Effects of hyperglycemia on the TGF-ß pathway in trabecular meshwork cells.

BACKGROUND: Hyperglycemia, which can lead to apoptosis, hypertrophy, fibrosis, and induces hyperinflammation in diabetic vascular complications due to oxidative stress. In order to elucidate the potential dual roles and regulatory signal transduction of TGF-ß1 and TGF-ß2 in human trabecular meshwork cells (HTMCs), we established an oxidative cell model in HTMCs using 5.5, 25, 50, and 100 mM d-glucose-supplemented media and characterized the TGF-ß-related oxidative stress pathway. METHODS: Further analysis was conducted to investigate oxidative damage and protein alterations in the HTMC caused by the signal transduction. This was done through a series of qualitative cell function studies, such as cell viability/apoptosis analysis, intracellular reactive oxygen species (ROS) detection, analysis of calcium release concentration, immunoblot analysis to detect the related protein expression alteration, and analysis of cell fibrosis to study the effect of different severities of hyperglycemia. Also, we illustrated the role of TGF-ß1/2 in oxidative stress-induced injury by shRNA-mediated knockdown or stimulation with recombinant human TGF-ß1 protein (rhTGF-ß1). RESULTS: Results from the protein expression analysis showed that p-JNK, p-p38, p-AKT, and related SMAD family members were upregulated in HTMCs under hyperglycemia. In the cell functional assays, HTMCs treated with rhTGFß-1 (1 ng/mL) under hyperglycemic conditions showed higher proliferation rates and lower ROS and calcium levels. CONCLUSIONS: To summarize, mechanistic analyses in HTMCs showed that hyperglycemia-induced oxidative stress activated TGF-ß1 along with its associated pathway. GENERAL SIGNIFICANCE: While at low concentrations, TGF-ß1 protects cells from antioxidation, whereas at high concentrations, it accumulates in the extracellular matrix, causing further HTMC dysfunction.

TCMBank: bridges between the largest herbal medicines, chemical ingredients, target proteins, and associated diseases with intelligence text mining.

Traditional Chinese Medicine (TCM) has long been viewed as a precious source of modern drug discovery. AI-assisted drug discovery (AIDD) has been investigated extensively. However, there are still two challenges in applying AIDD to guide TCM drug discovery: the lack of a large amount of standardized TCM-related information and AIDD is prone to pathological failures in out-of-domain data. We have released TCM Database@Taiwan in 2011, and it has been widely disseminated and used. Now, we developed TCMBank, the largest systematic free TCM database, which is an extension of TCM Database@Taiwan. TCMBank contains 9192 herbs, 61 966 ingredients (unduplicated), 15 179 targets, 32 529 diseases, and their pairwise relationships. By integrating multiple data sources, TCMBank provides 3D structure information of ingredients and provides a standard list and detailed information on herbs, ingredients, targets and diseases. TCMBank has an intelligent document identification module that continuously adds TCM-related information retrieved from the literature in PubChem. In addition, driven by TCMBank big data, we developed an ensemble learning-based drug discovery protocol for identifying potential leads and drug repurposing. We take colorectal cancer and Alzheimer's disease as examples to demonstrate how to accelerate drug discovery by artificial intelligence. Using TCMBank, researchers can view literature-driven relationship mapping between herbs/ingredients and genes/diseases, allowing the understanding of molecular action mechanisms for ingredients and identification of new potentially effective treatments. TCMBank is available at https://TCMBank.CN/.

Proteomic and microbial assessments on the effect of Antrodia cinnamomea in C57BL/6 mice.

