The nuclear protein poly(ADP-ribose) polymerase-1 (PARP-1) has a well-established role in the signaling and repair of DNA and is a prominent target in oncology, as testified by the number of candidates in clinical testing that unselectively target both PARP-1 and its closest isoform PARP-2. The goal of our program was to find a PARP-1 selective inhibitor that would potentially mitigate toxicities arising from cross-inhibition of PARP-2. Thus, an HTS campaign on the proprietary Nerviano Medical Sciences (NMS) chemical collection, followed by SAR optimization, allowed us to discover 2-[1-(4,4-difluorocyclohexyl)piperidin-4-yl]-6-fluoro-3-oxo-2,3-dihydro-1H-isoindole-4-carboxamide (NMS-P118, 20by). NMS-P118 proved to be a potent, orally available, and highly selective PARP-1 inhibitor endowed with excellent ADME and pharmacokinetic profiles and high efficacy in vivo both as a single agent and in combination with Temozolomide in MDA-MB-436 and Capan-1 xenograft models, respectively. Cocrystal structures of 20by with both PARP-1 and PARP-2 catalytic domain proteins allowed rationalization of the observed selectivity.

Multidrug resistance mediated by ATP binding cassette (ABC) transporters such as P-glycoprotein (P-gp) represents a serious problem for the development of effective anticancer drugs. In addition, P-gp has been shown to reduce oral absorption, modulate hepatic, renal, or intestinal elimination, and restrict blood-brain barrier penetration of several drugs. Consequently, there is a great interest in anticipating whether drug candidates are P-gp substrates or inhibitors. In this respect, two different computational models have been developed. A method for discriminating P-gp substrates and nonsubstrates has been set up based on calculated molecular descriptors and multivariate analysis using a training set of 53 diverse drugs. These compounds were previously classified as P-gp substrates or nonsubstrates on the basis of the efflux ratio from Caco-2 permeability measurements. The program Volsurf was used to compute the compounds' molecular descriptors. The descriptors were correlated to the experimental classes using partial least squares discriminant analysis (PLSD). The model was able to predict correctly the behavior of 72% of an external set of 272 proprietary compounds. Thirty of the 53 previously mentioned drugs were also evaluated for P-gp inhibition using a calcein-AM (CAM) assay. On the basis of these additional P-gp functional data, a PLSD analysis using GRIND-pharmacophore-based descriptors was performed to model P-gp substrates having poor or no inhibitory activity versus inhibitors having no evidence of significant transport. The model was able to discriminate between 69 substrates and 56 inhibitors taken from the literature with an average accuracy of 82%. The model allowed also the identification of some key molecular features that differentiate a substrate from an inhibitor, which should be taken into consideration in the design of new candidate drugs. These two models can be implemented in a virtual screening funnel.

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Cdc7 kinase is a key regulator of the S-phase of the cell cycle, known to promote the activation of DNA replication origins in eukaryotic organisms. Cdc7 inhibition can cause tumor-cell death in a p53-independent manner, supporting the rationale for developing Cdc7 inhibitors for the treatment of cancer. In this paper, we conclude the structure-activity relationships study of the 2-heteroaryl-pyrrolopyridinone class of compounds that display potent inhibitory activity against Cdc7 kinase. Furthermore, we also describe the discovery of 89S, [(S)-2-(2-aminopyrimidin-4-yl)-7-(2-fluoro-ethyl)-1,5,6,7-tetrahydropyrrolo[3,2-c]pyridin-4-one], as a potent ATP mimetic inhibitor of Cdc7. Compound 89S has a Ki value of 0.5 nM, inhibits cell proliferation of different tumor cell lines with an IC50 in the submicromolar range, and exhibits in vivo tumor growth inhibition of 68% in the A2780 xenograft model.