American Journal of Pharmacological Sciences
ISSN (Print): 2327-6711 ISSN (Online): 2327-672X Website: http://www.sciepub.com/journal/ajps Editor-in-chief: Srinivas NAMMI
Open Access
Journal Browser
Go
American Journal of Pharmacological Sciences. 2013, 1(2), 29-34
DOI: 10.12691/ajps-1-2-3
Open AccessArticle

Designing of Novel 6(H)-1,3,4-Thiadiazine Derivatives as MMP12 Inhibitors: A MLR and Docking Approach

Ajeet ., Laxmi Tripathi and Praveen Kumar,

Pub. Date: April 03, 2013

Cite this paper:
Ajeet ., Laxmi Tripathi and Praveen Kumar. Designing of Novel 6(H)-1,3,4-Thiadiazine Derivatives as MMP12 Inhibitors: A MLR and Docking Approach. American Journal of Pharmacological Sciences. 2013; 1(2):29-34. doi: 10.12691/ajps-1-2-3

Abstract

Here 6(H)-1,3,4-thiadiazine analogues have been used to correlate the inhibiting constant with the eccentric connectivity index (ECI), fragment complexity (FC), McGowan volume (MG) and topological polar surface area (TPSA) for studying the quantitative structure activity relationship (QSAR). Correlation may be an adequate predictive model which can help to provide guidance in designing and subsequently yielding greatly specific compounds that may have reduced side effects and improved pharmacological activities. The literature survey revealed that there are so many models available for MMP-1, MMP-2, MMP-3, MMP-7, MMP-8, MMP-9 and MMP-13, but QSAR model in respect of MMP-12 inhibition was necessity. We have used multiple linear regression (MLR) for developing QSAR model. For the validation of the developed QSAR model, statistical analysis such as cross validation test, standard deviation, quality factor, fischers test, root mean square deviation (RMSD), variance; and internal validation such as Y-randomization test have been performed and all the tests validated this QSAR model with fraction of variance r2 = 0.9364 and LOO-CV variance q2= 0.9146. Thirteen novel 6(H)-1,3,4-thiadiazine analogues have been designed and their inhibiting constant have been calculated with the developed QSAR model. It was found that the calculated inhibiting constant of these analogues were within the same range as of the training set. Further, these 6(H)-1,3,4-thiadiazine analogues have been docked with the catalytic domain of human matrix metalloproteinase (MMP12) which shows better docking score as compared to the (N-hydroxy-2-(N-hydroxyethyl)biphenyl-4-ylsulfonamido) acetamide, a MMP12 inhibitor. The results suggested that the designed novel 6(H)-1,3,4-thiadiazine analogues could be developed as a good MMP12 inhibitors.

Keywords:
6(H)-134-thiadiazine analogues QSAR MLR docking MMP12 inhibitors

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Figures

Figure of 5

References:

[1]  Verma, R.P.,Hansch, C., “Matrix metalloproteinases (MMPs): Chemical–biological functions and (Q)SARs,” Bioorg. Med. Chem, 15, 2223-2268, 2007.
 
[2]  Belaaouaj A, Shipley J.M., Kobayashi D.K., Zimonjic D.B., Popescu N., Silverman G.A., Shapiro S.D., “Human macrophage metalloelastase. Genomic organization, chromosomal location, gene linkage, and tissue-specific expression,” J. Biol. Chem, 270 (24), 14568–14575, 1995.
 
[3]  Verma, R.P.,Hansch, C., “QSAR modeling of taxane analogues against colon cancer,” Eur. J. Med. Chem. 45, 1470-1477, 2010.
 
[4]  Sardana, S.,Madan, A.K., “Topological models for prediction of antihypertensive activity of substituted benzylimidazoles,” J. Mol.Struct, 638, 41-49, 2003.
 
[5]  Gregg, S.,Eiso, A.B., Jan, S., “Integration of fragment screening and library design,” Drug Discovery Today, 12(23/24), 1032-1039, 2007.
 
[6]  Abraham, H. M., Ibrahim, A.,Zissimos, M. A., ”Determination of sets of solute descriptors from chromatographic measurements.,” Jour. Chromat, 1037, 29-47, 2004.
 
[7]  Hou, T.J.,Xu X.J., “ADME Evaluation in Drug Discovery. 3. Modeling Blood-Brain Barrier Partitioning Using Simple Molecular Descriptors,” J. Chem. Inf. Comput. Sci, 43, 2137-2152, 2003.
 
[8]  Sharma, J.,Ramanathan, K.,Rao, S., “Identification of Potential Inhibitors against Acetylcholinesterase Associated With Alzheimer's Diseases: A Molecular Docking Approach,” J. Comput. Method Mol. Design, 1(1), 44-51, 2011.
 
[9]  Yap, C.W., 2011. “PaDEL-descriptor: An open source software to calculate molecular descriptors and fingerprints,” J. Comput. Chem. 32(7), 1466-1474, 2011.