br Results and discussion CATALYST

Results and discussion CATALYST software allows automatic pharmacophore construction by using a collection of molecules with activities ranging over a number of orders of magnitude. In addition, CATALYST pharmacophores (hypotheses) explain the variability of bioactivity with respect to the geometric localization of the chemical features present in the molecules used to build it. The pharmacophore model consists of a collection of features necessary for the biological activity of the ligands arranged in 3D space (e.g., sodium fluoride australia acceptors and donors, hydrophobic regions, etc…). Different hypotheses were generated for a series of FBPase inhibitors. A total of 136 compounds were used in this study (Table 1) [32], [33], [34]; three training subsets were selected from the collection (Table 2) and each subset consisted of inhibitors of wide structural diversity. The biological activity in the training subsets spanned from 3.0 to 3.5 orders of magnitude.
Conclusions FBPase inhibitors are currently considered as potential treatments for diabetes. Recently, a potent derivative was reported to attenuate hyperglycemia in Zucker diabetic fatty rats [1]. The pharmacophoric space of FBPase inhibitors was explored via three diverse sets of inhibitors using CATALYST-HYPOGEN to identify high quality binding model(s). Two orthogonal pharmacophoric models suggest the existence of at least two distinct binding modes accessible to ligands within FBPase binding pocket. The selected pharmacophoric models were experimentally validated by the identification of several FBPase inhibitors retrieved via in silico screening. Our results suggest that the combination of pharmacophoric exploration and ROC analyses can be an useful tool for finding new diverse FBPase inhibitors.
Experimental
Introduction Fructose-1,6-bisphosphatase (FBPase; EC 3.1.3.11), catalyzing the irreversible reaction of hydrolysis of fructose 1,6-bisphosphate to fructose 6-phosphate and inorganic phosphate, is a regulatory enzyme of gluco- and glyconeogenesis (Tejwani, 1983, Dzugaj, 2006). Vertebrate genomes contain two distinct genes—fbp1 and fbp2, coding for two FBPase isozymes, while invertebrate genomes contain a single fbp locus (Tillmann et al., 2002). A protein product of fbp1 gene—FBP1 (also known as the liver FBPase), is expressed mainly in gluconeogenic organs, where it functions as a regulator of glucose synthesis from non-carbohydrates. The muscle isozyme—FBP2, is widely expressed also in non-gluconeogenic cells and it was initially viewed as a regulator of the glyconeogenic pathway. However, a growing body of research suggests that physiological function of FBP2 goes beyond participation in the synthesis of glucose/glycogen, and that the enzyme may be involved in regulation of cell mortality, division and differentiation (Gizak et al., 2009, Mamczur et al., 2012). The kinetic properties of both mammalian and avian isozymes are quite similar, except their sensitivity to the enzyme inhibitors. Mammalian and avian FBP2, in comparison to FBP1, is about 100 times more susceptible to the action of the allosteric inhibitors—AMP and NAD, and about 1000 times more sensitive to the inhibition by Ca (Gizak et al., 2004, Dzugaj, 2006). Moreover, calcium not only inhibits FBP2, but also disrupts the glyconeogenic complex in striated muscles, blocking resynthesis of glycogen (Mamczur et al., 2005). Kinetic and structural studies of FBPase muteins suggest that the key role in the high sensitivity of the muscle isozyme toward inhibition by Ca and AMP is played by Glu69 and non-acidic residue 20 (Lys or Thr), respectively (Zarzycki et al., 2007). These residues are present in all known vertebrate genome-derived FBP2 sequences. Thus, it might be expected that all vertebrate muscle FBPases should be regulated by the inhibitors similarly to mammalian FBP2. However, results of preliminary studies on amphibian FBP2 are somewhat confusing: the Pelophylax esculentus FBP2 is about 100 times less sensitive to Ca than mammalian muscle FBPase (Dziewulska-Szwajkowska and Dzugaj, 2010). On the other hand, it is still about 10-fold more sensitive than the liver isozyme.