Hybrid neural network approaches to predict drug-target binding affinity for drug repurposing: screening for potential leads for Alzheimer's disease.

Alzheimer's disease (AD) is a neurodegenerative disease that primarily affects elderly individuals. Recent studies have found that sigma-1 receptor (S1R) agonists can maintain endoplasmic reticulum stress homeostasis, reduce neuronal apoptosis, and enhance mitochondrial function and autophagy, making S1R a target for AD therapy. Traditional experimental methods are costly and inefficient, and rapid and accurate prediction methods need to be developed, while drug repurposing provides new ways and options for AD treatment. In this paper, we propose HNNDTA, a hybrid neural network for drug-target affinity (DTA) prediction, to facilitate drug repurposing for AD treatment. The study combines protein-protein interaction (PPI) network analysis, the HNNDTA model, and molecular docking to identify potential leads for AD. The HNNDTA model was constructed using 13 drug encoding networks and 9 target encoding networks with 2506 FDA-approved drugs as the candidate drug library for S1R and related proteins. Seven potential drugs were identified using network pharmacology and DTA prediction results of the HNNDTA model. Molecular docking simulations were further performed using the AutoDock Vina tool to screen haloperidol and bromperidol as lead compounds for AD treatment. Absorption, distribution, metabolism, excretion, and toxicity (ADMET) evaluation results indicated that both compounds had good pharmacokinetic properties and were virtually non-toxic. The study proposes a new approach to computer-aided drug design that is faster and more economical, and can improve hit rates for new drug compounds. The results of this study provide new lead compounds for AD treatment, which may be effective due to their multi-target action. HNNDTA is freely available at https://github.com/lizhj39/HNNDTA.

Modified Sijunzi decoction in the treatment of ulcerative colitis in the remission phase: study protocol for a series of N-of-1 double-blind, randomised controlled trials.

BACKGROUND: Modified Sijunzi decoction (SJZD) has been used to treat ulcerative colitis (UC) in remission. However, more rigorous clinical trials are necessary to evaluate its effectiveness. Therefore, a series of single-case randomised controlled trials (N-of-1 trials) is proposed to compare the efficacy of modified SJZD with mesalazine for treating UC in remission. METHODS: This is a single-site, hospital-based, double-blind N-of-1 trial for 10 single subjects. Three cycles of N-of-1 trials are planned. There are two treatment periods in each cycle. Modified SJZD combined with mesalazine placebo or mesalazine combined with modified SJZD placebo will be randomised during each 8-week treatment period. There is no washout period in the study. Subjects will be selected by the researcher strictly in accordance with the inclusion and exclusion criteria. DISCUSSION: Paired t tests and mixed-effect models will be used to analyse the visual analogue scale (VAS) for clinical symptoms and the quality of life questionnaire responses. The findings will be interpreted with caution. We anticipate that the results will show that modified SJZD is effective for patients with UC in remission. TRIAL REGISTRATION: Chinese Clinical Trial Register, ID: ChiCTR1900024086. Registered on 24 June 2019.

A network pharmacology-based study on Alzheimer disease prevention and treatment of Qiong Yu Gao.

BACKGROUND AND OBJECTIVE: As the pathological mechanisms of AD are complex, increasing evidence have demonstrated Chinese Medicine with multi-ingredients and multi-targets may be more suitable for the treatment of diseases with complex pathogenesis. Therefore, the study was to preliminarily decipher the bioactive compounds and potential mechanisms of Qiong Yu Gao (QYG) for AD prevention and treatment by an integrated network pharmacology approach. METHODS: Putative ingredients of QYG and significant genes of AD were retrieved from public database after screening. Then QYG ingredients target proteins/genes were obtained by target fishing. Compound-target-disease network was constructed using Cytoscape to decipher the mechanism of QYG for AD. KEGG pathway and GO enrichment analysis were performed to investigate the molecular mechanisms and pathways related to QYG for AD treatments. RESULTS: Finally, 70 compounds and 511 relative drug targets were collected. In which, 17 representative direct targets were found. Gene ontology enrichment analysis revealed that the adenylate cyclase-inhibiting G-protein coupled acetylcholine receptor signaling pathway was the key biological processes and were regulated simultaneously by the 17 direct targets. The KEGG pathway enrichment analysis found that three signaling pathways were closely related to AD prevention and treatment by QYG, including PI3K-Akt signaling pathway, regulation of actin cytoskeleton pathway and insulin resistance pathway. CONCLUSION: This study demonstrated that QYG exerted the effect of preventing and treating AD by regulating multi-targets with multi-components. Furthermore, the study demonstrated that a network pharmacology-based approach was useful for elucidation of the interrelationship between complex diseases and interventions of Chinese herbal medicines.