hepatotoxic activity like phloroglucinol, kaempferol, isobutyl isothiocyanate, quercetin, taurine and apigenin. Already many studies on the medicinal benefits of these phyto-compounds have been reported. It can be said that these compounds can be taken into consideration for making a drug with a low dosage, so that there is less toxic effect in the liver. All the compounds are noninhibitor of CYP450 enzyme (an enzyme helping in the metabolism of drugs for easy absorption and excretion), which can be known from the CYP2D6 reading. PPB binding of all the compounds was found to be poor except quercetin and FA, which depicts that all the compounds are pharmacologically active and can get unbound from plasma protein easily (Smith et al., 2010). The BBB level of all the compounds was low, which means there is less chance of side effects of the central nervous system (Cecchelli et al., 2007). In conclusion, BC alone accounts for 29% of all cancers diagnosed in women and around 61,000 cases are expected to be diagnosed in 2016 (Siegel et al., 2016). By 2020, BC cases are expected to increase by 26% and most of these will be seen in developing countries, especially in the global south (Confortini and Krong, 2015). So, it is an alarming situation to find out drugs which can be suitable for curing BC in women with least side effects. Garlic is a potent herb which yield compounds with plenty of medicinal properties. All the compounds being taken for the study passed Ro5 & VP, and the interaction experiment revealed only 12 compounds to bind with the BC targets. The ADMET profiling of the compounds revealed that almost all the compounds are perfect for proceeding into drug pipeline, if the dosage is considered. The study forms a strong base for researchers and scientists of the pharmaceutical industry, who can perform wet lab (in vitro and in vivo) analysis of these garlic compounds for developing into drugs. Acknowledgements The first author acknowledges the support by Department of Biotechnology, Ministry of Science and Technology, Govt. of India, through its HRD programme (BT/DI/03/014/2002). Arunaksharan N. acknowledge the receipt of financial grant in the form of CSIR-Senior Research Fellowship (09/869 (0012)/2012-EMR-I). References Abduljabbar R, Negm OH, Lai CF, et al (2015). Clinical and biological significance of glucocorticoid receptor (GR) expression in breast cancer. Breast Cancer Res Treat, 150, 335-46. Bagul M, Kakumanu S, Wilson TA (2015). Crude garlic extract inhibits cell proliferation and induces cell cycle arrest and apoptosis of cancer cells in vitro. J Med Food, 18, 731-7. Barlow DJ, Buriani A, Ehrman T, et al (2012). In-silico studies
in Chinese herbal medicines' research: evaluation of in-silico methodologies and phytochemical data sources, and a review of research to date. J Ethnopharmacol, 140, 526-34. Benson JR, I J (2012). The global breast cancer burden. Future Oncol, 8, 697-702. Brooks BR, Brooks CL, 3rd, Mackerell AD, Jr., et al (2009). CHARMM: the biomolecular simulation program. J Comput Chem, 30, 1545-614. Cecchelli R, Berezowski V, Lundquist S, et al (2007). Modelling of the blood-brain barrier in drug discovery and development. Nat Rev Drug Discov, 6, 650-61. Chen X, Yan CC, Zhang X, et al (2015). Drug-target interaction prediction: databases, web servers and computational models. Brief Bioinform. Confortini CC, Krong B (2015). Breast cancer in the global south and the limitations of a biomedical framing: a critical review of the literature. Health Policy Plan, 30, 1350-61. Contrт V, Basile JR, Proia P (2015). Sex steroid hormone receptors, their ligands, and nuclear and non-nuclear pathways. AIMS Mol Sci, 2, 294-310. Conzen SD (2008). Minireview: nuclear receptors and breast cancer. Mol Endocrinol, 22, 2215-28. Diep CH, Daniel AR, Mauro LJ, et al (2015). Progesterone action in breast, uterine, and ovarian cancers. J Mol Endocrinol, 54, 31-53. Dubey AK, Gupta U, Jain S (2015). Breast cancer statistics and prediction methodology: a systematic review and analysis. Asian Pac J Cancer Prev, 16, 4237-45. Ferlay J, Soerjomataram I, Dikshit R, et al (2015). cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer, 136, 359-86. Ferreira L, dos Santos R, Oliva G, et al (2015). Molecular docking and structure-based drug design strategies. Molecules, 20, 13384-421. Fioretti FM, Sita-Lumsden A, Bevan CL, et al (2014). Revising the role of the androgen receptor in breast cancer. J Mol Endocrinol, 52, 257-65. Garay JP, Park BH (2012). Androgen receptor as a targeted therapy for breast cancer. Am J Cancer Res, 2, 434-45. Gasteiger E, Hoogland C, Gattiker A, et al (2005). Protein identification and analysis tools on the ExPASy server. In: The proteomics protocols handbook, Ed.Walker. Humana Press, 571-607. Ghazanfari T, Yaraee R, Rahmati B, et al (2011). In vitro cytotoxic effect of garlic extract on malignant and nonmalignant cell lines. Immunopharmacol Immunotoxicol, 33, 603-8. Higa GM, Fell RG (2013). Sex hormone receptor repertoire in breast cancer. Int J Breast Cancer, 284036. Honorio KM, Moda TL, Andricopulo AD (2013). Pharmacokinetic properties and in silico ADME modeling in drug discovery. Med Chem, 9, 163-76. Huang J, Yang B, Xiang T, et al (2015). Diallyl disulfide inhibits growth and metastatic potential of human triple-negative breast cancer cells through inactivation of the beta-catenin signaling pathway. Mol Nutr Food Res, 59, 1063-75. Kach J, Conzen SD, Szmulewitz RZ (2015). Targeting the glucocorticoid receptor in breast and Prostate Cancers. Sci Transl Med. Khokhar A (2012). Breast cancer in India: where do we stand and where do we go? Asian Pac J Cancer Prev, 13, 4861-6. Kim S, Thiessen PA, Bolton EE, et al (2016). Pub Chem substance and compound databases. Nucleic Acids Res, 44, 1202-13. Kingsley-Kallesen M, Mukhopadhyay SS, Wyszomierski SL, et al (2002). The mineralocorticoid receptor may compensate for the loss of the glucocorticoid receptor at specific stages of
Asian Pacific Journal of Cancer Prevention, Vol 17, 2016 2505
Nabarun Roy et al
mammary gland development. Mol Endocrinol, 16, 2008-18. Zhang H, Wang K, Lin G, et al (2014). Antitumor mechanisms
Kujawski J, Popielarska H, Myka A, et al (2012). The log P
of S-allyl mercaptocysteine for breast cancer therapy. BMC
parameter as a molecular descriptor in the computer-aided
Complement Altern Med, 14, 270.
