CFP last date
20 December 2024
Reseach Article

Virtual Screening of CDK9 Inhibitors as Potential Anti Cancer Drugs

by Ravi Kumar K., Archana Giri, Rama Rao Nadendla
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 157 - Number 7
Year of Publication: 2017
Authors: Ravi Kumar K., Archana Giri, Rama Rao Nadendla
10.5120/ijca2017912778

Ravi Kumar K., Archana Giri, Rama Rao Nadendla . Virtual Screening of CDK9 Inhibitors as Potential Anti Cancer Drugs. International Journal of Computer Applications. 157, 7 ( Jan 2017), 40-46. DOI=10.5120/ijca2017912778

@article{ 10.5120/ijca2017912778,
author = { Ravi Kumar K., Archana Giri, Rama Rao Nadendla },
title = { Virtual Screening of CDK9 Inhibitors as Potential Anti Cancer Drugs },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2017 },
volume = { 157 },
number = { 7 },
month = { Jan },
year = { 2017 },
issn = { 0975-8887 },
pages = { 40-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume157/number7/26846-2017912778/ },
doi = { 10.5120/ijca2017912778 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:03:19.214598+05:30
%A Ravi Kumar K.
%A Archana Giri
%A Rama Rao Nadendla
%T Virtual Screening of CDK9 Inhibitors as Potential Anti Cancer Drugs
%J International Journal of Computer Applications
%@ 0975-8887
%V 157
%N 7
%P 40-46
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cell cycle inhibition is important hallmark of anti cancer research. CDKs are divided into two types based on their Cell cycle controlling and transcriptional control. CDK 9, a transcriptional regulator serves as potential drug target. Only few drugs are under clinical trials phase 1/2/3 of CDK 9 inhibitory potential. 3BLR (pdb id) is used as docking target. Virtual screening is carried out based on the pharmacophore information generated from literature. Docking is carried out using Molegro virtual docker with all the compounds and top ranking compounds are shortlisted. The best compound (ZINC91643349) was identified and further analyzed by Invitro assays.