Antrodia cinnamomea (AC) is a nutraceutical fungus and studies have suggested that AC has the potential to prevent or alleviate diseases. However, little is known about the AC-induced phenotypes on the intestine-liver axis and gut microbial alterations. Here, we performed two-dimensional difference gel electrophoresis (2D-DIGE) and MALDI-Biotyper to elaborate the AC-induced phenotypes on the intestine-liver axis and gut microbial distribution of C57BL/6 mice. The experimental outcomes showed that the hepatic density may increase by elevating hepatic redox regulation, lipid degradation and glycolysis-related proteins and alleviating cholesterol biosynthesis and transport-related proteins in C57BL/6 mice with AC treatment. Moreover, AC facilitates intestinal glycolysis, TCA cycle, redox and cytoskeleton regulation-related proteins, but also reduces intestinal vesicle transport-related proteins in C57BL/6 mice. However, the body weight, GTT, daily food/water intake, and fecal/urine weight were unaffected by AC supplementation in C57BL/6 mice. Notably, the C57BL/6-AC mice had a higher gut microbial abundance of Alistipes shahii (AS) than C57BL/6-Ctrl mice. In summary, the AC treatment affects intestinal permeability by regulating redox and cytoskeleton-related proteins and elevates the gut microbial abundance of AS in C57BL/6 mice that might be associated with increasing hepatic density and metabolism-related proteins of the liver in C57BL/6 mice. Our study provides an insight into the mechanisms of AC-induced phenotypes and a comprehensive assessment of AC's nutraceutical effect in C57BL/6 mice.

Group Music Intervention Using Percussion Instruments to Reduce Anxiety Among Elderly Male Veterans with Alzheimer Disease.

BACKGROUND This study aimed to assess the impact of a group music intervention on anxiety and depression of elderly male veterans with dementia. MATERIAL AND METHODS In total, 50 elderly men with Alzheimer disease were randomly divided into intervention and control groups. Patients in the intervention group attended a 60-minute group music session that used percussion instruments with familiar music in the morning once a week for 12 weeks, whereas those in the control group received a rest and reading session at the same intervals and under the same conditions. The Hamilton Anxiety Rating Scale and Geriatric Depression Scale were used to assess anxiety and depression at baseline, week 6, and week 12. The Primary Measures of Music Audiation (PMMA) was used to assess musical aptitude at the baseline. RESULTS A significant reduction in the anxiety level following the 12-week music sessions was observed in the intervention group (P<.001), but there was no significant change in the control group. However, the change in depressive symptoms between the 2 groups was nonsignificant. In the intervention group, when stratifying patients based on music aptitude determined through PMMA assessment, patients with high PMMA scores had significantly reduced anxiety symptoms over time compared with those with low scores. CONCLUSIONS For elderly male veterans with dementia, participating in a group music intervention reduced anxiety symptoms. In patients with high musical aptitude, the treatment effects on anxiety reduction were satisfactory. Measures of music aptitude may provide valuable information regarding patients' response to music intervention.

Insight into potent leads for alzheimer's disease by using several artificial intelligence algorithms.

Several proteins including S-nitrosoglutathione reductase (GSNOR), complement Factor D, complement 3b (C3b) and Protein Kinase R-like Endoplasmic Reticulum Kinase (PERK), have been demonstrated to be involved in pathogenesis pathways for Alzheimer's disease (AD) and considered as potential treatment targets to AD. Based on the concept of multitargets, a network pharmacology-based approach was employed to investigate potential Traditional Chinese Medicine (TCM) candidates that can dock well with GSNOR, C3b, Factor D and PERK proteins. To predict the bioactivities of candidates, Artificial Intelligence (AI) algorithms composed of seven machine learning algorithms and a deep learning model were performed to validate the docking results. Furthermore, in this study, we propose a novel combined method for efficiently exploring the predicted results of AI algorithms. Besides, Comparative force field analysis (CoMFA) and comparative similarity indices analysis (CoMSIA) were performed to construct predicted models. The results show that the square correlation coefficients (R2) of all models are almost higher than 0.75, which also acquire good achievements on the test set. Moreover, the binding stability of the potential inhibitors were evaluated using 100 ns of MD simulation. Collectively, this study elucidate that the herbs Ardisia japonica, Ligusticum chuanxiong, Lippia nodiflora and Mirabilis jalapa containing 2,2'-[benzene-1,4-diylbis(methanediyloxybenzene-4,1-diyl)]bis(oxoacetic acid), Glyasperin B, Nodifloridin A, Miraxanthin III and l-Valine-l-valine anhydride might be a potential medicine formula for AD.

