Journal of Pharmacy And Bioallied Sciences
Journal of Pharmacy And Bioallied Sciences Login  | Users Online: 1531  Print this pageEmail this pageSmall font sizeDefault font sizeIncrease font size 
    Home | About us | Editorial board | Search | Ahead of print | Current Issue | Past Issues | Instructions | Online submission

Year : 2010  |  Volume : 2  |  Issue : 1  |  Page : 27-31 Table of Contents     

QSAR studies of benzofuran/benzothiophene biphenyl derivatives as inhibitors of PTPase-1B

1 F/O Pharmacy, Rajendra Institute of Technology and Sciences, Sirsa-125055, India
2 Medicinal Chemistry Division, C.D.R.I., Lucknow-226001, India

Date of Submission03-Feb-2010
Date of Decision15-Feb-2010
Date of Acceptance25-Feb-2010
Date of Web Publication23-Apr-2010

Correspondence Address:
D Kaushik
F/O Pharmacy, Rajendra Institute of Technology and Sciences, Sirsa-125055
Login to access the Email id

Source of Support: UGC, Conflict of Interest: None

DOI: 10.4103/0975-7406.62703

Rights and Permissions

Objectives : Insulin resistance is associated with a defect in protein tyrosine phosphorylation in the insulin signal transduction cascade. The PTPase enzyme dephosphorylates the active form of the insulin receptor and thus attenuates its tyrosine kinase activity, therefore, the need for a potent PTPase inhibitor exists, with the intention of which the QSAR was performed. Materials and Methods : Quantitative structure-activity relationship (QSAR) has been established on a series of 106 compounds considering 27 variables, for novel biphenyl analogs, using the SYSTAT (Version 7.0) software, for their protein tyrosine phosphatase (PTPase-1B) inhibitor activity, in order to understand the essential structural requirement for binding with the receptor. Results : Among several regression models, one per series was selected on the basis of a high correlation coefficient (r, 0.86), least standard deviation (s, 0.234), and a high value of significance for the maximum number of subjects (n, 101). Conclusions : The influence of the different physicochemical parameters of the substituents in various positions has been discussed by generating the best QSAR model using multiple regression analysis, and the information thus obtained from the present study can be used to design and predict more potent molecules as PTPase-1B inhibitors, prior to their synthesis.

Keywords: Benzofuran / Benzothiophene, PTPase-1B inhibitor, QSAR

How to cite this article:
Kaushik D, Kumar R, Saxena A K. QSAR studies of benzofuran/benzothiophene biphenyl derivatives as inhibitors of PTPase-1B. J Pharm Bioall Sci 2010;2:27-31

How to cite this URL:
Kaushik D, Kumar R, Saxena A K. QSAR studies of benzofuran/benzothiophene biphenyl derivatives as inhibitors of PTPase-1B. J Pharm Bioall Sci [serial online] 2010 [cited 2022 Dec 9];2:27-31. Available from:

Diabetes has been recognized as a genetic disorder, in which the glucose metabolism is altered. The ability of insulin to bring about such a dramatic reversal in the symptoms of diabetes, with a return to a near normal life expectancy led the medical community to conclude that the problems of etiology and treatment had been resolved, but these conclusions were premature. While insulin did return control of the blood glucose level and did offset the development of ketoacidosis, it did not appear to rectify all the metabolic defects. [1]

It is thus evident that insulin therapy, as currently practiced, is not the panacea for diabetes mellitus. This realization has promoted a great deal of research toward the development of more effective ways of treating the disease, which has led to the discovery of various hypoglycemic agents, for example, Sulfonylurea, Biguanide, and more recently, glitazones.

It is now well established that insulin resistance can result from a defect in the insulin receptor signaling system at a site post binding of insulin to its receptor. [2] Insulin resistance is associated with a defect in protein tyrosine phosphorylation in the insulin signal transduction cascade. [3] This defect in tyrosine phosphorylation in the insulin-responsive muscle, tissue, liver, and adipose, causes a reduction in the metabolic actions of insulin and hyperglycemia. This decrease in protein tyrosine phosphorylation in the cells does not appear to be due to an inherent problem in the insulin receptor (IR) tyrosine kinase, but instead is caused by an elevation in the protein phosphate activity.

