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Rho Kinase (ROCKII) has been recently implicated in several cardiovascular diseases prompting several attempts to discover and optimize new ROCKII inhibitors. Towards this end we explored the pharmacophoric space of 138 ROCKII inhibitors to identify high quality pharmacophores. The pharmacophoric models were subsequently allowed to compete within quantitative structure-activity relationship (QSAR) context. Genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of accessing self-consistent QSAR of optimal predictive potential (r (77) = 0.84, F = 18.18, r (LOO) (2)  = 0.639, r (PRESS) (2) against 19 external test inhibitors = 0.494). Two orthogonal pharmacophores emerged in the QSAR equation suggesting the existence of at least two binding modes accessible to ligands within ROCKII binding pocket. Receiver operating characteristic (ROC) curve analyses established the validity of QSAR-selected pharmacophores. Moreover, the successful pharmacophores models were found to be comparable with crystallographically resolved ROCKII binding pocket. We employed the pharmacophoric models and associated QSAR equation to screen the national cancer institute (NCI) list of compounds Eight submicromolar ROCKII inhibitors were identified. The most potent gave IC(50) values of 0.7 and 1.0 μM.

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High expression of Nek2 has been detected in several types of cancer and it represents a novel target for human cancer. In the current study, structure-based pharmacophore modeling combined with multiple linear regression (MLR)-based QSAR analyses was applied to disclose the structural requirements for NEK2 inhibition. Generated pharmacophoric models were initially validated with receiver operating characteristic (ROC) curve, and optimum models were subsequently implemented in QSAR modeling with other physiochemical descriptors. QSAR-selected models were implied as 3D search filters to mine the National Cancer Institute (NCI) database for novel NEK2 inhibitors, whereas the associated QSAR model prioritized the bioactivities of captured hits for in vitro evaluation. Experimental validation identified several potent NEK2 inhibitors of novel structural scaffolds. The most potent captured hit exhibited an [Formula: see text] value of 237 nM.

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