A novel artificial intelligence protocol to investigate potential leads for Parkinson's disease.

Previous studies have shown that small molecule inhibitors of NLRP3 may be a potential treatment for Parkinson's disease (PD). NACHT, LRR and PYD domains-containing protein 3 (NLRP3), heat shock protein HSP 90-beta (HSP90AB1), caspase-1 (CASP1) and cellular tumor antigen p53 (TP53) have significant involvement in the pathogenesis pathway of PD. Molecular docking was used to screen the traditional Chinese medicine database TCM Database@Taiwan. Top traditional Chinese medicine (TCM) compounds with high affinities based on Dock Score were selected to form the drug-target interaction network to investigate potential candidates targeting NLRP3, HSP90AB1, CASP1, and TP53 proteins. Artificial intelligence model, 3D-Quantitative Structure-Activity Relationship (3D-QSAR) were constructed respectively utilizing training sets of inhibitors against the four proteins with known inhibitory activities (pIC50). The results showed that 2007_22057 (an indole derivative), 2007_22325 (a valine anhydride) and 2007_15317 (an indole derivative) might be a potential medicine formula for the treatment of PD. Then there are three candidate compounds identified by the result of molecular dynamics.

Artificial Intelligence Approach To Investigate the Longevity Drug.

Longevity is a very important and interesting topic, and Klotho has been demonstrated to be related to longevity. We combined network pharmacology, machine learning, deep learning, and molecular dynamics (MD) simulation to investigate potent lead drugs. Related protein insulin-like growth factor 1 receptor (IGF1R) and insulin receptor (IR) were docked with the traditional Chinese medicine (TCM) database to screen out several novel candidates. Besides, nine different machine learning algorithms were performed to build reliable and accurate predicted models. Moreover, we used the novel deep learning algorithm to build predicted models. All of these models obtained significant R2, which are all greater than 0.87 on the training set and higher than 0.88 for the test set, respectively. The long time 500 ns molecular dynamics simulation was also performed to verify protein-ligand properties and stability. Finally, we obtained Antifebrile Dichroa, Holarrhena antidysenterica, and Gelsemium sempervirens, which might be potent TCMs for two targets.

Artificial Intelligence Approach to Find Lead Compounds for Treating Tumors.

It has been demonstrated that MMP13 enzyme is related to most cancer cell tumors. The world's largest traditional Chinese medicine database was applied to screen for structure-based drug design and ligand-based drug design. To predict drug activity, machine learning models (Random Forest (RF), AdaBoost Regressor (ABR), Gradient Boosting Regressor (GBR)), and Deep Learning models were utilized to validate the Docking results, and we obtained an R2 of 0.922 on the training set and 0.804 on the test set in the RF algorithm. For the Deep Learning algorithm, R2 of the training set is 0.90, and R2 of the test set is 0.810. However, these TCM compounds fly away during the molecular dynamics (MD) simulation. We seek another method: peptide design. All peptide database were screened by the Docking process. Modification peptides were optimized the interaction modes, and the affinities were assessed with ZDOCK protocol and Refine Docked protein protocol. The 300 ns MD simulation evaluated the stability of receptor-peptide complexes. The double-site effect appeared on S2, a designed peptide based on a known inhibitor, when complexed with BCL2. S3, a designed peptide referred from endogenous inhibitor P16, competed against cyclin when binding with CDK6. The MDM2 inhibitors S5 and S6 were derived from the P53 structure and stable binding with MDM2. A flexible region of peptides S5 and S6 may enhance the binding ability by changing its own conformation, which was unforeseen. These peptides (S2, S3, S5, and S6) are potentially interesting to treat cancer; however, these findings need to be affirmed by biological testing, which will be conducted in the near future.

