Quantitative Predictive Studies of Multiple Biological Activities of TRPV1 Modulators.

TRPV1 channel agonists and antagonists, which have powerful analgesic effects without the addictive qualities associated with traditional analgesics, have become a focus area for the development of novel analgesics. In this study, quantitative structure-activity relationship (QSAR) models for three bioactive endpoints (Ki, IC50, and EC50) were successfully constructed using four machine learning algorithms: SVM, Bagging, GBDT, and XGBoost. These models were based on 2922 TRPV1 modulators and incorporated four types of molecular descriptors: Daylight, E-state, ECFP4, and MACCS. After the rigorous five-fold cross-validation and external test set validation, the optimal models for the three endpoints were obtained. For the Ki endpoint, the Bagging-ECFP4 model had a Q2 value of 0.778 and an R2 value of 0.780. For the IC50 endpoint, the XGBoost-ECFP4 model had a Q2 value of 0.806 and an R2 value of 0.784. For the EC50 endpoint, the SVM-Daylight model had a Q2 value of 0.784 and an R2 value of 0.809. These results demonstrate that the constructed models exhibit good predictive performance. In addition, based on the model feature importance analysis, the influence between substructure and biological activity was also explored, which can provide important theoretical guidance for the efficient virtual screening and structural optimization of novel TRPV1 analgesics. And subsequent studies on novel TRPV1 modulators will be based on the feature substructures of the three endpoints.

Accurate Density Prediction of Sesquiterpenoid HEDFs and the Multiproperty Computing Server SesquiterPre.

Accurate and rapid evaluation of density is crucial for evaluating the packing and combustion characteristics of high-energy-density fuels (HEDFs). This parameter is pivotal in the selection of high-performance HEDFs. Our study leveraged a polycyclic compound density data set and quantum chemical (QC) descriptors to establish a correlation with the target properties using the XGBoost algorithm. We utilized a recursive feature elimination method to simplify the model and developed a concise and interpretable density prediction model incorporating only six QC descriptors. The model demonstrated robust performance, achieving coefficients of determination (R 2) of 0.967 and 0.971 for internal and external test sets, respectively, and root-mean-square errors (RMSE) of 0.031 and 0.027 g/cm3, respectively. Compared to the other two mainstream methods, the marginal discrepancy between the predicted and actual molecular densities underscores the model's superior predictive ability and more usefulness for energy density calculation. Furthermore, we developed a web server (SesquiterPre, https://sespre.cmdrg.com/#/) that can simultaneously calculate the density, enthalpy of combustion, and energy density of sesquiterpenoid HEDFs, which greatly facilitates the use of researchers and is of great significance for accelerating the design and screening of novel sesquiterpenoid HEDFs.

Discovery of novel TRPV1 modulators through machine learning-based molecular docking and molecular similarity searching.

The transient receptor potential vanilloid 1 (TRPV1) channel belongs to the transient receptor potential channel superfamily and participates in many physiological processes. TRPV1 modulators (both agonists and antagonists) can effectively inhibit pain caused by various factors and have curative effects in various diseases, such as itch, cancer, and cardiovascular diseases. Therefore, the development of TRPV1 channel modulators is of great importance. In this study, the structure-based virtual screening and ligand-based virtual screening methods were used to screen compound databases respectively. In the structure-based virtual screening route, a full-length human TRPV1 protein was first constructed, three molecular docking methods with different precisions were performed based on the hTRPV1 structure, and a machine learning-based rescoring model by the XGBoost algorithm was constructed to enrich active compounds. In the ligand-based virtual screening route, the ROCS program was used for 3D shape similarity searching and the EON program was used for electrostatic similarity searching. Final 77 compounds were selected from two routes for in vitro assays. The results showed that 8 of them were identified as active compounds, including three hits with IC50 values close to capsazepine. In addition, one hit is a partial agonist with both agonistic and antagonistic activity. The mechanisms of some active compounds were investigated by molecular dynamics simulation, which explained their agonism or antagonism.

Silibinin exerts antidepressant effects by improving neurogenesis through BDNF/TrkB pathway.

