BCL-2 TARGETED STRUCTURAL BASED COMPUTER AIDED DRUG DESIGN (CAAD) FOR THERAPEUTIC ASSESSMENT OF RICIN IN PROSTATE CANCER
Abstract
Cancer is referred as uncontrolled growth of abnormal cell mass. Out of the several types of cancer, prostate cancer (PC) has become a major public health problem in men worldwide. Bcl-2 and p27 proteins are important regulatory molecules of cell cycle. Failure of cell cycle regulation leads to uncontrolled cell proliferation and causes cancer. For designing an effective structural based targeted drug, the assessment of protein-protein and protein-ligand interaction is indispensable. Therefore for treatment of PC, we selected a ribosome inactivating protein, Ricin, for assessment of its therapeutic nature. In the present work through CLUSTAL-W phylogenetic analysis, we found that Bcl-2 protein was found more conserved than p27. Further Bcl-2 was selected as target molecule for docking study with Ricin protein and other chemically synthetic inhibitor molecules i.e. 2-difluoromethylornithine (DFMO) and Sarcosine, as lead molecule. Through HEX5.1 docking software docking was performed between targeted receptor and lead molecules. Energy maximum (Emax= -93.12) and energy minimum (Emin= -163.07) was observed for docking complex of optimised and energy minimised structure of Bcl-2 receptor with Ricin, which in turn shows that it is highly stable interaction. On the other hand, for synthetic inhibitors, we found energy maximum (DFMO; Emax= -77.17, Emin= -117.83 and Sarcosine; Emax= -72.23, Emin= -103.00) and energy minimum, which are significant more as compared to Ricin docking complex. Due to ricin docking complex having less energies shows stable interaction with Bcl-2. We also observed that Ricin is less toxic (lesser log P value) as compared to other molecules by toxicity analysis by ADME/TOX server. These evidences show this Ricin could be better drug for PC. Further results are needed to validate by in vitro and in vivo study to make proper elucidation of drug for better PC treatment.
Keywords:
Ricin, Prostate cancer, Molecular Docking, Bcl-2, Anti-cancerDOI
https://doi.org/10.25004/IJPSDR.2015.070207References
2. Gleave ME, Miayake H, Goldie J, Nelson C, Tolcher A. Targeting Bcl-2 gene to delay androgen independent progression and enhance chemo sensitivity in prostate cancer antisense Bcl-2 oligodeoxynucleotides. Urology 1999; 54: 36-46.
3. Anthony JR, Harris P, Min-Wei C, Mark LD, Jack SS, Ralph B. Overexpression of bcl-2 protects prostate cancer cells from apoptosis in vitro and confers resistance to androgen depletion in vivo. Cancer Res 1995; 55: 4438-4445.
4. Tsihlias J, Kapusta LR, DeBoer G, Morava-Protzner I, Zbieranowski I, Bhattacharya N, Catzavelos GC, Klotz LH, Slingerland JM. Loss of cycline-dependent kinase p27Kip1 is a novel prognostic factor in localized human prostate adenocarcinoma. Cancer Res 1998; 58: 542-548.
5. Olsnes S, Pihl A. Different biological properties of the two constitute peptide chain of Ricin, a toxic protein inhibiting protein synthesis. Biochemistry 1973; 16: 3121-3126.
6. Lord JM, Roberts LM, Robertus JD. Ricin: structure, mode of action, and some current applications. FASEB J 1994; 2: 201-208.
7. Rao PV, Jayaraj R, Bhaskar AS, Kumar O, Bhattacharya R, Saxena P, Dash PK, Vijayaraghavan R. Mechanism of Ricin-induced apoptosis in human cervical cancer cells. Biochem Pharmacol 2005; 5: 855-865.
8. Prakash N, Patel S, Faldu NJ, Ranjan R, Sudheer DVN. Molecular docking studies of antimalarial drugs for malaria. J Comput Sci Syst Biol 2010; 3: 70-73.
9. Zacharias M. Protein-protein docking with a reduced protein model accounting for side-chain flexibility. Protein Sci 2003; 6: 1271-1282.
10. Lyskov S, Gray JJ. The Rosetta Dock server for local protein-protein docking. Nucleic Acids Res 2008; 36: 233-238.
11. David WR. Evaluation of protein docking predictions using Hex 3.1 in CAPRI rounds 1 and 2. Proteins 2003; 52: 98-106.
12. Chikhi A, Bensegueni A. Docking efficiency comparison of surflex, a commercial package and Arguslab, a Licensable Freewar. J Comput Sci Syst Biol 2008; 1: 81-86.
13. 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.
14. Kanehisa M, Goto S. Kyoto encyclopedia of genes and genomes. Nucleic Acids Res 2000; 28: 27-30.
15. Skariyachan S, Krishnan RS, Biradar UB. In Silico investigation and docking studies of E2F3 tumour marker: discovery and evaluation of potential inhibitors for prostate and breast cancer. International Journal of Pharmaceutical Sciences and Drug Research 2010; 2: 254-260.
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