Acupuncture therapy improves health-related quality of life in patients with chronic obstructive pulmonary disease: A systematic review and meta-analysis.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is highly prevalent around the world and has a large impact on its patients, leading to a poor health-related quality of life (HRQL) and exercise capacity. Even under optimal medications, there are still many patients with poor HRQL. Body acupuncture therapy (BAT) is a non-invasive and a popular therapy. Therefore, we aimed to comprehensively analyze the effects of BAT in COPD. MATERIALS AND METHODS: Eight electronic databases were searched. We included randomized controlled trials (RCTs) that evaluated the effect of BAT, medication (M), and pulmonary rehabilitation (PR). The primary outcome was HRQL evaluated by St. George's respiratory questionnaire (SGRQ) or COPD assessment test (CAT). RESULTS: Of the 922 articles, 12 studies were included with attesting a total of 798 participants. The result obtained indicated a significant improvement that favored the BAT + M group over the M group in CAT scores (MD: -4.77; 95% CI: -6.53 to -3.01; p < 0.00001). CONCLUSIONS: BAT is an effective adjunctive non-pharmacological treatment to improve HRQL in patients under medical treatment for COPD. We suggested that BAT should be considered as one of the methods of management in patients with COPD.

Deep Learning and Random Forest Approach for Finding the Optimal Traditional Chinese Medicine Formula for Treatment of Alzheimer's Disease.

It has demonstrated that glycogen synthase kinase 3ß (GSK3ß) is related to Alzheimer's disease (AD). On the basis of the world largest traditional Chinese medicine (TCM) database, a network-pharmacology-based approach was utilized to investigate TCM candidates that can dock well with multiple targets. Support vector machine (SVM) and multiple linear regression (MLR) methods were utilized to obtain predicted models. In particular, the deep learning method and the random forest (RF) algorithm were adopted. We achieved R2 values of 0.927 on the training set and 0.862 on the test set with deep learning and 0.869 on the training set and 0.890 on the test set with RF. Besides, comparative molecular similarity indices analysis (CoMSIA) was performed to get a predicted model. All of the training models achieved good results on the test set. The stability of GSK3ß protein-ligand complexes was evaluated using 100 ns of MD simulation. Methyl 3- O-feruloylquinate and cynanogenin A induced both more compactness to the GSK3ß complex and stable conditions at all simulation times, and the GSK3ß complex also had no substantial fluctuations after a simulation time of 5 ns. For TCM molecules, we used the trained models to calculate predicted bioactivity values, and the optimum TCM candidates were obtained by ranking the predicted values. The results showed that methyl 3- O-feruloylquinate contained in Phellodendron amurense and cynanogenin A contained in Cynanchum atratum are capable of forming stable interactions with GSK3ß.

A real-life experience of sorafenib treatment for patients with advanced hepatocellular carcinoma: a retrospective analysis at Cathay General Hospital, 2007-2015.

BACKGROUND: Sorafenib is an oral tyrosine kinase inhibitor that is indicated for advanced hepatocellular carcinoma (HCC). The aim of the present study was to determine the clinical outcomes of HCC patients receiving sorafenib in real-life clinical setting in comparison with formal clinical trials. METHODS: Patients diagnosed with advanced HCC between 2007 and 2015 at single institute were retrospectively enrolled and evaluated for survival and tolerability following sorafenib treatment. Overall survival (OS) and duration of treatment (TTP) were examined by different stratifications including age, gender, etiology, liver functions, and severities. RESULTS: A total of 67 advanced HCC patients were enrolled for analysis. Of the 67 eligible patients, 66 patients (99%) were diagnosed as Barcelona Clinic Liver Cancer stage C and 45 (67%) were Child-Pugh A. Chronic hepatitis B virus infection was the main etiology (67%), followed by hepatitis C virus infection (12%) and alcohol liver disease (8%). The median duration of treatment was 3.0 months (95% CI 2.6-3.4 months) and median OS was 8.0 months (95% CI 5.0-11.0 months). By multivariate analysis, female gender (HR =2.462, 95% CI 1.126-5.387, P=0.024), Child-Pugh C (HR =3.913, 95% CI 1.063-14.410, P=0.04), extrahepatic spread (HR =2.123, 95% CI 1.122-4.015, P=0.021), and combined other therapies (HR =0.410, 95% CI 0.117-0.949, P=0.037) were the independent predictors of OS. CONCLUSION: OS of advanced HCC patients treated with sorafenib was longer than that reported in the Asia-Pacific trial study. Impaired hepatic functions are associated with the shorter survival in real-life setting.

