1. INTRODUCTION:

Non-Steroidal Anti-Inflammatory Drugs:

NSAIDs comprise a large class of drugs with many different options. In addition to aspirin, there are currently several types of both non-prescription (over-the-counter) NSAIDs and prescription brands of NSAIDs. NSAIDS is a group of drugs called non steroidal anti-inflammatory drugs. It works by reducing hormones that cause inflammation and pain in the body¹. NSAIDS are used to treat pain or inflammation caused by conditions such as arthritis, ankylosing, spondylitis, tendinitis, bursitis, gout, or menstrual cramps.

Classification:

1.1. Non-Selective Cox Inhibitors

a. Propionic Acid Derivatives, (Ibuprofen, Naproxen),

b. Salicylates (Aspirin, Diflunisal, Salsalate),

c. Acetic Acid Derivatives (Indomethacin, Diclofenac)

1.2. Selective COX-2 Inhibitors

Coxibs (Celecoxib, Rofecoxib, Valdecoxib, Etoricoxib , Firocoxib), Naproxen

General Introduction:

Naproxen is a group of drugs called non steroidal anti-inflammatory drugs (NSAIDS). It is a prop ionic acid derivative. Naproxen can increase your risk of life-threatening heart or circulation problems, including heart attack or stroke². Do not use this medicine just before or after having heart bypass surgery³. Naproxen can also increase your risk of serious effects on the stomach or intestines, including bleeding. Older adults may have an even greater risk of these serious gastrointestinal side effects⁴ and general structure of Naproxen was shown in Figure 1.

Figure 1: Structure of Naproxen

Important Uses of Naproxen:

It is used to relieve pain and inflammation in a wide variety of musculoskeletal conditions including various types of arthritis (a painful condition of the joints).osteoarthritis, rheumatoid arthritis (including in children), ankylosing spondylitis), attacks of gout and other musculoskeletal conditions such as joint pain, muscular pain and back pain as well as painful periods. Naproxen works by blocking the action of cyclo-oxygenase (COX), which is involved in the production of chemicals that cause pain, swelling and inflammation. Typical Uses of Naproxen are Rheumatoid arthritis, Osteoarthritis, Juvenile rheumatoid arthritis, Ankylosing spondylitis Other musculoskeletal conditions such as joint pain, back pain, gout, muscle strains and tendonitis, Period pain⁵, Pain following surgery, Migraine.

Adverse Effects:

Chest pain, weakness, shortness of breath, slurred speech, problems with vision Black, bloody, or tarry stools. Coughing up blood or vomit that looks like coffee grounds⁶. Swelling or rapid weight gain, Urinating less than usual or not at all.

CELECOXIB:

General Introduction:

Celecoxib is a group of drug called SELECTIVE non-steroidal anti inflammatory drug. It works by reducing hormone that causes inflammation⁷ and pain in the body. Celecoxib is used to treat pain or inflammation caused by condition such as Arthritis, Ankglosing⁸, Spondylitis, Tenclinitis, Bursitis, Gout or menstrual cramps.

Common Adverse effects are Gastric ulceration/bleeding, Diarrhea⁹ and general structure of Celecoxib was shown in Figure 2.

Structure

Figure 2: Structure of Celecoxib

Computational biology and bioinformatics have the potential not only of speeding up the drug discovery process thus reducing the costs¹⁰, but also of changing the way drugs are designed, rational drug design helps facilities and speed up the drug process, which involves variety of methods to identify novel compounds. One such method is the docking of the drug molecules with the receptor, the site of the drug action, which is ultimately responsible for the pharmaceutical effect. Docking is the process by which two molecules fit together in 3d space.

2. MATERIALS AND METHODS:

For our studies we have used various bioinformatics software’s like Swiss-port, NCBI to get a query sequence. RASMOL and SWISS PDB VIEWER for visualization of predicted structure¹¹. We used SAVS [structural analysis and validation server], RAMPAGE to visualizing and analyze the modeled structure, BLAST for finding the homologous sequences to our Query. Swiss-Pdb Viewer is an application that provides a user friendly interface allowing analyzing several proteins at the same time, MODELLER is an automated homology modeling scheme designed to find the most probable three dimensional structure of a protein, given its amino acid sequence and its alignment with related structures. For Docking we used INSIGHT II program and various online docking programs like GrammX¹¹ and ClusPro. INSIGHT-II can also calculate protein ligand docking, assuming the ligand is rigid.

Drug bank is a unique bioinformatics resource that combines detailed drug data with comprehensive drug target¹². Each drug card entry contains more than 80 data fields with half of the information being devoted to drug data, and the other half devoted to protein target. The protein data bank is the single worldwide archive of structural data of biological macromolecules established in national laboratories. It contain structural information of the macromolecules determined by X-ray crystallographic, NMR method etc, national institute of health developed and managed by NIHS national center for biotechnology information (NCBI) in the national library of medicine¹³. RASMOL [Raster Display of Molecules] is a molecular graphics program indented for the structural visualization of protein, nucleic acid and biomolecules. The program reads in molecular coordinate files and interactively displays the molecules on the screen in variety of representation and color schemes.

