Need help?

800-5315-2751 Hours: 8am-5pm PST M-Th;  8am-4pm PST Fri
Medicine Lakex
medicinelakex1.com
/b/bioinfo.aizeonpublishers.net1.html
 

Bioinfo.aizeonpublishers.net

International Journal of Computational Bioinformatics
and In Silico Modeling

Vol. 1, No. 5 (2012): 55-57 Research Article Open Access ISSN: 2320-0634

In Silico lead identification by virtual screening and in vitro
anti-cancer activities by MTT assay

Adinarayana KPS1, Ajay Babu P2* and Srinivas Kumar Palakeerthi2
1Associate Professor, Department of Anatomy, RIMS Medical College, Srikakulam, Andhra Pradesh, India and 2Department of
Biotechnology, JNT University, Hyderabad, Andhra Pradesh, India * Corresponding author. email: [email protected] Received: 10 October 2012 Accepted: 25 Octob er 2012 Online: 12 November 2012 ABSTRACT
Computational tools have been widely utilized to design potent leads against specific targets as a part of drug
discovery process. Moreover, virtual screening has been reported as an efficient concept in filtering actives from a
huge library of compounds. In this paper, a computational approach employing virtual screening of Drug Bank
database was implemented to dock 1400 drugs against caspase-3 to evaluate the binding affinities of ligands with the
receptor. Docking analysis with Molegro Virtual Docker revealed top 10 drugs and hence consensus re-scoring was
employed to obtain true hits. Classes were generated using rank-sum technique and the top five hits (Olmesartan,
Verteporfin, Saprisartan, Atorvastatin and Lapatinib) were tested experimentally to determine the inhibitory effects
on growth of HeLa cells in vitro. It was observed that proliferation of HeLa cells could be significantly inhibited by
Atorvastatin in a concentration dependent manner.
Keywords: Apoptosis, Caspase-3, Docking, carcinoma of cervix, MTT assay
Few papers [2] emphasized focus on crucial factors that determine the success of screening paradigm such as the Advancements in science and technology have realized the potential benefits in numerous ways to enhance drug size and diversity of the dataset, 3-dimensional X-ray discovery process towards the development of novel structures and the parameters (algorithm, scoring drugs against many lethal diseases. The application of function etc) used in docking programs. Literature reports computational tools to design potent leads against suggested the magnitude of size of the dataset [3-4] as specific protein or enzyme target has become an integral part of in silico drug discovery process. An important aspect in docking studies is visualization of docked poses of high-scoring compounds because the In recent studies, virtual screening has been reported as an efficient concept in filtering actives from a huge library binding orientations of ligands differ with respect to the geometry of the active site region. Moreover, the strength of compounds for drug discovery process [1]. Virtual screening utilizes docking and scoring of each compound of binding is based on the interactions with conserved from a dataset and the technique is based on docking residues that are known to be important for the target compounds against X-ray crystallographic structure of a protein and the binding modes as well as binding affinities In the present study, computational approach followed by of each compound are predicted. X-ray crystallographic structures have become an important tool in modern drug experimental analysis of few drugs was carried out to test discovery process and insights can be obtained on the the inhibitory activity against carcinoma of cervix, HeLa protein-ligand interactions and biological function of cells. In order to advance the use of computational techniques in studying binding affinities of ligands with the receptor, Molegro Virtual Docker [6] is used to screen nearly 1400 drugs available from Drug Bank database Adinarayana et al. / Int J Comput Bioinfo and In Silico Model. 