Cytotoxic protobassic acid saponins from the kernels of Palaquium formosanum.

Bioassay guided fractionation and separation of the EtOH extract of the kernels of Palaquium formosanum against PC-3 cells via Sephadex LH-20 and reverse phase C-18 columns led to the isolation of 13 protobassic saponins. One of these saponins is new and was characterized as 3‴-O-rhamnopyranosyl-arganin C, a bisdesmoside of 16α-hydroxyprotobassic acid at the C-3 and C-28 positions. The structures of these compounds were determined on the basis of 1D NMR (1H, 13C), 2D NMR (1H-1H COSY, HSQC, HMBC, and NOESY), and selectively excited 1D TOCSY spectroscopic analyses and MS data, and comparison with literature data. Bioassay of these compounds and five additional compounds, isolated from Planchonella obovata leaf, against PC-3 prostate cancer cells indicated arganin C to be the most potent one with the IC50 value of 13.8 µM. Some structure and activity relationships were also drawn.

A Network Pharmacology-Based Approach to Investigate the Novel TCM Formula against Huntington's Disease and Validated by Support Vector Machine Model.

Several pathways are crucial in Huntington's disease (HD). Based on the concept of multitargets, network pharmacology-based analysis was employed to find out related proteins in disease network. The network target method aims to find out related mechanism of efficacy substances in rational design way. Traditional Chinese medicine prescriptions would be used for research and development against HD. Virtual screening was performed to obtain drug molecules with high binding capacity from traditional Chinese medicine (TCM) database@Taiwan. Quantitative structure-activity relationship (QSAR) models were conducted by MLR, SVM, CoMFA, and CoMSIA, constructed to predict the bioactivities of candidates. The compounds with high-dock score were further analyzed compared with control. Traditional Chinese medicine reported in the literature could be the training set provided for constructing novel formula by SVM model. We tried to find a novel formula that can bind well with these targets at the same time, which indicates our design could be highly related to the HD. Additionally, the candidates would validate by a long-term molecular dynamics (MD) simulation, 5 microseconds. Thus, we suggested the herbs Brucea javanica, Holarrhena antidysenterica, Dichroa febrifuga, Erythrophleum guineense, etc. which contained active compounds might be a novel medicine formula toward Huntington's disease.

Association between zolpidem use and glaucoma risk: a Taiwanese population-based case-control study.

BACKGROUND: To date, the relationship between zolpidem use and subsequent risk of glaucoma in a Taiwanese population has not been assessed. METHODS: We used data from the National Health Insurance system to investigate whether zolpidem use was related to glaucoma risk. A 1:4 matched case-control study was conducted. The cases were patients newly diagnosed with glaucoma from 2001 to 2010. The controls were randomly selected non-glaucoma subjects matched by sex and age (± 5 years). Zolpidem exposure and/or the average dosage of zolpidem used (mg/year) were evaluated. Medical comorbidities were considered as confounding factors. Multiple logistic regression models were used to evaluate the potential risk of zolpidem exposure on glaucoma with/without adjustment for the effects of confounding variables. RESULTS: The exposure rate of zolpidem use in the glaucoma group was significantly higher than that of the control group (2.8% vs. 2.0%, P < 0.0001). The adjusted odds ratio (OR) of the risk of glaucoma for those with zolpidem use vs. those without was 1.19 (95% confidence interval [CI], 1.02-1.38). Compared to non-zolpidem users, zolpidem users with an average dose of more than 200 mg/year had significantly increased risk of glaucoma (OR 1.31, 95% CI 1.03-1.68). CONCLUSIONS: This study suggests that the use of zolpidem might increase the risk of subsequent glaucoma. Further confirmatory studies are recommended to clarify this important issue.

