An in Silico Protocol for Identifying MTOR Inhibitors from Natural Products

Overview

Journal Mol Divers

Date 2014 Aug 27

PMID 25156384

Citations 6

Authors

Lei Chen

Ling Wang

Qiong Gu

Jun Xu

Affiliations

Soon will be listed here.

Abstract

The mammalian target of rapamycin (mTOR) is an anti-cancer target. In this study, we propose an in silico protocol for identifying mTOR inhibitors from the ZINC natural product database. First, a three-dimensional quantitative structure-activity relationship pharmacophore model was built based on known mTOR inhibitors. The model was validated with an external test set, Fischer's randomization method, a decoy set and pharmacophore mapping conformation testing. The results showed that the model can predict the mTOR inhibition activity of the tested compounds. Virtual screening was performed based on the best pharmacophore model, and the results were then filtered using a molecular docking approach. In addition, molecular mechanics/generalized born surface area analysis was used to refine the selected candidates. The top 20 natural products were selected as potential mTOR inhibitors, and their structural scaffolds could serve as building blocks in designing drug-like molecules for mTOR inhibition.

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References

Petroulakis E, Mamane Y, le Bacquer O, Shahbazian D, Sonenberg N . mTOR signaling: implications for cancer and anticancer therapy. Br J Cancer. 2006; 94(2):195-9. PMC: 2361102. DOI: 10.1038/sj.bjc.6602902. View

Zeng Z, Sarbassov D, Samudio I, Yee K, Munsell M, Ellen Jackson C . Rapamycin derivatives reduce mTORC2 signaling and inhibit AKT activation in AML. Blood. 2006; 109(8):3509-12. PMC: 1852241. DOI: 10.1182/blood-2006-06-030833. View

Borders E, Bivona C, Medina P . Mammalian target of rapamycin: biological function and target for novel anticancer agents. Am J Health Syst Pharm. 2010; 67(24):2095-106. DOI: 10.2146/ajhp100020. View

Choo A, Yoon S, Kim S, Roux P, Blenis J . Rapamycin differentially inhibits S6Ks and 4E-BP1 to mediate cell-type-specific repression of mRNA translation. Proc Natl Acad Sci U S A. 2008; 105(45):17414-9. PMC: 2582304. DOI: 10.1073/pnas.0809136105. View

Klein S, Levitzki A . Targeting the EGFR and the PKB pathway in cancer. Curr Opin Cell Biol. 2009; 21(2):185-93. DOI: 10.1016/j.ceb.2008.12.006. View

Fan Q, Knight Z, Goldenberg D, Yu W, Mostov K, Stokoe D . A dual PI3 kinase/mTOR inhibitor reveals emergent efficacy in glioma. Cancer Cell. 2006; 9(5):341-9. PMC: 2925230. DOI: 10.1016/j.ccr.2006.03.029. View

Roulin D, Cerantola Y, Dormond-Meuwly A, Demartines N, Dormond O . Targeting mTORC2 inhibits colon cancer cell proliferation in vitro and tumor formation in vivo. Mol Cancer. 2010; 9:57. PMC: 2850884. DOI: 10.1186/1476-4598-9-57. View

Barakat K, Jordheim L, Perez-Pineiro R, Wishart D, Dumontet C, Tuszynski J . Virtual screening and biological evaluation of inhibitors targeting the XPA-ERCC1 interaction. PLoS One. 2012; 7(12):e51329. PMC: 3522735. DOI: 10.1371/journal.pone.0051329. View

WALKER E, Pacold M, Perisic O, Stephens L, Hawkins P, Wymann M . Structural determinants of phosphoinositide 3-kinase inhibition by wortmannin, LY294002, quercetin, myricetin, and staurosporine. Mol Cell. 2000; 6(4):909-19. DOI: 10.1016/s1097-2765(05)00089-4. View

10.

Yang H, Rudge D, Koos J, Vaidialingam B, Yang H, Pavletich N . mTOR kinase structure, mechanism and regulation. Nature. 2013; 497(7448):217-23. PMC: 4512754. DOI: 10.1038/nature12122. View

11.

Tanneeru K, Guruprasad L . Ligand-based 3-D pharmacophore generation and molecular docking of mTOR kinase inhibitors. J Mol Model. 2011; 18(4):1611-24. DOI: 10.1007/s00894-011-1184-3. View

12.

Meric-Bernstam F, Gonzalez-Angulo A . Targeting the mTOR signaling network for cancer therapy. J Clin Oncol. 2009; 27(13):2278-87. PMC: 2738634. DOI: 10.1200/JCO.2008.20.0766. View

13.

Nagarajan S, Choo H, Cho Y, Oh K, Lee B, Shin K . IKKbeta inhibitors identification part II: ligand and structure-based virtual screening. Bioorg Med Chem. 2010; 18(11):3951-60. DOI: 10.1016/j.bmc.2010.04.030. View

14.

Garcia-Echeverria C . Allosteric and ATP-competitive kinase inhibitors of mTOR for cancer treatment. Bioorg Med Chem Lett. 2010; 20(15):4308-12. DOI: 10.1016/j.bmcl.2010.05.099. View

15.

Wang L, Chen L, Liu Z, Zheng M, Gu Q, Xu J . Predicting mTOR inhibitors with a classifier using recursive partitioning and Naïve Bayesian approaches. PLoS One. 2014; 9(5):e95221. PMC: 4018356. DOI: 10.1371/journal.pone.0095221. View

16.

Mukherjee P, Shah F, Desai P, Avery M . Inhibitors of SARS-3CLpro: virtual screening, biological evaluation, and molecular dynamics simulation studies. J Chem Inf Model. 2011; 51(6):1376-92. PMC: 3929308. DOI: 10.1021/ci1004916. View

17.

Feldman M, Apsel B, Uotila A, Loewith R, Knight Z, Ruggero D . Active-site inhibitors of mTOR target rapamycin-resistant outputs of mTORC1 and mTORC2. PLoS Biol. 2009; 7(2):e38. PMC: 2637922. DOI: 10.1371/journal.pbio.1000038. View

18.

Rollinger J, Stuppner H, Langer T . Virtual screening for the discovery of bioactive natural products. Prog Drug Res. 2007; 65:211, 213-49. PMC: 7124045. DOI: 10.1007/978-3-7643-8117-2_6. View

19.

Sakkiah S, Thangapandian S, John S, Kwon Y, Lee K . 3D QSAR pharmacophore based virtual screening and molecular docking for identification of potential HSP90 inhibitors. Eur J Med Chem. 2010; 45(6):2132-40. DOI: 10.1016/j.ejmech.2010.01.016. View

20.

Apsel B, Blair J, Gonzalez B, Nazif T, Feldman M, Aizenstein B . Targeted polypharmacology: discovery of dual inhibitors of tyrosine and phosphoinositide kinases. Nat Chem Biol. 2008; 4(11):691-9. PMC: 2880455. DOI: 10.1038/nchembio.117. View