ABSTRACT
Amyloid fibrils are found in systemic amyloidosis diseases such as Alzheimer's disease, Parkinson's disease, and type II diabetes. Currently, these diseases are diagnosed by observation of fibrils or plaques, which is an ineffective method for early diagnosis and treatment of disease. The goal of this study was to develop a simple and quick method to predict the possibility and speed of fibril formation before its occurrence. Oligomers generated from seven representative peptide segments were first isolated and detected by ion-mobility mass spectrometry (IM-MS). Then, their assemblies were disrupted using formic acid (FA). Interestingly, oligomers that showed small ion intensity changes upon FA addition had rapid fibril formation. By contrast, oligomers that had large ion intensity changes generated fibrils slowly. Two control peptides (aggregation/no fibrils and no aggregation/no fibrils) did not show changes in their ion intensities, which confirmed the ability of this method to predict amyloid formation. In summary, the developed method correlated MS intensity ratio changes of peptide oligomers on FA addition with their amyloid propensities. This method will be useful for monitoring peptide/protein aggregation behavior and essential for their mechanism studies.
ABSTRACT
Androgen receptor (AR) is a ligand-activated transcription factor that plays a pivotal role in the development and progression of many severe diseases such as prostate cancer, muscle atrophy, and osteoporosis. Binding of ligands to AR triggers the conformational changes in AR that may affect the recruitment of coactivators and downstream response of AR signaling pathway. Therefore, AR ligands have great potential to treat these diseases. In this study, we searched for novel AR ligands by performing a docking-based virtual screening (VS) on the basis of the crystal structure of the AR ligand binding domain (LBD) in complex with its agonist. A total of 58 structurally diverse compounds were selected and subjected to LBD affinity assay, with five of them (HBP1-3, HBP1-17, HBP1-38, HBP1-51, and HBP1-58) exhibiting strong binding to AR-LBD. The IC values of HBP1-51 and HBP1-58 are 3.96 µM and 4.92 µM, respectively, which are even lower than that of enzalutamide (Enz, IC = 13.87 µM), a marketed second-generation AR antagonist. Further bioactivity assays suggest that HBP1-51 is an AR agonist, whereas HBP1-58 is an AR antagonist. In addition, molecular dynamics (MD) simulations and principal components analysis (PCA) were carried out to reveal the binding principle of the newly-identified AR ligands toward AR. Our modeling results indicate that the conformational changes of helix 12 induced by the bindings of antagonist and agonist are visibly different. In summary, the current study provides a highly efficient way to discover novel AR ligands, which could serve as the starting point for development of new therapeutics for AR-related diseases.