QSAR ANALYSIS OF STRUCTURALLY SIMILAR 1, 3, 4- …

www.wjpr.net Vol 3, Issue 6, 2014.

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Sawant et al. World Journal of Pharmaceutical Research

QSAR ANALYSIS OF STRUCTURALLY SIMILAR 1, 3, 4-

OXADIAZOLE/THIADIAZOLE AND 1, 2, 4-TRIAZOLE

DERIVATIVES OF BIPHENYL-4-YLOXY ACETIC ACID AS ANTI-

INFLAMMATORY AGENTS

1Ramesh L Sawant*, 2 Dnyaneshwar B Hardas, 2Karan K Pawa, 2Abhishek K Shinde

1Head, Department Of Pharmaceutical Chemistry and PG Studies,Pad. Dr. Vithalrao Vikhe

Patil Foundation’s College of Pharmacy,Vilad Ghat, M.I.D.C. Ahmednagar (MS) 2Department of Pharmaceutical Chemistry and PG studies,Pad. Dr.Vithalrao Vikhe Patil

Foundation’s College of Pharmacy, Vilad Ghat, Ahmednagar, (MS), India, 414111

ABSTRACT

Two dimensional (2D) and three dimenstinal (3D) QSAR analysis of

series of structurally similar 1, 3, 4- Oxadiazoles /thiadiazole and 1, 2,

4-triazole derivatives of biphenyl-4-yloxy acetic acid as anti-

inflammatory agents have been done using VLife MDS 4.3 software.

The compounds were divided into training and test set. Various models

were built by using Partial Least Square (PLS) regression analysis and

Principle Component Regression (PCR) analysis. Best QSAR model

was selected on the basis of various statistical parameters like square

correlation coefficient (r2), cross validated square correlation

coefficient (q2) and sequential Fischer test (F). The results of the 2D-

QSAR models were further compared with 3D-QSAR models

generated by Molecular Field Analysis coupled with partial least

square (PLS) detecting the substitutional requirements for the

favorable anti-inflammatory activity and providing useful information in the characterization

and differentiation of their binding sites. The results derived may be useful in further

designing novel anti-inflammatory agents prior to synthesis.

KEY WORDS: 2D and 3D QSAR, Descriptors, Anti-inflammatory activity, 1, 3, 4-

oxadiazoles/thiadiazole and 1, 2, 4-triazole derivatives of biphenyl-4-yloxy acetic acid.

World Journal of Pharmaceutical ReseaRch SJIF Impact Factor 5.045

Volume 3, Issue 6, 1844-1858. Research Article ISSN 2277 – 7105

Article Received on 22 June 2014, Revised on 17 July 2014, Accepted on 12 August 2014

*Correspondence for

Author

Dr. Ramesh.L.Sawant

Professor and Head,

Department Of Pharmaceutical

Chemistry and PG Studies,Pad.

Dr. Vithalrao Vikhe Patil

Foundation’s College of

Pharmacy,Vilad Ghat,

M.I.D.C. Ahmednagar (MS)


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INTRODUCTION

Non- steroidal anti-inflammatory drugs (NSAIDS) are still the most commonly prescribed

drugs Worldwide for the treatment of inflammatory diseases like rheumatoid arthritis,

osteoarthritis,orthopedic injuries, post operative pain and acute myalgias.Non-steroidal anti-

inflammatory drugs (NSAIDs) are widely used to treat the sign and symptoms of

inflammation,particularly arthritic pain. NSAIDs exert their anti-inflammatory effect mainly

through inhibition of cyclooxygenases (COXs), the key enzyme in prostaglandin (PG)

biosynthesis from arachidonic acid (AA). There are at least two COX isoforms COX-1 and

COX-2. Constitutive COX-1 is responsible for providing cytoprotection in gastrointestinal

(GI) tract whereas inducible COX-2 mediates inflammation. Traditional NSAIDs such as

aspirin, diclofenac, flurbiprofen and ibuprofen are non-selective; however, they show

greaterselectivity for COX-1 than COX-2. Therefore chronic use of NSAIDs may elicit

appreciable GI irritation, bleeding and ulceration. The incidence of clinically significant GI

side effects is high (over 30%) and causes some patients to abandon NSAID therapy. Thus

the discovery of COX-2 provided the rationale for the development of drugs devoid of GI

disorders while retaining clinical efficacy as anti-inflammatory agents. But the recent reports

showed that selective COX-2 inhibitors (coxibs) could lead to adverse cardiovascular effects.

