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The artificial neural network (ANN), or simply neural network, is a machine learning method evolved from the idea of simulating the human brain. The data explosion in modem drug discovery research requires sophisticated analysis methods to uncover the hidden causal relationships between single or multiple responses and a large set of properties. The ANN is(More)
BACKGROUND Resistance to mericitabine (prodrug of HCV NS5B polymerase inhibitor PSI-6130) is rare and conferred by the NS5B S282T mutation. METHODS Serum HCV RNA from patients who experienced viral breakthrough, partial response, or nonresponse in 2 clinical trials in which patients received mericitabine plus peginterferon alfa-2a (40KD)/ribavirin were(More)
The cyclin-dependent kinases (CDKs) and their cyclin partners are key regulators of the cell cycle. Since deregulation of CDKs is found with high frequency in many human cancer cells, pharmacological inhibition of CDKs with small molecules has the potential to provide an effective strategy for the treatment of cancer. The 2,4-diamino-5-ketopyrimidines 6(More)
The beneficial effects of thyroid hormone (TH) on lipid levels are primarily due to its action at the thyroid hormone receptor β (THR-β) in the liver, while adverse effects, including cardiac effects, are mediated by thyroid hormone receptor α (THR-α). A pyridazinone series has been identified that is significantly more THR-β selective than earlier(More)
TARGETING PPIS: A novel strategy for designing libraries targeting protein-protein interfaces enabled us to identify diverse chemical entry points to interact with therapeutic targets for which conventional screening libraries delivered no or only few hit structures. The concept was experimentally validated by early hit evaluation in biochemical screens and(More)
A new molecular lipoaffinity descriptor was introduced in this paper to account for the effect of molecular hydrophobicity on blood-brain barrier penetration. The descriptor was defined based on Kier and Hall's atom-type electrotopological state indices. Its evaluation requires 2-D molecular bonding information only. A multiple linear regression equation(More)
The development of small-molecule MDM2 inhibitors to restore dysfunctional p53 activities represents a novel approach for cancer treatment. In a previous communication, the efforts leading to the identification of a non-imidazoline MDM2 inhibitor, RG7388, was disclosed and revealed the desirable in vitro and in vivo pharmacological properties that this(More)
Finding an accurate method for estimating the affinity of protein ligands activity is the most challenging task in computer-aided molecular design. In this study we investigate and compare seven different prediction methods for a set of 30 glycogen phosphorylase (GP) inhibitors with known crystal structures. Five of the methods involve quantitative(More)
A simple QSPR model, based on seven 1D and 2D descriptors and artificial neural network, was developed for fast evaluation of aqueous solubility. The model was able to predict the molar solubility of a diverse set of 1312 organic compounds with an overall correlation coefficient of 0.92 and a standard deviation of 0.72 log unit between the calculated and(More)
In an attempt to develop predictive models for Hansch substituent constants for less common substituents, neural network QSPR (Quantitative Structure-Property Relationship) studies were conducted to correlate Hansch substituent constants for hundreds of chemically diverse functional groups with two different molecular descriptor sets. The Hansch substituent(More)