In docking Patch Dock algorithm is inspired by object recognition and image segmentation techniques used in Computer Vision. Docking can be compared to assembling a puzzle. When solving the puzzle we try to match two pieces by picking one piece and searching for the complementary one was shown in Figure 3.

Figure 3: Surface Patch Matching

GRAMM-X Protein Docking Web Server:

This is the Web interface to our current protein docking software made available to the public. This software is different from the original GRAMM, except that both packages use FFT for the global search of the best rigid body conformations. (http://vakser.bioinformatics.ku.edu/ resources/gramm/grammx).The field of protein–protein docking is currently in thestate of rapid development and expansion. In a few months since its launch, the GRAMM-X server has processed>1000 jobs submitted by >250 users.

METHODS:

It is an emerging field with the potential to significantly improve how drugs are found, brought to the clinical trials and eventually released to the market place. The computer aided drug design heavily depends on bioinformatics tools. The structure of COX receptor was retrieved from PDB (P29216). Using chem. sketch the structures of the drugs was generated¹⁴. The docking analysis of naproxen and celecoxib was carried by INSIGHT-II docking software¹⁵.The steps involved in drug design and docking are as fallows

STEP: 1 First we search for the sequence of our target protein COX. We search our protein sequence in NCBI. We should make sure that does not have a PDB structure.

STEP: 2 The FASTA format of the target sequence thus obtained from NCBI was submitted to BLAST tool (blastp) and sequences with higher similarity (>40%), higher scores and less gaps and known PDB structures were selected.

STEP: 3 Among the closely related template sequences, one sequence 1BFO with the highest similarity, best score and least gap is selected as template and compared with our query sequence was shown in Figure 4.

Figure 4: Query sequence

STEP: 4 Comparative structural modeling by MODELLER

STEP: 5 we can visualize our generated model using RASMOL using following commands in the terminal.

STEP: 6 we can validate the predicted structure by Rampage (Ramachandran plot) and SAVS on line tools by just entering the PDB files of our predicted structures was shown in Figure 5.

Figure 5: Rampage

STEP: 7, The Best Structure Selected is visualized in INSIGHTII was shown in Figure 6.

Figure 6: Best structure

STEP: 8 Then we minimized its energy so that it attains the stable conformation was shown in Figure 7.

Figure 7: Stable structure

STEP: 9 Minimized structure is automatically stored as a core file is used for docking.

STEP: 10 DOCKING results of Naproxen and Celecoxib were shown in Figure 8 and 9.

Figure 8: Docking Result of Naproxen

Figure 9: Docking Result of Celecoxib

We use online Docking web server Patch dock, online tool was shown in Figure 10 and path dock results of Naproxen and Celecoxib was shown in Figure 11 and 12.

Figure 10: Docking by Online Tool

Figure 11: Patch Dock Result of Naproxen

Figure 12: Patch Dock Result of Celecoxib

3. RESULTS:

Docking results tabulated between COX RECEPTOR the modified drug as well as with the modified drugs are shown below along with the changes or modification within them. It was observed using RASMOL that acid group present in the drug naproxen and sulphonamide present in celecoxib was the site of binding receptor. Several modifications were made to these probable functional groups, which result in decrease in energy; the energy value was calculated by using INSIGHT II. The pharmacoporic part of the drug also partially identified¹⁶.

Based on the literature it has been shown clearly that the drugs naproxen and celecoxib have been used to target receptor COX¹⁶, Naproxen and Celecoxib on docking with Cox produce an energy value of -238.84 and -245.36 respectively was shown in Table 1 and 2. An analog with acid group and sulphonamide was prepared virtually by using chemsketch. This showed an increased in energy value, that mean more compatible with receptor than its predecessor. However, the binding site of the analog was similar to that of its predecessor, which means, the functional group involved were the same and by preparing the analog only stearic compatibility was increased. The functional group attaching position (R, R’, R’’) of naproxen and Celecoxib was shown in figure 13 and 14.

