The growth and metastasis of solid tumors are dependent on angiogenesis. The vascular endothelial growth factor (VEGF) is of particular interest since it is essential for angiogenesis. The development of novel inhibitors of VEGF receptor type 2 (VEGFR-2) is important. Quantitative structure-activity relationship (QSAR) studies were performed to understand the structural factors affecting inhibitory potency of 4-aryl-5-cyano-2-aminopyrimidines. Pharmacophore models indicate that the importance of steric and hydrogen bond acceptor groups. The bestfitted pharmacophore-based alignment was used for comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Both CoMFA (q 2 = 0.62, r 2 = 0.87, and r 2 predictive = 0.7) and CoMSIA (q 2 = 0.54, r 2 = 0.86, and r 2 predictive = 0.61) gave reasonable results. Factors such as steric bulkiness, electrostatic effect, and hydrogen bond acceptor were found to be important for the inhibitory activity. It is suggested that negatively charged, bulky H-bond accepting groups around the piperazine nitrogen would enhance inhibition against VEGFR-2.

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Protein kinase B (PKB; also known as Akt kinase) is located downstream in the PI-3 kinase pathway. Overexpression and constitutive activation of PKB/Akt leads to human prostate, breast and ovarian carcinomas. A series of 69 PKB/Akt inhibitors were examined to explore their binding modes using FlexX, and three-dimensional quantitative structure-activity relationship (3D-QSAR) studies based on comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed to provide structural insights into these compounds. CoMFA produced statistically significant results, with cross-validated q ( 2 ) and non-cross validated correlation r(2) coefficients of 0.53 and 0.95, respectively. For CoMSIA, steric, hydrophobic and hydrogen bond acceptor fields jointly yielded 'leave one out' q(2) = 0.51 and r(2) = 0.84. The predictive power of CoMFA and CoMSIA was determined using a test set of 13 molecules, which gave correlation coefficients, r(2)(predictive) of 0.58 and 0.62, respectively. Molecular docking revealed that the binding modes of these molecules in the ATP binding sites of the Akt kinase domain were very similar to those of the co-crystallized ligand. The information obtained from 3D contour maps will allow the design of more potent and selective Akt kinase inhibitors.

Small molecules often have toxicities that are a function of molecular structural features. Minor variations in structural features can make large difference in such toxicity. Consequently, in silico techniques may be used to correlate such molecular toxicities with their structural features. Relative to nine different sets of aromatic nitro compounds having known observed toxicities against different targets, we developed ligand-based 2D quantitative structure-toxicity relationship models using 20 selected topological descriptors. The topological descriptors have several advantages such as conformational independency, facile and less time-consuming computation to yield good results. Multiple linear regression analysis was used to correlate variations of toxicity with molecular properties. The information index on molecular size, lopping centric index and Kier flexibility index were identified as fundamental descriptors for different kinds of toxicity, and further showed that molecular size, branching and molecular flexibility might be particularly important factors in quantitative structure-toxicity relationship analysis. This study revealed that topological descriptor-guided quantitative structure-toxicity relationship provided a very useful, cost and time-efficient, in silico tool for describing small-molecule toxicities.