Ranyao Yang

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In this study two genistein derivatives (G1 and G2) are reported as inhibitors of acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE), and differences in the inhibition of AChE are described. Although they differ in structure by a single methyl group, the inhibitory effect of G1 (IC50=264 nmol/L) on AChE was 80 times stronger than that of G2(More)
To determine chemical-protein interactions (CPI) is costly, time-consuming, and labor-intensive. In silico prediction of CPI can facilitate the target identification and drug discovery. Although many in silico target prediction tools have been developed, few of them could predict active molecules against multitarget for a single disease. In this(More)
Butyrylcholinesterase (BuChE, EC is an important pharmacological target for Alzheimer's disease (AD) treatment. However, the currently available BuChE inhibitor screening assays are expensive, labor-intensive, and compound-dependent. It is necessary to develop robust in silico methods to predict the activities of BuChE inhibitors for the lead(More)
Exposure to chronic stress increases the likelihood of developing depression, but the underlying mechanisms remain equivocal. While recent evidence has indicated that Neuregulin-1 (NRG1) and its ErbB receptors play an essential role in neural development and function, and NRG1 has emerged as a novel modulator involved in the response of brain to stress,(More)
Cyclin-dependent kinase 5 (CDK5) has emerged as a principal therapeutic target for Alzheimer’s disease. It is highly desirable to develop computational models that can predict the inhibitory effects of a compound towards CDK5 activity. In this study, two machine learning tools (naive Bayesian and recursive partitioning) were used to generate four single(More)
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