The PTPase enzyme dephosphorylates the active form of the insulin receptor and thus attenuates its tyrosine kinase activity. [4]

Various research articles published on compounds possessing the PTPase inhibition activity, such as, phosphotyrosine bioisostere, [5] phosphonic acid derivative, [6] vanadium compounds, [7] benzofuran / benzothiophene derivative, [8] 11-aryl benzo[b] naptho (2,3d) furan and 11-arylbenzo[b]naptho (2,3d) thiophene, [9] and azolidinedione. [10] From overviewing all these various classes of compounds, we can suggest the general structure of PTPase 1B inhibitors as given in [Figure 1] .

Insulin resistance is thus one of the obstacles that we confront while undergoing therapy for diabetes mellitus. A number of PTPase inhibitors have been designed and studied to overcome this problem, to gain an insight into the structural and molecular requirements influencing the PTPase-1B inhibition activity; we herein describe the QSAR analysis of a set of structurally different compounds of PTPase inhibitors, for which it is conceivable to make an assumption that they interact with the enzyme.

   Materials and Methods Top

In silico studies

Malamas et al. [8] reported seven series of compounds based on benzofuran/benzothiophene biphenyl moiety. We had performed the QSAR analysis of all these series having 138 compounds, out of which only 106 compounds could be subjected to 2-D QSAR analysis, because of the non-availability of physicochemical substituent values and exact IC 50 values for some substituted compounds. The 2D QSAR study was carried out in the following steps:

Calculations of physicochemical constants

The values for the physicochemical constants for various substituents were determined from the literature. [11] The determined parameters for a series included, the Hansch constant (π), Molar Refractivity (h), Sigma / Hammet constant (s), Field effect (F), and the Indicator value (I).

To get the generated model we had clubbed all the series together for the sake of simplicity. We had designated different rings and positions as shown in the chemical structures, as (U, V, W, X) and (a, b, c, d, e, f), respectively. To simplify and make all the series collinear to each other the use of the indicator variable had been included. Thus, the compounds of the seven series were designated as follows:

Series I: As to x of V ring [Figure 2], we had assigned this position as [a], which was either oxygen or sulfur, so we had considered O=1 and S=0 as the indicator variable, V aI .

R 1 substitution was assigned as [b], so different physicochemical parameters were designated on the basis of ring and position, as πVb , σV b , and ηV b .

R 2 substitution position was [c], so the presence of an aceto moiety had been considered as an indicator variable with value 1 and the others as 0, and hence this position was considered as X cI (where X-ring, c-position, I- indicator). The parameters for the substituents on this aceto moiety had been designated as πXcI , σX cI , ηX cI , FX cI . Due to the substitution on the aceto moiety, there occurred the presence of a chiral center, due to which most of the compounds were enantiomers. Therefore, an indicator variable X cEI , (R=1, S=1, dl=0) was included, where the X-ring, c-position, E-enantiomer, I-indicator variable, and the value of X cEI= 1, -1, 0 depended on the optical rotation.

Series II: Similar to the first series, V aI was considered as an indicator variable [Figure 3].

R 1 position of the second series was considered as [d], so different parameters for the R 2 position had been designated as πXd , σX d , ηX d , FX d .

R 2 position was [e], so parameters of R 2 position were πXe , σX e , ηX e , FX e .

R 3 position was designated as X cI , X cEI, πXcI , σX cI , ηX cI , FX cI.

Series III: Benzofuran attached to biphenyl through the X linkage [Figure 4], which was designated as [f], so the corresponding parameters were πf, sf, hf, Ff.

Similarly the R 2 position was [d] and the parameters were πXd , σX d , ηX d , FX d

Position [e] was πXe , σX e , ηX e , FX e

Position [c] was X cI.

Series IV: R 1 position [Figure 5] was [c], so the earlier assigned R 1 position was an indicator variable, as X cI,, and its substitutions were as πXcI , σX cI , ηX cI , FX cI

R 2 and R 3 position parameters were πXd , σX d , ηX d , FX d and πXe , σX e , ηX e , FX e respectively.

