APPRAIS

ڤەکۆلینا بەڕێوەچوونی کۆنفرانسی -

In silico molecular docking and dynamic simulation of eugenol compounds against breast cancer
In silico molecular docking and dynamic simulation of eugenol compounds against breast cancer

ڤەکۆلینا بەڕێوەچوونی کۆنفرانسی -

In silico molecular docking and dynamic simulation of eugenol compounds against breast cancer

...

Read More

Breast cancer is one of the most severe problems, and it is the primary cause of cancer-related death in females worldwide. The adverse effects and therapeutic resistance development are among the most potent clinical issues for potent medications for breast cancer treatment. The eugenol molecules have a significant affinity for breast cancer receptors. The aim of the study has been on the eugenol compounds, which has potent actions on Erα, PR, EGFR, CDK2, mTOR, ERBB2, c-Src, HSP90, and chemokines receptors inhibition. Initially, the drug-likeness property was examined to evaluate the anti-breast cancer activity by applying Lipinski’s rule of five on 120 eugenol molecules. Further, structure-based virtual screening was performed via molecular docking, as protein-like interactions play a vital role in drug development. The 3D structure of the receptors has been acquired from the protein data bank and is docked with 87 3D PubChem and ZINC structures of eugenol compounds, and five FDA-approved anti-cancer drugs using AutoDock Vina. Then, the compounds were subjected to three replica molecular dynamic simulations run of 100 ns per system. The results were evaluated using root mean square deviation (RMSD), root mean square fluctuation (RMSF), and protein–ligand interactions to indicate protein–ligand complex stability. The results confirm that Eugenol cinnamaldehyde has the best docking score for breast cancer, followed by Aspirin eugenol ester and 4-Allyl-2-methoxyphenyl cinnamate. From the results obtained from in silico studies, we propose that the selected eugenols can be further investigated and evaluated for further lead optimization and drug development.

