STRUCTURE-BASED DRUG DESIGNING STUDIES TOWARDS EXPLORING THE POTENTIAL ANTICANCER ACTIVITY OF SELECTED PHYTOCOMPOUNDS AGAINST HISTONE DEACETYLASE 10 PROTEIN

Authors

  • Sabeena M Centre for Biotechnology and Bioinformatics, Jawaharlal Nehru Institute of Advanced Studies, Buddha Bhavan, Secunderabad, Telangana, India.
  • Kaiser Jamil Department of Genetics, Bhagwan Mahavir Medical Research Centre 10-1-1, Mahavir Marg, AC Guards, Hyderabad, Telangana, India.
  • Swamy Avn Department of Chemical Engineering, Jawaharlal Nehru Technological University Anantapur, Ananthapuramu, Andhra Pradesh, India.

DOI:

https://doi.org/10.22159/ajpcr.2018.v11i12.27944

Keywords:

Histone deacetylase 10, Post-translational modifications, Phytocompounds, Docking studies, Thioredoxin-interacting protein

Abstract

Objective: Histone deacetylases (HDACs) are proteins which play a crucial role in cell growth, maintenance, and regulation. Abnormal HDAC proteins produced by genetic mutations are common in human cancers. HDAC10 is a class II HDAC member, and its expression in many cancers has been documented. The aim of this study was to determine the best docking of phytocompounds selected from a list of such compounds in the database of chemicals for HDAC10.

Methods: The crystal structure of HDAC10 was retrieved from Protein Data Bank and prepared for docking studies by post-translational modification (PTM) analysis. Then, we have screened 450 phytocompounds for molecular docking studies and determined their binding affinities against HDAC10 by using PatchDock server.

Results: The PTM analysis showed that myristoylation sites were more abundant in HDAC10 which might be important functional sites for the gene regulation. The results revealed the receptor/inhibitor interactions within an active domain consisting of 30 important amino acid residues. Affinity-based studies have indicated the docking energy levels by calculating hydrogen bonding, steric, and hydrophobic interactions. Among the inhibitors, we could shortlist four compounds which showed excellent binding affinity. Hence, we evaluated drug binding affinities of these four compounds and determined their atomic contact energy values. Analysis of the docking results showed holacurtine>periplogenin>3,3'-diindolylmethane>epigallocat echin as the order of binding affinities, with holacurtine having the best docking score.

Conclusion: It is proposed from these studies that the docking and scoring methods could be useful for selecting and shortlisting the promising antitumor molecules. These molecules could be further tested using in vitro and in vivo methods to confirm their role in HDAC10-associated cancers. Furthermore, myristoylation sites in HDAC10 could form an important binding site for selecting hit inhibitor compounds. The PTM studies together with the binding mode analysis facilitate the protein-protein interaction studies of HDAC10, and thioredoxin-interacting protein is considered as one of the transcriptional regulators of HDAC10.

Downloads

Download data is not yet available.

Author Biography

Kaiser Jamil, Department of Genetics, Bhagwan Mahavir Medical Research Centre 10-1-1, Mahavir Marg, AC Guards, Hyderabad, Telangana, India.

Dean, School of Life Sciences and Director, Dept. of Biotechnology and Bioinformatics

References

Grunstein M. Histone acetylation in chromatin structure and transcription. Nature 1997;389:349-52.

Koprinarova M, Schnekenburger M, Diederich M. Role of histone acetylation in cell cycle regulation. Curr Top Med Chem 2016;16:732-44.

Wright DE, Wang CY, Kao CF. Histone ubiquitylation and chromatin dynamics. Front Biosci (Landmark Ed) 2012;17:1051-78.

Kuo MH, Allis CD. Roles of histone acetyltransferases and deacetylases in gene regulation. Bioessays 1998;20:615-26.

Delcuve GP, Khan DH, Davie JR. Roles of histone deacetylases in epigenetic regulation: Emerging paradigms from studies with inhibitors. Clin Epigenetics 2012;4:5.

Hagelkruys A, Sawicka A, Rennmayr M, Seiser C. The biology of HDAC in cancer: The nuclear and epigenetic components. Handb Exp Pharmacol 2011;206:13-37.

Warrell RP Jr., He LZ, Richon V, Calleja E, Pandolfi PP. Therapeutic targeting of transcription in acute promyelocytic leukemia by use of an inhibitor of histone deacetylase. J Natl Cancer Inst 1998;90:1621-5.

Ropero S, Esteller M. The role of histone deacetylases (HDACs) in human cancer. Mol Oncol 2007;1:19-25.

Pang M, Zhuang S. Histone deacetylase: A potential therapeutic target for fibrotic disorders. J Pharmacol Exp Ther 2010;335:266-72.

Falkenberg KJ, Johnstone RW. Histone deacetylases and their inhibitors in cancer, neurological diseases and immune disorders. Nat Rev Drug Discov 2014;13:673-91.

Kim HJ, Bae SC. Histone deacetylase inhibitors: Molecular mechanisms of action and clinical trials as anti-cancer drugs. Am J Transl Res 2011;3:166-79.