Classic antidepressants benefit depression patients partially by improving neurogenesis and/or brain-derived neurotrophic factor (BDNF)/TrkB pathway which were impaired in depression. In this study, we demonstrated that Silibinin (SLB), a polyphenolic flavanoid from Silybum marianum, ameliorated reserpinized mouse depressant-like behaviors. The antidepressants of SLB administration was associated with increased neural stem cells (NSCs) proliferation and further confirmed in BDNF/TrkB signaling transduction. SLB treatment reversed the decreased expression levels of BDNF and its receptor TrkB, and the reduced activation of downstream target proteins including phosphorylated extracellular-regulated protein kinase (p-ERK) and phosphorylated cAMP-response element binding protein (p-CREB) in depressived hippocampus. Furthermore, intracerebroventricular injection of GNF5837, a TrkB antagonist, abrogated antidepressant-like effects of SLB in mice along with the improved NSC proliferation, as well as enhanced levels of p-ERK and p-CREB in mice hippocampus. Taken together, these results suggest that SLB may exert antidepressant effects through BDNF/TrkB signaling pathway to improve NSC proliferation in acute depression.

A mesoporous silicon/poly-(DL-lactic-co-glycolic) acid microsphere for long time anti-tuberculosis drug delivery.

In this study, drug delivery systems for controlling release of hydrophobic anti-tuberculosis (TB) drug-rifampicin (RIF) or hydrophilic anti-TB drug-isoniazid (INH) from mesoporous silica (MS) were fabricated. The drug was first filled into the mesopores of MS particles, and then the drug-laden MS constructs were incorporated into the bulk of poly-(DL-lactic-co-glycolic) acid (PLGA) microspheres. In comparison with mono-component construct (drug-laden MS and drug-laden PLGA), this multi-component system significantly improved the release time of RIF and INH. For drug-laden MS, about 100% INH was released after 15 h, and about 70% RIF was released after 50 h. For drug-laden PLGA, about 100% INH and RIF were released after 30 and 40 days, respectively. After 60 days, the total RIF and INH release from MS/PLGA had only reached around only 48% and 57%, respectively. This MS/PLGA system could significantly prolong RIF or INH release compared to MS and PLGA. CCK-8 assay demonstrated that this MS/PLGA system had no cytotoxicity. And there has not been study of documenting the controlled release of anti-TB drugs such as RIF or INH from MS/PLGA. Considering the long time release of RIF and INH from MS/PLGA, a new door to bone TB would be opened.

[Clinical analysis of pediatric SARS cases in Beijing].

OBJECTIVE: To study clinical characteristics of pediatric SARS cases in Beijing. METHODS: Eighteen pediatric cases with SARS diagnosed on admission were analyzed. The cases were admitted to Beijing Children's Hospital and Ditan Hospital (pediatric ward) from April 8 to May 12. RESULTS: The 18 children aged 5 months to 15 years (10 male and 8 female) had epidemiologically linked findings. Fourteen cases had close contact with SARS patients. Four cases were living in the community where adult SARS patients were found. All the 18 patients but one presented with fever and cough. Most of them had high fever, 2 cases had bradycardia, 2 had diarrhea, and another 2 had tachypnea. Malaise and headache were noted only in 3 cases respectively which were much less frequently seen than in adult patients. Symptoms and signs of the children were much less severe and aggressive than adults cases. Thirteen children had chest radiographic consolidation. Of them, 9 cases had progressive changes after admission, then improved quickly. We did not find significant lower hemoglobin and platelet levels. Most patients had leukopenia and lymphopenia. Serologic test was performed for 15 cases and 8 were positive for SARS virus-IgG and 6 for IgM antibody. Of the 4 cases who had close contact with SARS adults and without chest radiograph abnormal findings, 3 were negative for SARS virus-antibodies. Part of the patients had temporary abnormality of myocardial enzyme and liver function. All these children finally had rapid improvement on chest radiograph. The patients were treated with antiviral agents and corticosteroid. Only two cases required oxygen therapy. No child needed assisted ventilation and no death, nor lung fibrosis occurred. After hospitalization, all patients were improved and discharged when this paper was being written. The average hospital stay of these patients was 14.6 days (6 - 22 days). CONCLUSION: Compared with adults, pediatric SARS patients seemed to have their own clinical characteristics. The disease in children had lower severity and infectivity than that in adults. The mechanisms of the disease in children should be studied in well-designed clinical trials. Cases like the 4 children who had close contact with SARS adult patients but without chest radiographic changes deserve further studies with the help of more reliable and sensitive etiologic tests.