In silico investigation of potential pyruvate kinase M2 regulators from traditional Chinese medicine against cancers.

A recent research in cancer research demonstrates that tumor-specific pyruvate kinase M2 (PKM2) plays an important role in chromosome segregation and mitosis progression of tumor cells. To improve the drug development of TCM compounds, we aim to identify potent TCM compounds as lead compounds of PKM2 regulators. PONDR-Fit protocol was utilized to predict the disordered disposition in the binding domain of PKM2 protein before virtual screening as the disordered structure in the protein may cause the side effect and downregulation of the possibility of ligand to bind with target protein. MD simulation was performed to validate the stability of interactions between PKM2 proteins and each ligand after virtual screening. The top TCM compounds, saussureamine C and precatorine, extracted from Lycium chinense Mill. and Abrus precatorius L., respectively, have higher binding affinities with target protein in docking simulation than control. They have stable H-bonds with residues A:Lys311 and some other residues in both chains of PKM2 protein. Hence, we propose the TCM compounds, saussureamine C and precatorine, as potential candidates as lead compounds for further study in drug development process with the PKM2 protein against cancer.

In silico investigation of potential TRAF6 inhibitor from traditional Chinese medicine against cancers.

It has been indicated that tumor necrosis factor receptor-associated factor-6 (TRAF6) will upregulate the expression of hypoxia-inducible factor-1α (HIF-1α) and promote tumor angiogenesis. TRAF6 proteins can be treated as drug target proteins for a differentiation therapy against cancers. As structural disordered disposition in the protein may induce the side-effect and reduce the occupancy for ligand to bind with target protein, PONDR-Fit protocol was performed to predict the disordered disposition in TRAF6 protein before virtual screening. TCM compounds from the TCM Database@Taiwan were employed for virtual screening to identify potent compounds as lead compounds of TRAF6 inhibitor. After virtual screening, the MD simulation was performed to validate the stability of interactions between TRAF6 proteins and each ligand. The top TCM compounds, tryptophan, diiodotyrosine, and saussureamine C, extracted from Saussurea lappa Clarke, Bos taurus domesticus Gmelin, and Lycium chinense Mill., have higher binding affinities with target protein in docking simulation. However, the docking pose of TRAF6 protein with tryptophan is not stable under dynamic condition. For the other two TCM candidates, diiodotyrosine and saussureamine C maintain the similar docking poses under dynamic conditions. Hence, we propose the TCM compounds, diiodotyrosine and saussureamine C, as potential candidates as lead compounds for further study in drug development process with the TRAF6 protein against cancer.

Potential smoothened inhibitor from traditional Chinese medicine against the disease of diabetes, obesity, and cancer.

Nowadays, obesity becomes a serious global problem, which can induce a series of diseases such as type 2 diabetes mellitus, cancer, cardiovascular disease, metabolic syndrome, and stoke. For the mechanisms of diseases, the hedgehog signaling pathway plays an important role in body patterning during embryogenesis. For this reason, smoothened homologue (Smo) protein had been indicated as the drug target. In addition, the small-molecule Smo inhibitor had also been used in oncology clinical trials. To improve drug development of TCM compounds, we aim to investigate the potent lead compounds as Smo inhibitor from the TCM compounds in TCM Database@Taiwan. The top three TCM compounds, precatorine, labiatic acid, and 2,2'-[benzene-1,4-diylbis(methanediyloxybenzene-4,1-diyl)]bis(oxoacetic acid), have displayed higher potent binding affinities than the positive control, LY2940680, in the docking simulation. After MD simulations, which can optimize the result of docking simulation and validate the stability of H-bonds between each ligand and Smo protein under dynamic conditions, top three TCM compounds maintain most of interactions with Smo protein, which keep the ligand binding stable in the binding domain. Hence, we propose precatorine, labiatic acid, and 2,2'-[benzene-1,4-diylbis(methanediyloxybenzene-4,1-diyl)]bis(oxoacetic acid) as potential lead compounds for further study in drug development process with the Smo protein.