drug design - an overview. Comput Methods Sci Technol,
18, 81-8.
Leo JC, Guo C, Woon CT, et al (2004). Glucocorticoid and
mineralocorticoid cross-talk with progesterone receptor to
induce focal adhesion and growth inhibition in breast cancer
cells. Endocrinol, 145, 1314-21.
Lipinski CA (2004). Lead and drug like compounds: the rule-
of-five revolution. Drug Discov Today Technol, 1, 337-41.
Lumachi F, Santeufemia DA, Basso SM (2015). Current medical
treatment of estrogen receptor-positive breast cancer. World J Biol Chem, 6, 231-9.
Modem S, Dicarlo SE, Reddy TR (2012). Fresh garlic extract
induces growth arrest and morphological differentiation of
MCF7 breast cancer cells. Genes Cancer, 3, 177-86.
Oda A, Okayasu M, Kamiyama Y, et al (2007). Evaluation of docking accuracy and investigations of roles of parameters and each term in scoring functions for protein-ligand docking
56.3 50.0
using Argus lab software. Bull Chem Soc Jap, 80, 1920-5.
Omoto Y, Iwase H (2015). Clinical significance of estrogen
receptor beta in breast and prostate cancer from biological aspects. Cancer Sci, 106, 337-43.
Park S, Koo J, Park HS, et al (2010). Expression of androgen
receptors in primary breast cancer. Ann Oncol, 21, 488-92.
Qin C, Zhang C, Zhu F, et al (2014). Therapeutic target database update 2014: a resource for targeted therapeutics. Nucleic
Newly diagnosed without treatment
Acids Res, 42, 21.
Rose PW, Prlic A, Bi C, et al (2015). The RCSB protein data
bank: views of structural biology for basic and applied
research and education. Nucleic Acids Res, 43, 1118-23.
Sever R, Glass CK (2013). Signaling by Nuclear Receptors. Cold
Spring Harbor Perspectives Biol, 5, 16709.
Smith DA, Di L, Kerns EH (2010). The effect of plasma
protein binding on in vivo efficacy: misconceptions in drug
discovery. Nat Rev Drug Discov, 9, 929-39.
Stierand K, Rarey M (2010). Drawing the PDB: protein-ligand
complexes in two dimensions. ACS Medicinal Chemistry
Letters, 1, 540-5.
Suleria HAR, Butt MS, Khalid N, et al (2015). Garlic (Allium
sativum): diet based therapy of 21st century-a review. Asian
Pac J Tropical Disease, 5, 271-8.
Tian S, Wang J, Li Y, et al (2015). The application of in silico
drug-likeness predictions in pharmaceutical research.
Advanced Drug Delivery Reviews, 86, 2-10.
Tsubura A, Lai YC, Kuwata M, et al (2011). Anticancer effects
of garlic and garlic-derived compounds for breast cancer
control. Anticancer Agents Med Chem, 11, 249-53.
Usha T, Goyal AK, Lubna S, et al (2014). Identification of anti-
cancer targets of eco-friendly waste Punica granatum peel
by dual reverse virtual screening and binding analysis. Asian
Pac J Cancer Prev, 15, 10345-50.
Veber DF, Johnson SR, Cheng HY, et al (2002). Molecular
properties that influence the oral bioavailability of drug
candidates. J Med Chem, 45, 2615-23.
Voutsadakis IA (2016). Epithelial-Mesenchymal Transition
(EMT) and regulation of EMT factors by steroid nuclear
receptors in breast cancer: a review and in silico investigation.
J Clin Med, 5, 11.
Wu G, Robertson DH, Brooks CL, 3rd, et al (2003). Detailed
analysis of grid-based molecular docking: a Case Study of
CDOCKER-a CHARMm-based MD docking algorithm. J
Comput Chem, 24, 1549-62.
Xu HE (2015). Family reunion of nuclear hormone receptors:
structures, diseases, and drug discovery. Acta Pharmacol
Sin, 36, 1-2.
2506 Asian Pacific Journal of Cancer Prevention, Vol 17, 2016

File: garlic-phytocompounds-possess-anticancer-activity-by-specifically.pdf
Published: Mon Jun 27 22:26:41 2016
Pages: 6
File size: 0.93 Mb

Copyright © 2018