QSAR STUDIES ON NOVEL 1, 4-DIHYDROPYRIDINE DERIVATIVESHTML Full Text
QSAR STUDIES ON NOVEL 1, 4-DIHYDROPYRIDINE DERIVATIVES
Asma Samaunnisa A.*1, C.H.S. Venkataramana 1 and V. Madhavan 2
Department of Pharmaceutical Chemistry, Department of Pharmacognosy, M.S. Ramaiah College of Pharmacy, Bangalore, India
ABSTRACT:QSAR studies on N3, N5-diphenyl-1, 4-dihydropyridine-3, 5-dicarbohydrazides [2A-2D’] and 2, 6-dimethyl-1,4-dihydro-pyridine-3, 5-yl-bis[carbonyl-2-(phenyl)]pyrazolidine-3, 5-diones] [3A -3D’] were carried out. 3D chemical structures were given as input and desired molecular attributes and molecular indices were selected. Various molecular descriptors were studied using TSAR (Tools for Structure Activity Relationship) Accelrys Discovery studio software. All the properties were calculated based on the chemical structure. Hansch equations were developed for all the above mentioned compounds against respective microorganisms and for anti-inflammatory activities, using some of the calculated descriptors. A correlation matrix was developed, which gives the inter correlation between the calculated descriptors.
1,4-Dihydropyridine, Pyrazolidine-3,5-Diones, QSAR studies, Hansch equation, Correlation matrix
INTRODUCTION:1, 4-Dihydropyridines and their analogues are well known for their diverse activities like antibacterial, antifungal, anti-hypertensive, anticonvulsant, anti-inflammatory, anticancer etc 1-6. The structural formula of an organic compound basically encodes within it all the information that predetermines the chemical, biological and physical properties of that compound 7.
The characteristic of various biological activities exhibited by the same basic nucleus owes to the presence of a number of varying substituents. Biological activity of a molecule is profoundly influenced by various substituents present. So,there exists a relationship between molecular structure and biological response 8.
The biological activity of a molecule differs accordingly, with changes in the substituents. An extensive study on any class of molecules is required to develop a quantitative structure and activity relationship. This has provided us with a direction to the research.
The rationale behind this project was to carry out QSAR study of N3, N5-diphenyl-1,4-dihydropyridine-3, 5-dicarbo hydrazides [2A-2D’] 9 and 2, 6-dimethyl-1,4-dihydropyridine-3,5-yl-bis[carbonyl-2-(phenyl)] pyrazolidine-3, 5-diones] [3A-3D’] 10 derivatives. Hansch equations for antimicrobial as well as anti-inflammatory activities were developed using Accelrys TSAR Software. Correlation matrix was also developed with the aid of this software by using the calculated molecular descriptors.
MATERIALS AND METHODS 7, 11: Tsar is an integrated analysis package for interactive investigation of Quantitative Structure-Activity Relationships (QSARs). It is intended to provide all the functions required to carry out any QSAR investigation.
TSAR uses an integrated approach to provide all components together. It uses a chemically aware spreadsheet to store and manipulate different types of data. The main application of this software is to develop Hansch equation for a given training set compounds and this equation can be used for the future generation compounds to obtain biological activity data without being synthesized. This rational approach will allow us to synthesize compounds with good biological activity. Regression analysis module of statistical analysis tool TSAR was used to build the QSAR models.
Regression analysis was performed using zone of inhibition as independent variable and calculated descriptors as dependent variables. QSAR models were derived after ensuring reasonable correlation of zone of inhibition with individual descriptor and minimum inter-correlation among the descriptors used in the derived models. The use of more than one variable in multivariate equation was justified by autocorrelation study. In the present study various statistical measures were used such as n = number of compounds; r = coefficient of correlation; s = standard error; f = test for quality to fit.
All the properties are calculated based on the chemical structure and a Hansch equation is developed using some of the calculated descriptors. The following structures are first drawn using DS Viewer Pro Suite software and their smiles strings are appended into TSAR software. Substitutions for the derivatives are given in Table 1.
TABLE 1: SET OF COMPOUNDS FOR TSAR STUDY
RESULTS AND DISCUSSION: Various Molecular attributes calculated and biological activities for the set of compounds 2A-2D’ and 3A-3D’ are given in the following figures 1-10.
FIGURE 1: MOLECULAR ATTRIBUTES FOR THE SET 2A-2D’
FIGURE 2: MOLECULAR ATTRIBUTES FOR THE SET 2A-2D’
FIGURE 3: MOLECULAR ATTRIBUTES FOR THE SET 3A-3D’
FIGURE 4: MOLECULAR ATTRIBUTES FOR THE SET 3A-3D’
FIGURE 5: OBSERVED BIOLOGICAL ACTIVITY FOR THE SET 2A-2D’
FIGURE 6: PREDICTED BIOLOGICAL ACTIVITY FOR THE SET 2A-2D’
FIGURE 7: OBSERVED BIOLOGICAL ACTIVITY FOR THE SET 3A-3D’
FIGURE 8: PREDICTED BIOLOGICAL ACTIVITY FOR THE SET 3A-3D’
FIGURE 9: OBSERVED AND PREDICTED % INHIBITION OF ALBUMIN DENATURATION FOR THE SET 2A-2D’
FIGURE 10: OBSERVED AND PREDICTED % INHIBITION OF ALBUMIN DENATURATION FOR THE SET 3A-3D’
Totally 14 Hansch equations were developed based on the above molecular descriptors, observed and predicted biological activities which are given in the following tables 2 and 3.