As the isoxazole ring attached to either at third or fourth position, the indicator variable position was assigned as VW pI (position of attachment of V and W rings as indicator parameters at the fourth position as 1, and at the third position as 0).

Series V: R 1 position [Figure 6] was earlier designated as X cI, πXcI , σX cI , ηX cI , FX cI

R 2 position was [e] here and thus parameter R 2 position was termed as πXe , σX e , ηX e , FX e

The X group linkage between benzofuran and the naphthalene ring position was designated as [f], so the parameter of the X group became πf, σf, ηf, Ff.

Series VI: As R 1 , on the phenyl sulfono ring [Figure 7] was attached to position [c] of ring X, the R 1 position was assigned to X c3R 1 (X-ring, c-position, 3-third position of the phenyl ring, and R as the indicator).

Wherever R 1 was -OH, X c3R 1 =1, For -COOH, X c3R 1 =0

Similarly R 2 was X c4R 2

Wherever R 2 was COOH, there Xc4R 2 =1,

Wherever R 2 was OH, there Xc4R 2 =0

R 3 was [d] position and thus the parameter of R 3 position was designated as πXd , σX d , ηX d , FX d

R 4 was [e] position and thus the parameters were πXe , σX e , ηX e , FX e .

As x was in a V ring, which was assigned position [a], the indicator variable V aI

was considered.

V aI =1, when X=O

=0, when X=S

Series VII: Similar to the sixth series except that R 5 was taken as V aI [Figure 8] wherever the benzofuran ring comes

V aI =1, when R 5 was benzofuran

V aI =0, when R 5 was either Benzothiophene or other.

However, when it was considered to club all 26 variables of the series, in the fifth series the biphenyl ring was replaced by a naphthalene ring, and the presence of the biphenyl ring was considered as variable Iwx

Iwx =1, where the W, X rings are present as biphenyl

=0, where the W, X rings are present as naphthalene

Thus for all 106 compounds, the value of the substituent constant for all 27 variables was obtained from literature.

Determination of the correlation matrix

The correlation matrix for all the 27 variables along with the biological activity was determined using the program 'SYSTAT' (version 7.0). [12] The most significant parameters of the PTPase inhibiting activity were chosen on the basis of their correlation ship and Interco relationship.

Multiple regression analysis

It was performed by using the program 'SYSTAT' for the PTPase inhibiting activity, that is, -LogIC50 was considered as a dependent variable and all the 27 physicochemical parameters were considered as independent variables.

   Results and Discussion Top

The correlation matrix [Table 1] reveals the dependency of various parameters on the biological activity and among themselves. Those which have a high value of correlation ship for biological activity and the least Inter-corelationship between themselves are considered for multiple regression analysis. The multiple regression analysis is generated following the QSAR model:

-LogIC50 =0.020( 0.004) ηV b + 0.297 ( 0.041) πXd - 0.057( 0.18) ηf

+ 0.546( 0.113) Xc3R 1 + 0.069( 0.105)

n=101, r=0.86, s=0.234, F=42.697

The derived QSAR equation showed a very good r (correlation coefficient) value of 0.86 with 76.93% of the variation in biological activity being explained by the equation. This was associated with a low value of standard error of estimate, s, of 0.23. The equation was found to be highly statistically significant, with an F-test value of 42.697 and the critical F-test value at 99.95% confidence limit being 4.82.

Five compounds were considered as outliers because of high residual and leverage values. Perusal of the above-mentioned equation indicated that molar refractivity at the V b position and the hydrophobic substituent at the X d position contributed positively to the biological activity, while any substitution between biphenyl and benzofuran / benzothiophene, that is, at the f position had a detrimental effect on the biological activity of the compounds. The model also suggested that substitution on the aceto moiety also had a positive contribution for biological activity, as suggested by the QSAR model. These findings were in agreement with the pharmacophore model, as reported earlier, which suggested that the benzofuran / benzothiophene ring should be attached directly to biphenyl, which should have some phenyl moiety attached to it.

A different set of descriptors may give a different correlation with activity and this must be considered while interpreting the equation. The QSAR equation generated presently for Benzofuran Biphenyl is in agreement with the literature reports for ligand requirements based on the Structure-Activity Relationships (SAR). Furthermore, this equation provides a mathematical tool for designing compounds with better activity. Thus from the QSAR model, appropriate variations of the substituent at various positions can be effected to obtain an effective molecule, which may be remarkable to experimentally confirm the predictive power of the QSAR model by actual synthesis and its biological evaluation of the most potent theoretical compound.