Therefore, development of novel compounds having anti-inflammatory and analgesic activity

with improved safety profile is still a necessity[1].Hakan Bet al reported synthesis of series of

some new 1, 2, 4 triazole derivatives as anti-microbial agents[2]. Mihaela Met alreported

synthesis of some new 1, 3, 4 thiadiazole derivatives as anti-inflammatory agents[3].

Quantitative Structure activity relationship (QSAR) models are highly effective in describing

the structural basis of biological activity.It is now widely used for the prediction of

physicochemical properties and biological activities in chemical, environmental and

pharmaceutical areas.The success of QSAR approach can be explained by the insight

offeredinto the structural determination of chemical properties, and the possibility to estimate

theproperties of new chemical compounds without the need to synthesize and test them. Since

the biphenyl-4-yioxy acetic acid derivatives have potent anti-inflammatory activity so there is

a need to correlate anti-inflammatory activity and the physicochemical parameters of the

compound by QSAR methods for increasing the potency of future molecules.


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Table 1 Structure of 21 Compounds with their Biological Activities

Sr No Structure % inhibition

1

15.90

2

52.27

3

81.81

4

18.18

5

31.81

6

79.54


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7

59.09

8

54.54

9

27.27

10

54.54

11

63.63

12

29.54

13

29.54


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14

56.81

15

18.18

16

77.27

17

63.63

18

57.57

19

29.54

20

79.54

21

25.00


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MATERIALS AND METHODS

1. Biological activity data

Twenty one compounds from series of structurally similar 1, 3, 4-oxadiazole/thiadiazole and

1, 2, 4-triazole derivatives of biphenyl-4-yloxy acetic acid as anti-inflammatory agents were

selected from literature reported by Kumar Het al[4]. The experimental biological activities, in

the form of percentage inhibition of paw volume were converted into logarithmic form and

used as dependent variable for development of valid 2D QSAR and 3D QSAR models. Table

1 shows the 21 compounds with their percentage inhibition of paw edema values.

2. Geometry optimization

Three-dimensional quantitative structure activity relationship studies of structurally similar 1,

3, 4-oxadiazole/thiadiazole and 1, 2, 4-triazole as derivatives of biphenyl-4-yloxy acetic acid

were carried out by using Molecular Design Suite software version 4.3. The 3D structures of

all compounds have been constructed using VLife MDS 4.3 and their geometries were

subsequently optimized to make the conformations having least potential energy[5]. Energy

minimizations were performed using Merck Molecular Force Field (MMFF) and MMFF

charge for the atom followed by considering distance-dependent dielectric constant of 1.0 and

convergence criteria (rms gradient) of 0.01kcal/mol[6].

3. Alignment of molecules

All molecules in the data set were aligned by template-based method where a template is

built by considering common substructures in the series. The basic structure of biphenyl-4-

yloxy acetic acid template is shown in Fig.1. Highly bioactive energetically stable derivative

in this class of compounds is chosen as a reference molecule Fig. 2 on which other molecules

in the data set are aligned, considering template as a basis for the alignment Fig.3. The 2D

and 3D descriptors for each optimized molecule were calculated by “compute descriptor and

“calculate descriptor” module of the software and selected descriptors are shown in Table 2

and Table 3 respectively.


