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RETRACTED

This article has been retracted as it is essentially identical in technical content with a previously published paper titled “QSAR Study on Inhibitors of Enzyme Ribonucleoside Diphosphate Reductase”, by “VED PRAKASH SINGH, DURGA NATH DHAR, RAVI KUMAR SRIVASTAVA” in “Asian Journal of Chemistry”, Volume 21, Issue 10, pp. 2052–2058, 2009.

E-Journal of Chemistry
Volume 7 (2010), Issue 3, Pages 953-961
http://dx.doi.org/10.1155/2010/254539

DFT Based QSAR Study of Enzyme Ribonucleoside Diphosphate Reductase

Mohiuddin Ansari, Ahmad Khalid Raza Khan, and Suhail Ahmad Khan

Maharani Lal Kunwari Post Graduate College, Balrampur, U.P., India

Received 21 July 2009; Revised 22 October 2009; Accepted 15 December 2009

Copyright © 2010 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Quantum chemical descriptors such as heat of formation, energy of HOMO, total energy, absolute hardness and chemical potential in different combinations have been used to develop QSAR models of inhibitors of enzyme ribonucleoside diphosphate reductase, RDR. The inhibitors are mainly derivatives of 1-formylisoquinoline thiosemicarbazone and 2-formylpyridine thiosemicarbazone. The values of various descriptors have been evaluated with the help of Win MOPAC 7.21 software using DFT method. Multiple linear regression analysis has been made with the help of above mentioned descriptors using the same software. Regression equations have been found to be successful models as indicated by the regression coefficient r2 having the value as high as 0.96 and cross validation coefficient rCV2 having the value approaching 0.95. The value of these two coefficients is indicative of high order of reliability for the proposed prediction. The results obtained are also validated on account of the closeness of observed and predicted inhibitory activities. The best combination of descriptors is heat of formation, total energy and energy of HOMO. Thus the prediction of suitability of inhibitors of the enzyme RDR can be made with the help of the best regression equation.