Citation Information
  1. Lokhande KB, Nagar S, Swamy KV (2019) Molecular interaction studies of Deguelin and its derivatives with Cyclin D1 and Cyclin E in cancer cell signaling pathway: the computational approach. Sci Rep 9:1–13
  2. Article
  3.  
  4. CAS
  5.  
  6. Google Scholar
  7.  Rampun A, Morrow PJ, Scotney BW, Wang H (2020) Breast density classification in mammograms: an investigation of encoding techniques in binary-based local patterns. Comput Biol Med 122:103842
  8. Article
  9.  
  10. PubMed
  11.  
  12. Google Scholar
  13.  Akram M, Iqbal M, Daniyal M, Khan AU (2017) Awareness and current knowledge of breast cancer. Biol Res 50:1–23
  14. Article
  15.  
  16. CAS
  17.  
  18. Google Scholar
  19.  Kuhl H, Schneider HPG (2013) Progesterone–promoter or inhibitor of breast cancer. Climacteric 16:54–68
  20. Article
  21.  
  22. CAS
  23.  
  24. PubMed
  25.  
  26. Google Scholar
  27.  Saha Roy S, Vadlamudi RK (2012) Role of estrogen receptor signaling in breast cancer metastasis. Int J Breast Cancer 2012
  28. Thomas C, Gustafsson J-Å (2011) The different roles of ER subtypes in cancer biology and therapy. Nat Rev Cancer 11:597–608
  29. Article
  30.  
  31. CAS
  32.  
  33. PubMed
  34.  
  35. Google Scholar
  36.  Hayashi SI, Eguchi H, Tanimoto K et al (2003) The expression and function of estrogen receptor alpha and beta in human breast cancer and its clinical application. Endocr Relat Cancer 10:193–202
  37. Article
  38.  
  39. CAS
  40.  
  41. PubMed
  42.  
  43. Google Scholar
  44.  Salih AK, Fentiman IS (2001) Breast cancer prevention: present and future. Cancer Treat Rev 27:261–273
  45. Article
  46.  
  47. CAS
  48.  
  49. PubMed
  50.  
  51. Google Scholar
  52.  Wang Z-Y, Yin L (2015) Estrogen receptor alpha-36 (ER-α36): a new player in human breast cancer. Mol Cell Endocrinol 418:193–206
  53. Article
  54.  
  55. CAS
  56.  
  57. PubMed
  58.  
  59. Google Scholar
  60.  Acharya R, Chacko S, Bose P et al (2019) Structure based multitargeted molecular docking analysis of selected furanocoumarins against breast cancer. Sci Rep 9:1–13
  61. Article
  62.  
  63. Google Scholar
  64.  Kiani J, Khan A, Khawar H et al (2006) Estrogen receptor α-negative and progesterone receptor-positive breast cancer: Lab error or real entity? Pathol Oncol Res 12:223–227
  65. Article
  66.  
  67. PubMed
  68.  
  69. Google Scholar
  70.  Costa R, Shah AN, Santa-Maria CA et al (2017) Targeting epidermal growth factor receptor in triple negative breast cancer: new discoveries and practical insights for drug development. Cancer Treat Rev 53:111–119
  71. Article
  72.  
  73. CAS
  74.  
  75. PubMed
  76.  
  77. Google Scholar
  78.  Palma G, Frasci G, Chirico A et al (2015) Triple negative breast cancer: looking for the missing link between biology and treatments. Oncotarget 6:26560
  79. Article
  80.  
  81. PubMed
  82.  
  83. PubMed Central
  84.  
  85. Google Scholar
  86.  Reddy PS, Lokhande KB, Nagar S et al (2018) Molecular modeling, docking, dynamics and simulation of gefitinib and its derivatives with EGFR in non-small cell lung cancer. Curr Comput Aided Drug Des 14:246–252
  87. Article
  88.  
  89. CAS
  90.  
  91. PubMed
  92.  
  93. Google Scholar
  94.  Ding L, Cao J, Lin W et al (2020) The roles of cyclin-dependent kinases in cell-cycle progression and therapeutic strategies in human breast cancer. Int J Mol Sci 21:1960
  95. Article
  96.  
  97. CAS
  98.  
  99. PubMed Central
  100.  
  101. Google Scholar
  102.  Carraway H, Hidalgo M (2004) New targets for therapy in breast cancer: mammalian target of rapamycin (mTOR) antagonists. Breast Cancer Res 6:1–6
  103. Article
  104.  
  105. CAS
  106.  
  107. Google Scholar
  108.  Gee JMW, Robertson JFR, Ellis IO, Nicholson RI (2001) Phosphorylation of ERK1/2 mitogen-activated protein kinase is associated with poor response to anti-hormonal therapy and decreased patient survival in clinical breast cancer. Int J cancer 95:247–254
  109. Article
  110.  
  111. CAS
  112.  
  113. PubMed
  114.  
  115. Google Scholar
  116.  Ferrando IM, Chaerkady R, Zhong J et al (2012) Identification of targets of c-Src tyrosine kinase by chemical complementation and phosphoproteomics. Mol Cell Proteomics 11:355–369
  117. Article
  118.  
  119. PubMed
  120.  
  121. PubMed Central
  122.  
  123. CAS
  124.  
  125. Google Scholar
  126.  Zagouri F, Bournakis E, Koutsoukos K, Papadimitriou CA (2012) Heat shock protein 90 (hsp90) expression and breast cancer. Pharmaceuticals 5:1008–1020
  127. Article
  128.  
  129. CAS
  130.  
  131. PubMed
