Scleractinian coral stylophora pistillata carbonic anhydrase (STPCA) enzyme is a secreted isoform, plays a direct role in bio-mineralization. Sulfonamides, including some clinically used derivatives are the most important class of STPCA inhibitors. In order to search for efficient STPCA inhibitors molecules, the present work deals with quantitative structure-activity relationship (QSAR) studies of a series of 36 bioactive molecules. A heuristic algorithm selects the best multiple linear regression (MLR) equation showed the correlation between the observed values and the calculated values of activity is very good (N=36, Se=0.1683, r(2)=0.9158, F=54.3809, r(cv)(2)=0.8569). The novelty of this work is not only to explore the structural attributes of bioactive molecules but also to design and predict in silico the STPCA inhibitory activity of new not yet synthesized compounds. The analyzed prediction set includes many molecules having greater computed activity than observed value of inhibitory activity.

Chemometric QSAR modeling and in silico design of carbonic anhydrase inhibition of a coral secretory isoform by sulfonamide / S. Singh;C. T. Supuran. - In: BIOORGANIC & MEDICINAL CHEMISTRY. - ISSN 0968-0896. - STAMPA. - 21:(2013), pp. 1495-1502. [10.1016/j.bmc.2012.09.001]

Chemometric QSAR modeling and in silico design of carbonic anhydrase inhibition of a coral secretory isoform by sulfonamide.

SUPURAN, CLAUDIU TRANDAFIR
2013

Abstract

Scleractinian coral stylophora pistillata carbonic anhydrase (STPCA) enzyme is a secreted isoform, plays a direct role in bio-mineralization. Sulfonamides, including some clinically used derivatives are the most important class of STPCA inhibitors. In order to search for efficient STPCA inhibitors molecules, the present work deals with quantitative structure-activity relationship (QSAR) studies of a series of 36 bioactive molecules. A heuristic algorithm selects the best multiple linear regression (MLR) equation showed the correlation between the observed values and the calculated values of activity is very good (N=36, Se=0.1683, r(2)=0.9158, F=54.3809, r(cv)(2)=0.8569). The novelty of this work is not only to explore the structural attributes of bioactive molecules but also to design and predict in silico the STPCA inhibitory activity of new not yet synthesized compounds. The analyzed prediction set includes many molecules having greater computed activity than observed value of inhibitory activity.
2013
21
1495
1502
S. Singh;C. T. Supuran
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/776405
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