TABLE 2: HANSCH EQUATIONS FOR ANTIMICROBIAL AND ANTI-INFLAMMATORY ACTIVITIES FOR THE SET OF COMPOUNDS 2A-2D’
|BA = 0.0086299218*X1+1.2655897*X2-1.5737636*X3+0.02968015*X4+4.1891551||Staphylococcus aureus|
|BA = 0.006181885*X1+0.54577816*X2+0.54216611*X3+0.020884452*X4+4.1868463||Bacillus subtillus|
|BA = 0.0077026109*X1+0.77354515*X2-0.62876654*X3+0.033232186*X4+3.1347725||E. Coli|
|BA= 0.0011946505*X1+0.034694269*X2+1.1057063*X3+0.0057437047*X4+11.016533||Proteus vulgaris|
|BA= -0.0072026318*X1-1.3829733*X2-0.64852422*X3-0.021038659*X4+21.532642||Aspergillus niger|
(BA=Biological activity, X1= Molecular surface area, X2=LogP, X3=Total Lipole, X4=molar refractivity)
TABLE 3: HANSCH EQUATIONS FOR ANTIMICROBIAL AND ANTI-INFLAMMATORY ACTIVITIES FOR THE SET OF COMPOUNDS 3A-3D’
|BA = 0.00090397045*X1+0.46999887*X2+0.17540462*X3+0.01102224*X4+6.448936||Bacillus subtillus|
|BA =0.003513477*X1+0.40956402*X2+0.13441697*X3+0.012577558*X4+6.2336264||E. Coli|
|BA = -0.006993338*X1-0.29975083*X2-0.12470307*X3-0.025773037*X4+21.625942||Proteus vulgaris|
|BA = 0.00897035*X1+0.1751522*X2+0.085003294*X3+0.021848412*X4+3.2972562||Aspergillus niger|
|BA = 0.0044008382*X1+0.31588811*X2+0.11829211*X3+0.013429222*X4+7.327291||Candida albicans|
(BA=Biological activity, X1= Molecular surface area, X2=LogP, X3=Total Lipole, X4=molar refractivity)
For all the above equations given in tables 2 and 3, the positive values of the descriptors X1, X2, X3, X4 implies that they contribute positively to the antimicrobial activity against corresponding microorganism or anti-inflammatory activity against % inhibition of albumin denaturation. The Negative values of the descriptors X1, X2, X3, X4 implies that they contribute negatively to the antimicrobial activity against corresponding microorganism or anti-inflammatory activity against % inhibition of albumin denaturation. By selecting various molecular attributes, correlation matrix is obtained which gives the inter correlation between the chosen calculated descriptors. Correlation matrix for the set of compounds 2A-2D’ and 3A-3D’ are shown in figures 11 and 12.
FIGURE 11: CORRELATION MATRIX FOR THE SET 2A-2D’
FIGURE 12: CORRELATION MATRIX FOR THE SET 3A-3D’
CONCLUSION: Various molecular attributes were calculated for the 16 above mentioned derivatives. Using which, Correlation matrix was obtained. Observed Biological activities were given as input and then using TSAR software predicted biological activities were calculated. Using these results Hansch (QSAR) equations were developed. From the equations it can be concluded that almost all of the equations shows positive contribution towards the selected microorganism for antibacterial activity and % inhibition of albumin denaturation for anti-inflammatory activity.
By using regression analysis of zone of inhibition as independent variable, QSAR equations were developed for the activity against each of the microorganism studied as well as for the % inhibition of albumin denaturation. Using this data promising leads can be obtained and the biological activity data for which can be calculated without the compound being synthesized.
ACKNOWLEDGEMENTS: I am grateful to express my sincere thanks to the GEF (medical), the Management and staff of M.S. Ramaiah College of Pharmacy, Bangalore for providing all the facilities and encouragement for carrying out the work.
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- Help files AccelrysAccord for Excel 6.1, TSAR 3.3
- Hansch C and Fujita TP: A method for the correlation of biological activity and chemical structure. J. Am. Chem. Soc 1964; 86: 1616-1626.
- Asma Samaunnisa A, Venkataramana C.H.S and Madhavan V: Synthesis, characterization and biological evaluation of novel N3, N5-diphenyl-1,4-dihydropyridine-3,5-dicarbohydrazide derivatives. International Journal of Research in Pharmacy and Chemistry 2013; 3 (1): 160-167.
- Asma Samaunnisa A, Venkataramana C.H.S and Madhavan V: Synthesis, characterization and biological evaluation of novel derivatives of bis pyrazolidine-3,5-dione tethered with 1,4-dihydropyridine moiety. CIOP 2013; 2 (2): 36-42.
- M. Pharm thesis: Asma Samaunnisa A: Design, synthesis and biological evaluation of novel bis pyrazolidine
How to cite this article:
Asma Samaunnisa A, Venkataramana CHS and Madhavan V: QSAR studies on novel 1, 4-dihydropyridine derivatives. Int J Pharm Sci Res 2013: 4(8); 3057-3064. doi: 10.13040/IJPSR. 0975-8232.4(8).3057-64
All © 2013 are reserved by International Journal of Pharmaceutical Sciences and Research. This Journal licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
Asma Samaunnisa A.*, C.H.S. Venkataramana and V. Madhavan
Department of Pharmaceutical Chemistry, M.S. Ramaiah College of Pharmacy, Bangalore, India
30 March, 2013
14 May, 2013
26 July, 2013
01 August, 2013