PREDICTING THE ANTI-INFLAMMATORY AND ANALGESIC ACTIVITY OF SOME BENZOTHIAZOLE DERIVATIVES USING 2D AND 3D QSAR ANALYSIS
Mahfoozur Rahman*, Ziyaul Haque, Dr. Rashid Akhtar, Dr. J. V. Musale, D. P. Patil, P. P. Nahar
ABSTRACT
A series of 21 molecules of Benzothiazole derivatives reported in literature Ashok kumar et al (2010) were used for development of 2D and 3D QSAR models. The data set of 20 molecules were divided into training and test set in the ratio of 70:30, The biological activity was converted to logarithmic scale (pIC50) in mathematical operation mode of the software. The statistically significant 2D-QSAR models for Analgesic activity are r2 =0.8578 and q2 = 0.7415 and on Anti inflammatory giving r2 = 0.9457 and q2 =0.9476. 3D QSAR results for internal (q2 = 0.9245, q2=0.8170) and external (predictive r2 = 0.6320, q2 = 0.7773) validation criteria. Thus, 3D QSAR models showed that electrostatic effects dominantly determine the binding affinities. 2D QSAR studies revealed that Saas CE Index descriptors were major contributing descriptor in case of analgesic activity and Xlog P in case of Anti inflammatory activity. By using kNN-MFA method. The results derived may be useful in further designing novel anti-cancer agents. After successful QSAR studies, attempts were made to predict the activities of the newly designed analogues of these reported compounds. In future we can synthesize these designed compounds using the selected scheme and confirm their activity by carrying out in vivo evaluation.
Keywords: Benzothiazole derivatives, Anti-inflammatory agents, 2D QSAR, 3D QSAR, kNN-MFA.
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