2012, 1(5): 55-57 against cell death mediated apoptotic protease enzyme volume of 100 µl and then cultured for 48 hr. All caspase-3. Apoptosis is the most well known processes by compounds were prepared as 3mg/ml concentration which cell death is mediated by at least 14 members of stock solutions in dimethyl sulfoxide (DMSO). The final cysteinyl aspartic proteases implicated in various diseases concentration of DMSO in the culture was within 0.2%. such as stroke, arthritis, autoimmune disorders and Culture medium and solvent are used as controls. Each cancers [7]. Of all the caspases, caspase-3 enzyme plays a well then received 2 µl of fresh MTT (0.5mg/ml in PBS) major role in the apoptotic signaling cascade and was followed by incubation for 2hr at 37°C. The growth found to be activated in multiple signaling pathways of medium was removed from the wells and replaced with apoptosis and hence chosen as potential target in this 100 µl of DMSO to solubilise the coloured formazan study [8]. Consensus scoring and ranking of top five drugs product. After 30 min incubation, the absorbance of the are selected to perform cytotoxic activities by MTT assay culture plate was read at a wavelength of 570 nm on an [9] on carcinoma of cervix. ELISA plate reader, Anthos 2020 spectrophotometer. The mean OD values of each test compound were corrected MATERIALS AND METHODS
by subtracting with the mean OD of blanks. Relative percent inhibition activity is expressed as: Receptor X-ray structure
The X-ray crystallographic structure of caspase-3 bound % inhibition = 100 – (corrected mean OD of sample x 100 / with an isatin sulphonamide inhibitor (PDB code: 1GFW) corrected mean OD of control) from Protein Data http://www.rcsb.org/pdb) and selected as the receptor RESULTS AND DISCUSSION
model in virtual screening program. Drug Bank database (www.drugbank.ca) and the docking software Molegro Before screening Drug Bank database, the docking Virtual Docker (MVD) was considered for virtual ligand protocol was validated. 1GFW bound ligand was docked docking. Before docking, the 2D structures of 1400 drugs into the binding pocket to obtain the docked pose and the were converted to 3-dimensional formats online RMSD of all atoms between these two conformations was 1.082 A° (Table 1) indicating that the parameters for structures were energy minimized using MVD. docking simulation are good in reproducing the X-ray crystal structure. Therefore, Drug Bank database was As docking and scoring play important roles in drug screened to retrieve compounds that bind to the active design, it has been reported that consensus re-scoring site region of 1GFW with relatively high binding affinities was generally more effective than single scoring scheme and the top 10 drugs are given in Table-2. and represented an effective way in improving hit rates in various virtual database screening studies [10-11]. Table 1. Mol dock scores of 1GFW bound co-crystallized ligand
Therefore, in this study, we tested five different scoring functions (Molegro Virtual Docker, PatchDock, GOLD, Mol Dock Score(kcal/mol)
MEDock and AutoDock), respectively. Initially all drugs Dock Score
were docked using MVD. During ranking, signs of some scoring functions are changed to make certain that a lower score always indicates higher affinity. In vitro cytotoxicity studies
In vitro cytotoxicity studies were carried out by MTT assay From the docking analysis, it has been identified that on top five hits from our screening study. MTT assay relies nearly 10 drugs are found to have binding affinities more on the ability of live cells to reduce a water-soluble yellow than the co-crystallized ligand and hence consensus re- scoring was employed (Table 2) to obtain true hits. diphenyltetrazolium bromide) to a water-insoluble purple Ranking was done individually by clustering scores into formazan product. The MTT assay developed by equally split three classes of which compounds in class3 Mossmann [9] was modified and used to determine the represents the highest class or top rank. Classes were inhibitory effects of test compounds on growth of HeLa generated for all scoring functions and instead of taking cells in vitro. Briefly, the trypsinized cells from T-25 flask an average, rank-sum technique [11] was employed to were seeded in 96-well flat-bottomed tissue culture plate retrieve best compounds. The ranks obtained from each at a density of 5x103 cells/well in growth medium (DMEM of the scoring functions were added to give the rank-sum. supplemented with 10% Fetal calf serum) and cultured at The advantage of a sum over average was that the contribution from the rank for each individual score can 2 to adhere. After 48 hrs of incubation, the cells were pretreated with growth medium and mixed more easily be split out for illustrative purposes in the with different concentrations of test compounds (8, 16, former instance. 32, 64, 128 and 256 µg/ml) in triplicates to achieve a final