  132.  
  133. PubMed Central
  134.  
  135. Google Scholar
  136.  Liu H, Yang Z, Lu W et al (2020) Chemokines and chemokine receptors: a new strategy for breast cancer therapy. Cancer Med 9:3786–3799
  137. Article
  138.  
  139. CAS
  140.  
  141. PubMed
  142.  
  143. PubMed Central
  144.  
  145. Google Scholar
  146.  Vela M, Aris M, Llorente M et al (2015) Chemokine receptor-specific antibodies in cancer immunotherapy: achievements and challenges. Front Immunol 6:12
  147. Article
  148.  
  149. PubMed
  150.  
  151. PubMed Central
  152.  
  153. CAS
  154.  
  155. Google Scholar
  156.  Al-Sharif I, Remmal A, Aboussekhra A (2013) Eugenol triggers apoptosis in breast cancer cells through E2F1/survivin down-regulation. BMC Cancer 13:1–10
  157. Article
  158.  
  159. Google Scholar
  160.  Abdullah ML, Hafez MM, Al-Hoshani A, Al-Shabanah O (2018) Anti-metastatic and anti-proliferative activity of eugenol against triple negative and HER2 positive breast cancer cells. BMC Complement Altern Med 18:1–11
  161. Article
  162.  
  163. CAS
  164.  
  165. Google Scholar
  166.  Islam SS, Al-Sharif I, Sultan A et al (2018) Eugenol potentiates cisplatin anti-cancer activity through inhibition of ALDH-positive breast cancer stem cells and the NF-κB signaling pathway. Mol Carcinog 57:333–346
  167. Article
  168.  
  169. CAS
  170.  
  171. PubMed
  172.  
  173. Google Scholar
  174.  Bezerra DP, Militão GCG, De Morais MC, De Sousa DP (2017) The dual antioxidant/prooxidant effect of eugenol and its action in cancer development and treatment. Nutrients 9:1367
  175. Article
  176.  
  177. CAS
  178.  
  179. PubMed Central
  180.  
  181. Google Scholar
  182.  Ma M, Ma Y, Zhang G-J et al (2017) Eugenol alleviated breast precancerous lesions through HER2/PI3K-AKT pathway-induced cell apoptosis and S-phase arrest. Oncotarget 8:56296
  183. Article
  184.  
  185. PubMed
  186.  
  187. PubMed Central
  188.  
  189. Google Scholar
  190.  Yan X, Zhang G, Bie F et al (2017) Eugenol inhibits oxidative phosphorylation and fatty acid oxidation via downregulation of c-Myc/PGC-1β/ERRα signaling pathway in MCF10A-ras cells. Sci Rep 7:1–13
  191. Article
  192.  
  193. CAS
  194.  
  195. Google Scholar
  196.  Fangjun L, Zhijia Y (2018) Tumor suppressive roles of eugenol in human lung cancer cells. Thorac Cancer 9:25–29
  197. Article
  198.  
  199. PubMed
  200.  
  201. CAS
  202.  
  203. Google Scholar
  204.  Hussain A, Brahmbhatt K, Priyani A et al (2011) Eugenol enhances the chemotherapeutic potential of gemcitabine and induces anticarcinogenic and anti-inflammatory activity in human cervical cancer cells. Cancer Biother Radiopharm 26:519–527
  205. CAS
  206.  
  207. PubMed
  208.  
  209. Google Scholar
  210.  Carrasco AH, Espinoza CL, Cardile V et al (2008) Eugenol and its synthetic analogues inhibit cell growth of human cancer cells (Part I). J Braz Chem Soc 19:543–548
  211. Article
  212.  
  213. Google Scholar
  214.  Choudhury P, Barua A, Roy A et al (2021) Eugenol emerges as an elixir by targeting β-catenin, the central cancer stem cell regulator in lung carcinogenesis: an in vivo and in vitro rationale. Food Funct 12:1063–1078
  215. Article
  216.  
  217. CAS
  218.  
  219. PubMed
  220.  
  221. Google Scholar
  222.  Berman HM, Westbrook J, Feng Z et al (2000) The protein data bank. Nucleic Acids Res 28:235–242
  223. Article
  224.  
  225. CAS
  226.  
  227. PubMed
  228.  
  229. PubMed Central
  230.  
  231. Google Scholar
  232.  2IOK, Dykstra KD, Guo L, Birzin ET et al (2007) Estrogen receptor ligands. Part 16: 2-Aryl indoles as highly subtype selective ligands for ERα. Bioorg Med Chem Lett 17:2322–2328
  233. Article
  234.  
  235. CAS
  236.  
  237. Google Scholar
  238.  4OAR, Petit-Topin I, Fay M, Resche-Rigon M et al (2014) Molecular determinants of the recognition of ulipristal acetate by oxo-steroid receptors. J Steroid Biochem Mol Biol 144:427–435
  239. Article
  240.  
  241. CAS
  242.  
  243. Google Scholar
  244.  2J6M, Yun C-H, Boggon TJ, Li Y et al (2007) Structures of lung cancer-derived EGFR mutants and inhibitor complexes: mechanism of activation and insights into differential inhibitor sensitivity. Cancer Cell 11:217–227
  245. Article
  246.  
  247. CAS
  248.  
  249. Google Scholar
  250.  4RJ3, Hanan EJ, Eigenbrot C, Bryan MC et al (2014) Discovery of selective and noncovalent diaminopyrimidine-based inhibitors of epidermal growth factor receptor containing the T790M resistance mutation. J Med Chem 57:10176–10191
  251. Article
  252.  
  253. CAS
  254.  
  255. Google Scholar
