Abstract

Urokinase-type plasminogen activator (uPA), a trypsin-like serine protease, has been implicated in large number of malignancies, tumor cell invasion, angiogenesis and metastasis; hence, the potent and selective inhibitors of uPA may therefore be therapeutically useful drugs for treatment of various forms of cancer. A three-dimensional quantitative structure-activity relationship (3D QSAR) study was performed on five different chemical series reported as selective uPA inhibitors employing comparative molecular field analysis (CoMFA)/comparative molecular similarity indices analysis (CoMSIA) techniques to investigate the structural requirements for substrates and derive a predictive model that may be used for the design of novel uPA inhibitors. ClogP has been used as an additional descriptor in the CoMFA analysis to study the effects of lipophilic parameters on activity. Inclusion of ClogP did not improve the models significantly and exhibited comparable correlation coefficients with CoMFA steric and electrostatic models. 3D QSAR models were derived for 2-pyridinylguanidines (training set N = 25, test set N = 8), 4-aminoarylguanidines and 4-aminoarylbenzamidines (training set N = 29, test set N = 8), thiophene-2-carboxamindines (training set N = 64, test set N = 19), 2-naphthamidines (training set N = 32, test set N = 8), and 1-isoquinolinylguanidines (training set N = 29, test set N = 7). The CoMFA models with steric and electrostatic fields exhibited r(2)(cv) 0.452-0.722, r(2)(ncv) 0.812-0.986, r(2)(pred) 0.597-0.870, whereas CoMFA ClogP models showed r(2)(cv) 0.420-0.707, r(2)(ncv) 0.849-0.957, r(2)(pred) 0.600-0.870. The CoMSIA models displayed r(2)(cv) 0.663-0.729, r(2)(ncv) 0.909-0.998, r(2)(pred) 0.554-0.855. 3D contour maps generated from these models were analyzed individually, which provides the regions in space where interactive fields may influence the activity. The superimposition of contour maps on the active site of serine proteases additionally helps in understanding the structural requirements of these inhibitors. Further, the predictive ability of 3D QSAR models was affirmed by predicting the activity of novel 2-naphthamidines. 3D QSAR models developed may be used in designing and predicting the uPA inhibitory activity of novel molecules.

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