Estrogen receptor α (ERα) is a successful target for ER‐positive breast cancer and also reported to be relevant in many other diseases. Selective estrogen receptor modulators (SERMs) make a good therapeutic effect in clinic. Because of the drug resistance and side effects of current SERMs, the discovery of new SERMs is given more and more attention. Virtual screening is a validated method to high effectively to identify novel bioactive small molecules. Ligand‐based machine learning methods and structure‐based molecular docking were first performed for identification of ERα antagonist from in‐house natural product library. Naive Bayesian and recursive partitioning models with two kinds of descriptors were built and validated based on training set, test set, and external test set and then were utilized for distinction of active and inactive compounds. Totally, 162 compounds were predicted as ER antagonists and were further evaluated by molecular docking. According to docking score, we selected 8 representative compounds for both ERα competitor assay and luciferase reporter gene assay. Genistein, daidzein, phloretin, ellagic acid, ursolic acid, (−)‐epigallocatechin‐3‐gallate, kaempferol, and naringenin exhibited different levels for antagonistic activity against ERα. These studies validated the feasibility of machine learning methods for predicting bioactivities of ligands and provided better insight into the natural products acting as estrogen receptor modulator, which are important lead compounds for future new drug design.

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 (IC50=21,210 nmol/L). Enzyme-kinetic analysis, molecular docking and molecular dynamics (MD) simulations were conducted to better understand the molecular basis for this difference. The results obtained by kinetic analysis demonstrated that G1 can interact with both the catalytic active site and peripheral anionic site of AChE. The predicted binding free energies of two complexes calculated by the molecular mechanics/generalized born surface area (MM/GBSA) method were consistent with the experimental data. The analysis of the individual energy terms suggested that a difference between the net electrostatic contributions (ΔE ele+ΔG GB) was responsible for the binding affinities of these two inhibitors. Additionally, analysis of the molecular mechanics and MM/GBSA free energy decomposition revealed that the difference between G1 and G2 originated from interactions with Tyr124, Glu292, Val294 and Phe338 of AChE. In conclusion, the results reveal significant differences at the molecular level in the mechanism of inhibition of AChE by these structurally related compounds.

Luteolin, a 3’,4’,5,7-tetrahydroxyflavone, is a plant flavonoid and pharmacologically active agent that has been isolated from several plant species. In the present study, the effects of luteolin obtained from the medicinal plant Elsholtzia rugulosa and the related mechanisms were examined in an Alzheimer's disease (AD) cell model. In this model, copper was used to exacerbate the neurotoxicity in β-amyloid precursor protein Swedish mutation stably overexpressed SH-SY5Y cells (named “APPsw cells” for short). Based on this model, we demonstrated that luteolin increased cell viability, reduced intracellular ROS generation, enhanced the activity of SOD and reversed mitochondrial membrane potential dissipation. Inhibition of caspase-related apoptosis was consistently involved in the neuroprotection afforded by luteolin. Furthermore, it down-regulated the expression of AβPP and lowered the secretion of Aβ_1-42. These results indicated that luteolin from the Elsholtzia rugulosa exerted neroprotective effects through mechanisms that decrease AβPP expression, lower Aβ secretion, regulate the redox imbalance, preserve mitochondrial function, and depress the caspase family-related apoptosis.