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Fig 1 Template

Fig 2 Reference molecule

Fig 3: Align molecules


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Table 2. Selected Molecular 2D Descriptors Sr No SssNHE-index VolumeCount SulfursCount

1 3.0939 11.366 0 2 2.9128 12.652 0 3* 0 11.866 1 4* 0 13.580 1 5 0 14.2 1 6 0 11.966 0 7 0 13.152 1 8 0 13.366 1 9 0 13.866 1

10* 3.4108 11.866 1 11* 3.4145 13.580 1 12 3.4172 14.2 1 13 3.2297 13.152 1 14 3.4374 13.366 1

15* 3.4646 13.866 1 16 0 12.680 0 17 0 12.680 0 18 0 13.395 0 19 0 14.228 0

20* 0 14.966 0 21 0 15.8 0

* Test set compounds

Table 3. Selected Molecular 3D Descriptors

Sr No E281 S27 E612 1 0.0162 -8.3126 0.0690 2 0.0257 -8.5470 -0.2691 3* 0.0285 -8.5334 0.7042 4* 0.0265 -8.8019 -0.2325 5 0.0270 -8.7708 -0.2194 6 0.0117 -8.8293 -0.3131 7 0.0172 -8.8564 -0.2277 8 0.0188 -9.1092 -0.2336 9 0.0048 -8.5289 -0.5504

10* 0.0197 -8.8555 -0.4660 11* 0.0182 -8.8571 -0.4750 12 0.0235 -8.8520 -0.4484 13 0.0086 -8.6696 -0.5581 14 0.0342 -8.8233 -0.3310

15* 0.0119 -7.1029 0.0527 16 0.0191 -7.1328 0.0714 17 0.0098 -7.0951 0.0601 18 0.0172 -7.1315 0.0835 19 0.0153 -7.7552 0.0478

20* 0.0463 -8.2862 -0.0470 21 -0.0031 -8.1381 -0.1897



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4. Activity prediction

The predictability of the QSAR model would be good if the values of percentage inhibition of

paw edema predicted by the QSAR model do not appreciably differ from the observed results

of percentage inhibition of paw edema for the given data set. Quality of selected models was

further ascertained by r2, q2, F test. The QSAR models were evaluated using statistical

measures such as ‘n’ represents number of observations, f is the degree of freedom, r is the

square root of the multiple R-squared for regression, q2 is the cross validated correlation

coefficient.

5. Computational details

2D QSAR

The structures were sketched using 2D Draw application and were exported to QSAR plus

through MDS path. Three- dimensional structures of all the molecules were generated. For

2D QSAR, used optimized molecule in 2D sheet and added log value of percentage paw

edema inhibition. All the calculated descriptors were considered as independent variable and

logaritmic value of percentage inhibition as dependent variable. Using random selection

method and manual selection method training and test set was selected. Training set of

15molecules and test set of 6 molecules used. Partial Least Square (PLS) and Principle

Component Regression (PCR) methods were used to perform QSAR analysis to generate

several models[7].

3D QSAR

Several 3D-QSAR techniques such as comparative molecular field analysis (COMFA),

comparative molecular similarity analysis (COMSIA), k-nearest neighbor (kNN) are being

used in modern QSAR research[8]. In the present study, molecular field analysis coupled with

partial least square (PLS) was applied to obtain a 3D QSAR model, PLS is frequently used as

the regression method in 3D-QSAR. The calculated electrostatic field descriptors were used

as independent variables and logarithmicvalues of percentage inhibition were used as

dependent variables in partial least squares regression analysis to derive the 3D-QSAR

models.


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RESULTS AND DISCUSSION

A. 2D QSAR model

Log of % inhibition=-0.0991(±0.0202)SssNHE-index + 0.4159(±0.0434) VolumeCount +

0.4159(±0.0434)SulfursCount n = 15, r2= 0.9811, q2= 0.8970, Pred. r2= 0.9603, F test =

56.49.

Model 1

The Model 1 suggest that the anti inflammatory activity ofstructurally similar 1, 3, 4-

Oxadiazole/thiadiazole and 1, 2, 4-triazole derivatives of biphenyl-4-yloxy acetic

aciddependent on SssNHE-index, VolumeCount and SulfursCount descriptors. Out of that

SssNHE-index descriptors signify electrotopological state indices for number of –NH group

connected with 2 single bonds. VolumeCount descriptor signifies volume of compound and

SulfursCount descriptor signifies number of sulfur atom in a compound. Both the descriptors

that isVolumeCount and SulfursCount are positively contributing towards the biological

activity.The actual, predicted and residual biological activities of 2D QSAR model showed in

Table 6. The Fig.4 and Fig 5 shows comparative actual and predicted activity of training set

and test set compounds respectively through Radar plot. Fig 6 and Fig 7 shows contribution

plot and fitness plot respectively.