Figure 13: Naproxen

Table: 1

NAPROXEN

R-OCH₃

R’-CH₃

R”-COOH

E-VALUE

-238.84

Structure I

R-CH₃

R’-CH₃

R”-COOH

-241.02

Structure II

R-CH₃

R’-OCH₃

R”-COOH

-256.70

Structure III

R-CH₃

R’-OCH₃

R”-C₆H₆

-266.80

Structure IV

R-OCH₃

R’-OCH₃

R”-COOH

-234.38

Structure V

R-OCH₃

R’-OCH₃

R”- C₆H₆

-259.20

CELECOXIB:

Figure 14: Celecoxib

Table: 2

CELECOXIB

R-CH₃

R’- CF₃

R”- NH₂

E-VALUE

-245.36

Structure I

R-COOCH₃

R’-CF₃

R”-NH₂

-302.34

Structure II

R-COOCH₃

R’-CH₃

R”-NH₂

-289.28

Structure III

R-CH₃

R’-CH₃

R”-CONH2

-274.02

Structure IV

R-COOCH₃

R’-CF₃

R”-CONH₂

-298.36

Structure V

R-COOCH₃

R’-CH₃

R”-CONH₂

-256.72

4. DISCUSSION:

The protein – ligand interaction plays a significant role in structural based drug designing. The COX-NSAID docking was performed in Patch dock by Grid docking procedure. The docking brings about conformational changes in COX protein. The protein sequence was retrieved from NCBI. The fasta format of raw sequence was submitted to blast search. The homologous sequence was selected through blast search. The homologous sequence thus obtained was selected as template over which model building of target was done. The structure of target protein was generated by Modeller 9v1. The generated model was then evaluated by SAVS. The best model was loaded in Patch dock. The drug was build by using Chemsketch tools. The best generated model was subjected to energy minimization to attain stable configuration. Finally docking was performed. Thus model building of COX docking with NSAIDs was performed¹⁷.From this we concluded that some of the modified drugs are better than the Naproxen and Celecoxib available in the market. In further research work the ADME/T (absorption, distribution, metabolism, and excreation/ toxicity) properties of these compounds can be calculated using the commercial ADME/T tools available thus reducing the time and cost in drug discovery process.

5. REFERENCES:

1. W. F. Stewart, C. Kawas, M. Corrada, et al., NSAID use. The Journal of Neurology, 1997; No. 48: 46 – 47.

2. Dr. Markenson, A .M. Simon AM, et al. HSS Physicians Review Literature on the Safety of COX-2 Inhibitors, 2005; 17(6): 963-976 and A. S. Taha, S. McLaughlin, P. J. Holland, R. W. Kelly, et al., R I Russell Annals of the Rheumatic Diseases, 1990; No. 49: 354-358.

3. T. Kurth, R. J. Glynn, A. M. Walker, et al., The American Journal of Primary Health Care, 2003; No.108: 1191 – 1195.

4. El Hajj I, Hawchar M, Sharara A. Department of Internal Medicine, Division of Gastroenterology, American University of Beirut Medical Center (AUBMC), 2009; NO. 57 (4): 274 – 276.

5. J. M. Schildkraut, P. G. Moorman, S. Halabj, et al., The American Journal of Primary Health Care, 2006; No. 17: 104-107.

6. Schildkraut JM, Moorman PG, Halabj S, Calingaert B, Marks JR, Berchuck A. Analgesic drug use and risk of ovarian cancer. Epidemiology, 2006; NO. 17(1): 104-107.

7. Romanò CL, et al. Celecoxib versus Indomethacin in the Prevention of Heterotopic Ossification After Total Hip Arthroplasty. The Journal of Arthroplasty, 2004; NO. 19(1): 14-18.

8. Zhang et al., Cyclooxygenase-2 regulates mesenchymal cell differentiation into the osteoblast lineage and is critically involved in bone repair. The Journal of Clinical Investigation, 2004; 109(11): 1405-1415.

9. Lee S. Simon, Arthur L. Weaver, David Y. Graham, Anti-inflammatory and Upper Gastrointestinal Effects of Celecoxib in Rheumatoid Arthritis, A Randomized Controlled Trial. JAMA, 1999; No. 20: 1921.

10. Computational Biology and Drug Discovery: From single – network Drugs Current Bioinformatics, 2006; NO.1: 3-13.

11. (http://vakser.bioinformatics.ku.edu/resources/gramm/grammx).

12. sc - PDB: a database for identifying variations and multiplicity of ‘druggable’ binding sites in proteins Bioinformatics, 2011; No.27(9): 1324-1326 (http://bioinfo-pharma.u-strasbg.fr/scPDB).

13. Eric W. Sayers, Tanya Barrett, Dennis A. Benson, National Center for Biotechnology Information, National Library of Medicine, National Institutes of HealthAcceptedOctober13, 2009.(http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2808881.

14. http://vina.scripps.edu/manual.html.

15. Brice Dali Melalie Keita, Eugene Megnassan Vladimir Frecer Stanislav Miertus, Chemical Biology and Drug Design (http://www.ics.trieste.it/core-programmes/drug-design/publications/art-chemical-biology-09.aspx).

16. http://www.medicinenet.com/cox-2_inhibitors/article.htm.

17. Pub Med: Online Search Engine for science and biomedical articles, www.pubmedcentral.nih.gov.

Received on 15.11.2011 Modified on 10.12.2011

Asian J. Research Chem. 5(1): January 2012; Page 38-43