Adinarayana et al. / Int J Comput Bioinfo and In Silico Model. 2012, 1(5): 55-57 Table 2. Docking, re-scoring results and ranking of top 10 drugs Vs 1GFW
Binding energies (kcal/mol)
Olmesartan
Verteporfin
Saprisartan
Lapatinib
Finally, cell based cytotoxic activity of top five drugs Atorvastatin and Lapatinib were investigated for their against carcinoma of cervix (HeLa) by MTT assay revealed ability to inhibit HeLa cell proliferation using MTT assay. growth inhibitory characteristic of these drugs in vitro. Atorvastatin was found to be the most effective in Cancer cells were exposed to the selected compounds for reducing the growth of HeLa cell lines. Hence, this study 48 hrs and it was found that cell viability gradually employing molecular docking analysis along with decreased in a dose-dependent manner and the results experimental observations reveals the importance of reported in Table 3 suggest that the proliferation of HeLa various drugs specific to a disease on one hand and may cells could be significantly inhibited by Atorvastatin in a also act as possible anti cancer agents, on the other. concentration dependent manner. The maximum percent inhibition was found to be 83.6% at a tested dose of 64 REFERENCES
g/ml. The morphology of cells after treatment with drugs Jalaie M, Shanmugasundaram V. Virtual screening: are we there appeared significantly different than untreated cells, yet? Mini Rev Med Chem. 2006 6(10):1159-1167 which could probably due to the growth inhibitory and Warren GL, Andrews CW, Capelli AM et al. A critical assessment of cell death initiating ability of the studied compounds. docking programs and scoring functions. J Med Chem. 2006 49(20):5912-31 Rummey C, Nordhoff S, Thiemann M et al. In silico fragment-based Table 4. Inhibitory effects of drugs on the growth of HeLa cells
discovery of DPP-IV S1 pocket binders. Bioorg Med Chem Lett. 2006 cultured in vitro. Kellenberger E, Springael JY, Parmentier M et al. Identification of nonpeptide CCR5 receptor agonists by structure-based virtual Percent Inhibition (%)
screening. J Med Chem. 2007 50(6):1294-303 Waszkowycz B. Towards improving compound selection in structure-based virtual screening. Drug Discov Today. 2008 13(5- Thomsen R and Christensen MH (2006). MolDock: a new technique for high-accuracy molecular docking. J Med Chem 49: 3315-3321 Thompson CB. Apoptosis in the pathogenesis and treatment of disease. Science. 1995;267:1456–62 Porter AG and Janicke RU. Emerging roles of caspase-3 in apoptosis. Cell Death Differ. 1999; 6:99–104 Mosmann T (1983). Rapid colorimetric assay for cellular growth and survival: Application to proliferation and cytotoxicity assays, J Immunol Methods. 65: 55-63 10. Charifson PS, Corkery JJ, Murcko MA et al. (1999). Consensus scoring: a method for obtaining improved hit-rates from docking databases of three-dimensional structures into proteins. J Med CONCLUSION
Chem. 42: 5100–5109 Screening studies of 1400 drugs obtained from drug bank 11. Clark RD, Strizhev A, Leonard JM et al. (2002). Consensus scoring database are docked against 1GFW using Molegro Virtual for ligand/protein interactions. J Mol Graph Modeling 20: 281-29 Docker software resulted in 10 drugs and the top five drugs 2012; AIZEON Publishers

This is an Open Access article distributed under the terms of the Creative Commons Attribution License which permits unrestricted use,
distribution, and reproduction in any medium, provided the original work is properly cited.

Source: http://bioinfo.aizeonpublishers.net/content/2012/1/jbr11.pdf

4mygp.info

ContentsIntroduction What is Alzheimer's? 02 visit: www.alzheimersresearchuk.org This introductory booklet aims to provide an overview of Alzheimer's disease. It is for anyone who wants to know more about the disease, including people living with Alzheimer's, their carers, friends and family. The information here does not replace any advice that doctors, pharmacists or nurses may give you. It provides background information which we hope you will find helpful.

test.epanekkinisi.gr

AnnAls of CliniCAl PsyChiAtry AnnAls of CliniCAl PsyChiAtry 2011;23(2):105-112 strategic vs nonstrategic gambling: Characteristics of pathological gamblers based on gambling preference Brian L. Odlaug, BA BACKGROUND: Although prior studies have examined various clinical char- Department of Psychiatry acteristics of pathological gambling (PG), limited data exist regarding the