Treatment of rheumatoid arthritis with traditional chinese medicine.

Rheumatoid arthritis (RA) is a chronic inflammatory disease that will affect quality of life and, working efficiency, and produce negative thoughts for patients. Current therapy of RA is treated with disease-modifying antirheumatic drugs (DMARDs). Although most of these treatment methods are effective, most patients still have a pleasant experience either due to poor efficacy or side effects or both. Interleukin-6 receptor (IL6R) is important in the pathogenesis of RA. In this study, we would like to detect the potential candidates which inhibit IL6R against RA from traditional Chinese medicine (TCM). We use TCM compounds from the TCM Database@Taiwan for virtually screening the potential IL6R inhibitors. The TCM candidate compound, calycosin, has potent binding affinity with IL6R protein. The molecular dynamics simulation was employed to validate the stability of interaction in the protein complex with calycosin. The analysis indicates that protein complex with calycosin is more stable. In addition, calycosin is known to be one of the components of Angelica sinensis, which has been indicated to have an important role in the treatment of rheumatoid arthritis. Therefore, calycosin is a potential candidate as lead compounds for further study in drug development process with IL6R protein against rheumatoid arthritis.

In silico investigation of potential mTOR inhibitors from traditional Chinese medicine for treatment of Leigh syndrome.

A recent research demonstrates that the inhibition of mammalian target of rapamycin (mTOR) improves survival and health for patients with Leigh syndrome. mTOR proteins can be treated as drug target proteins against Leigh syndrome and other mitochondrial disorders. In this study, we aim to identify potent TCM compounds from the TCM Database@Taiwan as lead compounds of mTOR inhibitors. PONDR-Fit protocol was employed to predict the disordered disposition in mTOR protein before virtual screening. After virtual screening, the MD simulation was employed to validate the stability of interactions between each ligand and mTOR protein in the docking poses from docking simulation. The top TCM compounds, picrasidine M and acerosin, have higher binding affinities with target protein in docking simulation than control. There have H-bonds with residues Val2240 and π interactions with common residue Trp2239. After MD simulation, the top TCM compounds maintain similar docking poses under dynamic conditions. The top two TCM compounds, picrasidine M and acerosin, were extracted from Picrasma quassioides (D. Don) Benn. and Vitex negundo L. Hence, we propose the TCM compounds, picrasidine M and acerosin, as potential candidates as lead compounds for further study in drug development process with the mTOR protein against Leigh syndrome and other mitochondrial disorders.

Treatment of cardiovascular disease by traditional Chinese medicine against pregnane X receptor.

Recently, cardiovascular disease, also known as loop circulatory system diseases or disorders, is one of the serious diseases including heart disease, stroke, atherosclerosis, myocardial infarction, hypertension, hypotension, and thrombosis. Human pregnane X receptor, PXR, plays a crucial role in exogenous and endobiotic metabolism for rabbit, rat, mouse, and human. The PXR activation can protect the blood vessels from damage of hazardous substances. In this study we aim to investigate the potent lead compounds as PXR receptor agonist against cardiovascular disease. To improve drug development of TCM compounds, we aim to investigate the potent lead compounds as PXR agonists from the TCM compounds in TCM Database@Taiwan. The top three TCM compounds, bis(4-hydroxybenzyl) ether mono-ß-D-glucopyranoside (BEMG), ixerisoside, and tangshenoside II, have displayed higher potent binding affinities than the positive control, PNU-142721, in the docking simulation. After MD simulations, which can optimize the result of docking simulation and validate the stability of H-bonds between each ligand and PXR protein under dynamic conditions, top TCM compounds, BEMG and tangshenoside II, maintain most of interactions with PXR protein, which keep the ligand binding stable in the binding domain. Hence, we propose BEMG and tangshenoside II as potential lead compounds for further study in drug development process with the PXR protein.