   Conclusion Top

The regression model shows that the molar refractivity and hydrophobic substituent at the V b and X d positions, respectively, are the significant descriptors responsible for describing the downregulation of PTPase 1B. Besides this, any substitution between biphenyl and benzofuran / benzothiophene has a detrimental effect on the biological activity, which is also an important parameter to be taken into consideration while designing new inhibitors belonging to the above said class of compounds. The QSAR model is statistically and chemically sound and explains more than 95% variance in experimental activity. Finally, it can be concluded that the study presented here will play an important role in understanding the relationship of the physicochemical parameters with the structure and biological activity of the PTPase 1B inhibitor and will help in choosing a suitable substituent for obtaining the active compound with maximum potency.

   Acknowledgment Top

The authors thank the Director, CDRI, Lucknow for providing the necessary facilities. D.Kaushik is grateful to UGC for providing financial assistance for this project.

   References Top

1.Foye WO. Principles of Medicinal Chemistry. 3 rd ed. Mumbai: Varghese Publishing House; 1989.   Back to cited text no. 1      
2.Haring HU. The Insulin receptor: Signaling mechanism and contribution to the pathogenesis of insulin resistance. Diabetologia 1991;34:848-61.  Back to cited text no. 2      
3.Byon JC, Kusari AB, Kusari J. Protein- tyrosine phosphatase-1B acts as a negative regulator of insulin signal transduction. Mol Cell Biol 1998;182:101-8.  Back to cited text no. 3      
4.Goldstein BJ. Protein- Tyrosine Phosphatases and the regulation of insulin action. J Cell Biochem 1992;31:33-42.   Back to cited text no. 4      
5.Bieasdale JE, Ogg D, Palazuk BJ, Jacob CS, Swanson ML, Wong XY, et al. Small molecule peptidomimetics containing a novel phosphotyrosine bioisostere inhibit protein tyrosine phosphatase !B and augment insulin action. Biochem 2001;40:5642-54.   Back to cited text no. 5      
6.Leblanc Y. Phosphonic acid derivatives as inhibitors of protein tyrosine phosphatase 1B (PTP-1B). WO/2001/046205. 2001 June 28.  Back to cited text no. 6      
7.Evans JL, Jallal B. Their role in insulin action and potential as drug targets. Expert Opin Investing Drugs 1999;8:139-60.   Back to cited text no. 7      
8.Malamas MS, Sredy J, Moxham C, Katz A, Xu W, McDevitt R, et al. Novel benzofuran and benzothiophene biphenyls as inhibitors of protein tyrosine phosphatase 1B with antihyperglycemics properties. J Med Chem 2000;43:1293-310.  Back to cited text no. 8      
9.Wrobel J, Sredy J, Moxham C, Dietrich A, Li Z, Sawicki DR, et al. PTP1B inhibition and antihyperglycemics activity in the ob/ob mouse model of novel 11-arylbenzo[b]naptho[2,3d]furans and 11-arylbenzo[b]naptho[2,3-d] thiophenes. J Med Chem 1999;42:3199-202.  Back to cited text no. 9      
10.Malamas MS, Sredy J, Gunawan I, Mihan B, Sawicki DR, Seestaller L, et al. New azolidinediones as inhibitors of protein tyrosine phosphatase 1B with antihyperglycemic properties. J Med Chem 2000;43:995-1010.  Back to cited text no. 10      
11.Hansch C, Leo A. Substituent constants for correlation analysis in chemistry and biology. New York: John Wiley and Sons; 1979.  Back to cited text no. 11      
12.Systat (version 7.0), S.P.S.S., Inc., 944, North Michigan Avenue, Chicago, IL 60611.U.S.  Back to cited text no. 12      


  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7], [Figure 8]

  [Table 1]


    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

  In this article
    Materials and Me...
    Results and Disc...
    Article Figures
    Article Tables

 Article Access Statistics
    PDF Downloaded268    
    Comments [Add]    

Recommend this journal