Fig 4: Radar plot of training set compounds for Model 1


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Fig 5: Radar plot of test set compounds for Model 1

Fig 6: Contribution plot for Model 1

Fig 7: Fitness plot for Model 1


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Table 4:Actual, Predicted and Residual Biological Activities for Model-1

Sr. No Actual Predicted Residual Sr. No Actual Predicted Residual 1 1.20 1.32 -0.11 12 1.47 1.56 -0.09 2 1.71 1.43 0.28 13 1.47 1.63 -0.16 3* 1.91 1.30 0.60 14 1.75 1.89 -0.13 4* 1.25 1.42 -0.16 15* 1.25 1.40 -0.15 5 1.50 1.20 0.30 16 1.88 1.33 0.55 6 1.90 1.90 0.00 17 1.80 1.42 0.38 7 1.77 1.72 0.05 18 1.76 1.75 0.00 8 1.73 1.69 0.03 19 1.47 1.40 0.06 9 1.43 1.56 -0.13 20* 1.90 1.90 -0.00

10* 1.73 1.69 0.03 21 1.39 1.30 0.08 11* 1.80 1.47 0.32


B. 3D QSAR model

Log % inhibition = 5.1928(±0.0063)E_281 - 6825.9200(±9036.8900)S_27 + 0.2546E_612

n = 15, r2 = 0.8812, q2 = 0.8521, Pred. r2 = 0.6241, F test = 49.32

Model2

The model-2 describes the optimum structural features for anti-inflammatory activity. The

E_281 and E_612 are the electrostatic field energy interaction between methyl probe and

compounds at their corresponding spatial grid points of 281 and 612. This model suggest that

electrostatic field descriptors E_281 and E_612 with positive coefficient indicate that the less

electropositive (electron deficient or electron withdrawing) groups are favorable in this

region. The S_27 is the steric descriptor which negatively contributes towards the biological

activity. It signifies that substitution of bulkier group in this region around descriptor S_27

with its grid point at 27 is not favorable for the activity. The actual, predicted and residual

biological activities of 3D QSAR model showed in Table 5. The Fig.8 and Fig.9 shows

comparative actual and predicted activity of training set compounds and test set

compoundsrespectively through Radar plot. Fig 10 and Fig 11 shows contribution plot and

fitness plot respectively, and Fig. 12 shows Molecular field analysis.


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Fig 8: Radar plot of training set compounds for Model 2

Fig 9: Radar plot of test set compounds for Model 2

Fig 10: Contribution plot for Model 2Fig 11: Fitness plot for Model 2.


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Fig 11: Molecular field analysis

Table 5:Actual, Predicted and Residual Biological Activities for Model-2

Sr. No Actual Predicted Residual Sr. No Actual Predicted Residual 1 1.20 1.67 -0.47 12 1.47 1.75 -0.28 2 1.71 1.65 0.06 13 1.47 1.61 -0.14

3* 1.91 1.98 -0.07 14 1.75 1.77 -0.01 4* 1.25 1.81 -0.55 15* 1.25 1.56 -0.30 5 1.50 1.81 -0.31 16 1.88 1.60 0.28 6 1.90 1.71 0.18 17 1.80 1.55 0.25 7 1.77 1.94 -0.17 18 1.76 1.59 0.16 8 1.73 1.98 -0.25 19 1.47 1.62 -0.15 9 1.43 1.18 0.25 20* 1.90 1.79 0.10

10* 1.73 1.43 0.29 21 1.39 1.49 -0.09 11* 1.80 1.29 0.50


CONCLUSION

The QSAR analysis of series of structurally similar 1, 3, 4-oxadiazole/thiadiazole and 1, 2, 4-

triazole derivatives of biphenyl-4-yloxy acetic acid as anti-inflammatory agents have revealed

that substitutions of electro positive group are essential for the activity on the ortho and para

position of biphenyl ring and also substitution of electropositive groups on first position of

five membered heterocyclic ring increases the biological activity. While substitution of bulky

group on para position of biphenyl ring retards the activity of compounds.

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