Dokmanovic M, Marks PA. Prospects: Histone deacetylase inhibitors. J Cell Biochem 2005;96:293-304.

Ren J, Zhang J, Cai H, Li Y, Zhang Y, Zhang X, et al. HDAC as a therapeutic target for treatment of endometrial cancers. Curr Pharm Des 2014;20:1847-56.

Bolden JE, Peart MJ, Johnstone RW. Anticancer activities of histone deacetylase inhibitors. Nat Rev Drug Discov 2006;5:769-84.

Tambunan US, Wulandari EK. Identification of a better homo sapiens class II HDAC inhibitor through binding energy calculations and descriptor analysis. BMC Bioinformatics 2010;11 Suppl 7:S16.

Marks PA, Richon VM, Rifkind RA. Histone deacetylase inhibitors: Inducers of differentiation or apoptosis of transformed cells. J Natl Cancer Inst 2000;92:1210-6.

Tong JJ, Liu J, Bertos NR, Yang XJ. Identification of HDAC10, a novel class II human histone deacetylase containing a leucine-rich domain. Nucleic Acids Res 2002;30:1114-23.

Yang Y, Huang Y, Wang Z, Wang HT, Duan B, Ye D, et al. HDAC10 promotes lung cancer proliferation via AKT phosphorylation. Oncotarget 2016;7:59388-401.

Song C, Zhu S, Wu C, Kang J. Histone deacetylase (HDAC) 10 suppresses cervical cancer metastasis through inhibition of matrix metalloproteinase (MMP) 2 and 9 expression. J Biol Chem 2013;288:28021-33.

Islam MM, Banerjee T, Packard CZ, Kotian S, Selvendiran K, Cohn DE, et al. HDAC10 as a potential therapeutic target in ovarian cancer. Gynecol Oncol 2017;144:613-20.

Guardiola AR, Yao TP. Molecular cloning and characterization of a novel histone deacetylase HDAC10. J Biol Chem 2002;277:3350-6.

Lee JH, Jeong EG, Choi MC, Kim SH, Park JH, Song SH, et al. Inhibition of histone deacetylase 10 induces thioredoxin-interacting protein and causes accumulation of reactive oxygen species in SNU- 620 human gastric cancer cells. Mol Cells 2010;30:107-12.

Jamil K, Mustafa SM. Thioredoxin system: A model for determining novel lead molecules for breast cancer chemotherapy. Avicenna J Med Biotechnol 2012;4:121-30.

Osada H, Tatematsu Y, Saito H, Yatabe Y, Mitsudomi T, Takahashi T, et al. Reduced expression of class II histone deacetylase genes is associated with poor prognosis in lung cancer patients. Int J Cancer 2004;112:26-32.

Oehme I, Lodrini M, Brady NR, Witt O. Histone deacetylase 10-promoted autophagy as a druggable point of interference to improve the treatment response of advanced neuroblastomas. Autophagy 2013;9:2163-5.

Wang JC, Kafeel MI, Avezbakiyev B, Chen C, Sun Y, Rathnasabapathy C, et al. Histone deacetylase in chronic lymphocytic leukemia. Oncology 2011;81:325-9.

Coiffier B, Federico M, Caballero D, Dearden C, Morschhauser F, Jäger U, et al. Therapeutic options in relapsed or refractory peripheral T-cell lymphoma. Cancer Treat Rev 2014;40:1080-8.

Raedler LA. Farydak (Panobinostat): First HDAC inhibitor approved for patients with relapsed multiple myeloma. Am Health Drug Benefits 2016;9:84-7.

Magrane M, UniProt Consortium. UniProt knowledgebase: A hub of integrated protein data. Database (Oxford) 2011;2011:bar009.

Hai Y, Shinsky SA, Porter NJ, Christianson DW. Histone deacetylase 10 structure and molecular function as a polyamine deacetylase. Nat Commun 2017;8:15368.

Zhang Z, Li Y, Lin B, Schroeder M, Huang B. Identification of cavities on protein surface using multiple computational approaches for drug binding site prediction. Bioinformatics 2011;27:2083-8.

Wang Y, Xiao J, Suzek TO, Zhang J, Wang J, Bryant SH, et al. PubChem: A public information system for analyzing bioactivities of small molecules. Nucleic Acids Res 2009;37:W623-33.

O’Boyle NM, Banck M, James CA, Morley C, Vandermeersch T, Hutchison GR, et al. Open babel: An open chemical toolbox. J Cheminform 2011;3:33.

Duhovny D, Nussinov R, Wolfson HJ. Efficient Unbound Docking of Rigid Molecules. Berlin Heidelberg: Springer; 2002. p. 185-200.

Schneidman-Duhovny D, Inbar Y, Nussinov R, Wolfson HJ. PatchDock and symmDock: Servers for rigid and symmetric docking. Nucleic Acids Res 2005;33:W363-7.

Voruganti HK, Dasgupta B. A novel volumetric criterion for optimal shape matching of surfaces for protein-protein docking. J Comput Des Eng 2018;5:180-90.

Benyamini H, Shulman-Peleg A, Wolfson HJ, Belgorodsky B, Fadeev L, Gozin M, et al. Interaction of c(60)-fullerene and carboxyfullerene with proteins: Docking and binding site alignment. Bioconjug Chem 2006;17:378-86.

Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 2001;46:3-26.

Kishimoto A, Nishiyama K, Nakanishi H, Uratsuji Y, Nomura H, Takeyama Y, et al. Studies on the phosphorylation of myelin basic protein by protein kinase C and adenosine 3’:5’-monophosphate-dependent protein kinase. J Biol Chem 1985;260:12492-9.

Murray D, Ben-Tal N, Honig B, McLaughlin S. Electrostatic interaction of myristoylated proteins with membranes: Simple physics, complicated biology. Structure 1997;5:985-9.

Kong L, Ranganathan S. Delineation of modular proteins: Domain boundary prediction from sequence information. Brief Bioinform 2004;5:179-92.

Dewhurst HM, Torres MP. Systematic analysis of non-structural protein features for the prediction of PTM function potential by artificial neural networks. PLoS One 2017;12:e0172572.

Audagnotto M, Dal Peraro M. Protein post-translational modifications: In silico prediction tools and molecular modeling. Comput Struct Biotechnol J 2017;15:307-19.

Chakrabarti S, Lanczycki CJ. Analysis and prediction of functionally important sites in proteins. Protein Sci 2007;16:4-13.

Begum A, Begum S, Kvsrg P, Bharathi K. In silico studies on functionalized azaglycine derivatives containing 2, 4-thiazolidinedione scaffold on multiple targets. Int J Pharm Pharm Sci 2017;9:62-75.

Singh AN, Baruah MM, Sharma N. Structure based docking studies towards exploring potential anti-androgen activity of selected phytochemicals against prostate cancer. Sci Rep 2017;7:1955.

Hansen SB, Wang HL, Taylor P, Sine SM. An ion selectivity filter in the extracellular domain of cys-loop receptors reveals determinants for ion conductance. J Biol Chem 2008;283:36066-70.

Stetz G, Verkhivker GM. Functional role and hierarchy of the intermolecular interactions in binding of protein kinase clients to the Hsp90–Cdc37 chaperone: Structure-based network modeling of allosteric regulation. J Chem Inf Model 2018;58:405-21.

Chou KC, Zhang CT. Predicting protein folding types by distance functions that make allowances for amino acid interactions. J Biol Chem 1994;269:22014-20.

Dyson HJ, Wright PE, Scheraga HA. The role of hydrophobic interactions in initiation and propagation of protein folding. Proc Natl Acad Sci U S A 2006;103:13057-61.

Mary RD, Saravanan MK, Selvaraj S. Conservation of inter-residue interactions and prediction of folding rates of domain repeats. J Biomol Struct Dyn 2015;33:534-51.

Gromiha MM, Selvaraj S. Inter-residue interactions in protein folding and stability. Prog Biophys Mol Biol 2004;86:235-77.

Schaftenaar G, de Vlieg J. Quantum mechanical polar surface area. J Comput Aided Mol Des 2012;26:311-8.

Bartzatt R. Lomustine analogous drug structures for intervention of brain and spinal cord tumors: The benefit of in silico substructure search and analysis. Chemother Res Pract 2013;2013:360624.

Johnson IT. Phytochemicals and cancer. Proc Nutr Soc 2007;66:207-15.

Yin SY, Yang NS, Lin TJ. Phytochemicals approach for developing cancer immunotherapeutics. front pharmacol. Front Med 2017;8:386.

zMalar CG, Chellaram C. Studies on phytochemical screening, antioxidant activity and anti-bacterial activity of salacia oblonga stem extract. Int J Pharm Pharm Sci 2016;8:32-6.

Upadhyay S, Dixit M. Role of polyphenols and other phytochemicals on molecular signaling. Oxid Med Cell Longev 2015;2015:504253.

Thakur VS, Deb G, Babcook MA, Gupta S. Plant phytochemicals as epigenetic modulators: Role in cancer chemoprevention. AAPS J 2014;16:151-63.

Farrand L, Oh S-W, Song YS, Tsang BK. Phytochemicals: A multitargeted approach to gynecologic cancer therapy. Biomed Res Int 2014;2014:890141.

Losson H, Schnekenburger M, Dicato M, Diederich M. Natural compound histone deacetylase inhibitors (HDACi): Synergy with inflammatory signaling pathway modulators and clinical applications in cancer. Molecules 2016;21: pii: E1608.

Dhiman M, Khanna A, Manju S. A new phenanthroindolizidine alkaloid from Tylophora indica. Chem Pap 2013;67:245-8.

Published

07-12-2018

How to Cite

M, S., K. Jamil, and S. Avn. “STRUCTURE-BASED DRUG DESIGNING STUDIES TOWARDS EXPLORING THE POTENTIAL ANTICANCER ACTIVITY OF SELECTED PHYTOCOMPOUNDS AGAINST HISTONE DEACETYLASE 10 PROTEIN”. Asian Journal of Pharmaceutical and Clinical Research, vol. 11, no. 12, Dec. 2018, pp. 262-8, doi:10.22159/ajpcr.2018.v11i12.27944.

Issue

Section

Original Article(s)