  256.  4DRH: März AM, Fabian A-K, Kozany C et al (2013) Large FK506-binding proteins shape the pharmacology of rapamycin. Mol Cell Biol 33:1357–1367
  257. 2A9I: Lasker M V, Gajjar MM, Nair SK (2005) Cutting edge: molecular structure of the IL-1R-associated kinase-4 death domain and its implications for TLR signaling. J Immunol 175:4175–4179
  258. 2SRC: Xu W, Doshi A, Lei M et al (1999) Crystal structures of c-Src reveal features of its autoinhibitory mechanism. Mol Cell 3:629–638
  259. 2VCJ: Brough PA, Aherne W, Barril X et al (2008) 4, 5-diarylisoxazole Hsp90 chaperone inhibitors: potential therapeutic agents for the treatment of cancer. J Med Chem 51:196–218
  260. 4JL7: Lu G, Wu Y, Jiang Y et al (2013) Structural insights into neutrophilic migration revealed by the crystal structure of the chemokine receptor CXCR2 in complex with the first PDZ domain of NHERF1. PLoS One 8:e76219
  261. 3OE6: Wu B, Chien EYT, Mol CD, et al (2010) Structures of the CXCR4 chemokine GPCR with small-molecule and cyclic peptide antagonists. Science (80- ) 330:1066–1071
  262. 4MBS: Tan Q, Zhu Y, Li J, et al (2013) Structure of the CCR5 chemokine receptor–HIV entry inhibitor maraviroc complex. Science (80- ) 341:1387–1390
  263. Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31:455–461
  264. CAS
  265.  
  266. PubMed
  267.  
  268. PubMed Central
  269.  
  270. Google Scholar
  271.  Kim S, Chen J, Cheng T et al (2021) PubChem in 2021: new data content and improved web interfaces. Nucleic Acids Res 49:D1388–D1395
  272. Article
  273.  
  274. CAS
  275.  
  276. PubMed
  277.  
  278. Google Scholar
  279.  Sterling T, Irwin JJ (2015) ZINC 15–ligand discovery for everyone. J Chem Inf Model 55:2324–2337
  280. Article
  281.  
  282. CAS
  283.  
  284. PubMed
  285.  
  286. PubMed Central
  287.  
  288. Google Scholar
  289.  O’Boyle NM, Banck M, James CA et al (2011) Open Babel: an open chemical toolbox. J Cheminform 3:1–14
  290. CAS
  291.  
  292. Google Scholar
  293.  Wishart DS, Feunang YD, Guo AC et al (2018) DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res 46:D1074–D1082
  294. Article
  295.  
  296. CAS
  297.  
  298. PubMed
  299.  
  300. Google Scholar
  301.  Molinspiration Cheminformatics. In: Nov. ulica. https://www.molinspiration.com/
  302. Lipinski CA (2000) Drug-like properties and the causes of poor solubility and poor permeability. J Pharmacol Toxicol Methods 44:235–249
  303. Article
  304.  
  305. CAS
  306.  
  307. PubMed
  308.  
  309. Google Scholar
  310.  Chagas CM, Moss S, Alisaraie L (2018) Drug metabolites and their effects on the development of adverse reactions: revisiting Lipinski’s Rule of Five. Int J Pharm 549:133–149
  311. Article
  312.  
  313. CAS
  314.  
  315. PubMed
  316.  
  317. Google Scholar
  318.  Release S (2017) 3: Desmond molecular dynamics system, DE Shaw research, New York, NY, 2017. Maest Interoperability Tools, Schrödinger, New York, NY
  319. Pushpalatha R, Selvamuthukumar S, Kilimozhi D (2017) Comparative insilico docking analysis of curcumin and resveratrol on breast cancer proteins and their synergistic effect on MCF-7 cell line. J Young Pharm 9:480
  320. Article
  321.  
  322. CAS
  323.  
  324. Google Scholar
  325.  DeBono A, Thomas DR, Lundberg L et al (2019) Novel RU486 (mifepristone) analogues with increased activity against Venezuelan Equine Encephalitis Virus but reduced progesterone receptor antagonistic activity. Sci Rep 9:1–19
  326. Article
  327.  
  328. CAS
  329.  
  330. Google Scholar
  331.  Barzegar M, Ma S, Zhang C et al (2017) SKLB188 inhibits the growth of head and neck squamous cell carcinoma by suppressing EGFR signalling. Br J Cancer 117:1154–1163
  332. Article
  333.  
  334. CAS
  335.  
  336. PubMed
  337.  
  338. PubMed Central
  339.  
  340. Google Scholar
  341.  Liu Z, Wang F, Zhou Z-W et al (2017) Alisertib induces G2/M arrest, apoptosis, and autophagy via PI3K/Akt/mTOR-and p38 MAPK-mediated pathways in human glioblastoma cells. Am J Transl Res 9:845
  342. CAS
  343.  
  344. PubMed
  345.  
  346. PubMed Central
  347.  
  348. Google Scholar
  349.  Ding Y, Fang Y, Moreno J et al (2016) Assessing the similarity of ligand binding conformations with the Contact Mode Score. Comput Biol Chem 64:403–413
  350. Article
  351.  
  352. CAS
  353.  
  354. PubMed
  355.  
  356. PubMed Central
  357.  
  358. Google Scholar
  359.  García-Godoy MJ, López-Camacho E, García-Nieto J et al (2016) Molecular docking optimization in the context of multi-drug resistant and sensitive EGFR mutants. Molecules 21:1575


فیدباکی خۆتمان بۆ بنێرە