A5089675765- Estrogen and related hormone effects
- Prostate Cancer Treatment and Research
- Computational Drug Discovery Methods
- Receptor Mechanisms and Signaling
- Protein Degradation and Inhibitors
- Cytokine Signaling Pathways and Interactions
- Machine Learning in Materials Science
- Hormonal and reproductive studies
- Protein Structure and Dynamics
- NF-κB Signaling Pathways
- Immune Response and Inflammation
- Environmental Impact and Sustainability
- Epigenetics and DNA Methylation
- Cancer therapeutics and mechanisms
- Vitamin D Research Studies
- Click Chemistry and Applications
- Tuberculosis Research and Epidemiology
- Stress Responses and Cortisol
- Cell Image Analysis Techniques
- Biochemical and Molecular Research
- Asthma and respiratory diseases
- Cancer-related gene regulation
- Vehicle emissions and performance
- Energy, Environment, and Transportation Policies
- Chemical Synthesis and Analysis
Zhejiang University
2018-2023
Zhejiang Lab
2020-2023
Central South University
2020
Abstract Machine learning-based scoring functions (MLSFs) have attracted extensive attention recently and are expected to be potential rescoring tools for structure-based virtual screening (SBVS). However, a major concern nowadays is whether MLSFs trained generic uses rather than given target can consistently applicable VS. In this study, systematic assessment was carried out re-evaluate the effectiveness of 14 reported in Overall, most these could hardly achieve satisfactory results any...
Abstract Inhibitors that form covalent bonds with their targets have traditionally been considered highly adventurous due to potential off-target effects and toxicity concerns. However, the clinical validation approval of many inhibitors during past decade, design discovery novel attracted increasing attention. A large amount scattered experimental data for reported, but a resource by integrating information inhibitor is still lacking. In this study, we presented Covalent Inhibitor Database...
Abstract Binding of different ligands to glucocorticoid receptor (GR) may induce conformational changes and even trigger completely opposite biological functions. To understand the allosteric communication within GR ligand binding domain, folding pathway helix 12 (H12) induced by agonist dexamethasone (DEX), antagonist RU486, modulator AZD9567 are explored molecular dynamics simulations Markov state model analysis. The can regulate volume activation function‐2 through residues Phe737 Gln738....
Machine-learning (ML)-based scoring functions (MLSFs) have gradually emerged as a promising alternative for protein-ligand binding affinity prediction and structure-based virtual screening. However, clouds of doubts still been raised against the benefits this novel type (SFs). In study, to benchmark performance target-specific MLSFs on relatively unbiased dataset, trained from three representative interaction representations were assessed LIT-PCBA classical Glide SP SF types ligand-based...
Abstract Androgen receptor (AR) is a ligand-activated transcription factor that plays pivotal role in the development and progression of many severe diseases such as prostate cancer, muscle atrophy, osteoporosis. Binding ligands to AR triggers conformational changes may affect recruitment coactivators downstream response signaling pathway. Therefore, have great potential treat these diseases. In this study, we searched for novel by performing docking-based virtual screening (VS) on basis...
Androgen receptor (AR) antagonists have been widely used for the treatment of prostate cancer (PCa). As a link between AR and its transcriptional function, activation function 2 (AF2) region has recently revealed as novel targeting site developing antagonists. Here, we reported series N-(4-(benzyloxy)-phenyl)-sulfonamide derivatives new-scaffold AF2. Therein, compound T1-12 showed excellent antagonistic activity (IC50 = 0.47 μM) peptide displacement 18.05 μM). Furthermore, in vivo LNCaP...
Androgen receptor (AR) has proved to be a vital drug target for treating prostate cancer. Here, we reported the discovery of novel AR antagonist 92 targeting ligand-binding pocket, but distinct from marketed enzalutamide (Enz), demonstrated inhibition on domain (LBD) dimerization, which is mechanism first time. First, hit (26, IC50 = 5.57 μM) was identified through virtual screening based theoretical LBD dimer bound with Enz model. Then, guided by molecular modeling, discovered 32.7-fold...
Recently, deep learning (DL)-based de novo drug design represents a new trend in pharmaceutical research, and numerous DL-based methods have been developed for the generation of novel compounds with desired properties. However, comprehensive understanding advantages disadvantages these is still lacking. In this study, performances different generative models were evaluated by analyzing properties generated molecules scenarios, such as goal-directed (rediscovery, optimization scaffold hopping...
Selective glucocorticoid receptor modulators (SGRMs), which can dissociate the transactivation from transrepression of (GR), are regarded as very promising therapeutics for inflammatory and autoimmune diseases. We previously discovered a SGRM HP-19 based on passive antagonistic conformation GR bioassays. In this study, we further analyzed dynamic changes state upon binding designed synthesized 62 N-acyl-6-sulfonamide-tetrahydroquinoline derivatives by structural optimization HP-19. Therein,...
As a major drug target for anti-inflammatory therapy, the glucocorticoid receptor (GR) regulates wide range of physiological processes through transactivation (TA) or transrepression. GR TA is involved in many adverse effects GR-targeting drugs, and therefore, discovery novel ligands with lower activity longer residence time quite urgent. Undoubtedly, understanding ligand dissociation mechanisms structural basis regulation crucial development drugs. Here, we used random accelerated molecular...
Background and Purpose: Androgen receptor (AR), a ligand-activated transcription factor, is master regulator in the development progress of prostate cancer (PCa). A major challenge for clinically used AR antagonists rapid emergence resistance induced by some point mutations ligand binding domain (LBD), therefore discovery novel anti-AR therapeutics that can combat mutation-induced quite demanding. Therein, blocking interaction between DNA represents an innovative strategy to overcome...