References
  1. Jemal A,Bray F,Center MM,Ferlay J, Ward E,Forman D. Global cancer statistics. CA: A Cancer Journal for Clinicians. 2011, 61(2),69–90.
  2. Suresh Gudala, Uzma Khan, Niteesh Kanungo, Srinivas Bandaru, Tajamul Hussain, MS Parihar, Anuraj Nayarisseri, Hema Prasad Mundluru. Identification and Pharmacological Analysis of High Efficacy Small Molecule Inhibitors of EGF-EGFR Interactions in Clinical Treatment of Non-Small Cell Lung Carcinoma: a Computational Approach. Asian Pacific Journal of Cancer Prevention:2015, 16(18), 8191- 8196.
  3. Anand P, Kunnumakkara AB, Kunnumakara AB, Sundaram C, Harikumar KB, Tharakan ST, Lai OS, Sung B, Aggarwal BB.Cancer is a preventable disease that requires major lifestyle changes. Pharm. Res.2008, 25 (9): 2097–2116.
  4. Sherr, Charles J. Cancer cell cycles. Science 1996, 27(4), 5293, 1672-1677.
  5. Campisi, Judith. Cellular senescence as a tumor-suppressor mechanism. Trends in cell biology, 2001, (11) S27-S31.
  6. MacLachlan, Timothy K., Nianli Sang, and Antonio Giordano. Cyclins, cyclin-dependent kinases and cdk inhibitors: implications in cell cycle control and cancer. Critical Reviewsin Eukaryotic Gene Expression.1995, (5), 127-156.
  7. Malumbres, Marcos, and Mariano Barbacid. Mammalian cyclin-dependent kinases. Trends in Biochemical Sciences.2005, 30, 11, 630-641.
  8. Bruyère, Céline, and Laurent Meijer. Targeting cyclin-dependent kinases in anti-neoplastic therapy. Current Opinion in Cell Biology.2013, 25,(6), 772-779.
  9. Canduri, F., Peres, P. C., Caceres, R. A., de Azevedo, J., and Filgueira, W. CDK9 a potential target for drug development. Medicinal Chemistry. 2008, 4(3), 210-218.
  10. Liu, Xiangrui, Shenhua Shi, Frankie Lam, Chris Pepper, Peter M. Fischer, and ShudongWang. CDKI-71, a novel CDK9 inhibitor, is preferentially cytotoxic to cancer cells compared to flavopiridol. International Journal of Cancer. 2012, 130(5), 1216-1226.
  11. Baumli, S., Lolli, G., Lowe, E. D., Troiani, S., Rusconi, L., Bullock, A. N.,and Johnson, L. N. The structure of P-TEFb (CDK9/cyclin T1), its complex with flavopiridol and regulation by phosphorylation. The EMBO journal,2008,27 (13), 1907-1918.
  12. Ravi Kumar Kurapati, Archana Giri and Rama Rao Nadendla. Cross Docking as a method to select CDK-9 protein target for virtual screening studies. International Journal of Computational Bioinformatics and In Silico Modeling 2013, 2(6): 275-277.
  13. Shudong Wang, G.Griffiths, CA Midgley, A L Barnett, M Cooper, JGrabarek, L Ingram, W Jackson, G Kontopidis, J Steven, I Stuart, MP Thomas, DIZheleva, DP Lane, RC Jackson, David M Glover, D GBlake, PM Fischer. Discovery and characterization of 2-anilino-4-(thiazol-5-yl) pyrimidine transcriptional CDK inhibitors as anticancer agents. Chemistry &Biology. 2010,17,(10): 1111-1121.
  14. Lukasik, Pawel M., SElabar, F Lam, Hao Shao, X Liu, Abdullah Y. Abbas, and Shudong Wang. Synthesis and biological evaluation of imidazol [4, 5-b] pyridine and 4-heteroaryl-pyrimidine derivatives as anti-cancer agents. E J of Medicinal Chemistry 2012.57, 311-22.
  15. Lipinski CA. Drug-like properties and the causes of poor solubility and poor permeability. J PharmacolToxicol Methods.2000, (44), 235-249.
  16. Irwin JJ., and Shoichet, B. K. Zinc-a free database of commercially available compounds for virtual screening. Journal of Chemical Information And Modeling,2005, 45(1),177-182.
  17. Arash Boroumand Nasr,Deepika Ponnala, Someshwar Rao Sagurthi, Ramesh Kumar Kattamuri,Vijaya Kumar Marri, Suresh Gudala, Chandana Lakkaraju, Srinivas Bandaru, and Anuraj Nayarisseri (2015). "Molecular Docking studies of FKBP12-mTOR inhibitors using binding predictions. Bioinformation,2015,11(6), 307-315.
  18. Patidar K, Deshmukh A, Bandaru S, Lakkaraju C, Girdhar A, Vr G, Banerjee T, Nayarisseri A, Singh SK. Virtual Screening Approaches in Identification of Bioactive Compounds Akin to Delphinidin as Potential HER2 Inhibitors for the Treatment of Breast Cancer. Asian Pacific Journal of Cancer Prevention. 2016, 17(4), 2291-2295.
  19. Validation of Quantitative Structure-Activity Relationship (QSAR) Model for Photosensitizer Activity Prediction Neni Frimayanti, Mun Li Yam, Hong Boon Lee, Rozana Othman, Sharifuddin M. Zain and Noorsaadah Abd. Rahman, TSAR, Oxford Molecular, Ltd. Oxford, UK version 3.3. Int. J. Mol. Sci. 2011, (12), 8626-8644.
Index Terms

Computer Science
Information Sciences

Keywords

CDK9 CDK9 inhibitors Virtual Screening Molecular Docking