A deep learning based multi-model approach for predicting drug-like chemical compound's toxicity.

Ensuring the safety and efficacy of chemical compounds is crucial in small-molecule drug development. In the later stages of drug development, toxic compounds pose a significant challenge, losing valuable resources and time. Early and accurate prediction of compound toxicity using deep learning models offers a promising solution to mitigate these risks during drug discovery. In this study, we present the development of several deep-learning models aimed at evaluating different types of compound toxicity, including acute toxicity, carcinogenicity, hERG_cardiotoxicity (the human ether-a-go-go related gene caused cardiotoxicity), hepatotoxicity, and mutagenicity. To address the inherent variations in data size, label type, and distribution across different types of toxicity, we employed diverse training strategies. Our first approach involved utilizing a graph convolutional network (GCN) regression model to predict acute toxicity, which achieved notable performance with Pearson R 0.76, 0.74, and 0.65 for intraperitoneal, intravenous, and oral administration routes, respectively. Furthermore, we trained multiple GCN binary classification models, each tailored to a specific type of toxicity. These models exhibited high area under the curve (AUC) scores, with an impressive AUC of 0.69, 0.77, 0.88, and 0.79 for predicting carcinogenicity, hERG_cardiotoxicity, mutagenicity, and hepatotoxicity, respectively. Additionally, we have used the approved drug dataset to determine the appropriate threshold value for the prediction score in model usage. We integrated these models into a virtual screening pipeline to assess their effectiveness in identifying potential low-toxicity drug candidates. Our findings indicate that this deep learning approach has the potential to significantly reduce the cost and risk associated with drug development by expediting the selection of compounds with low toxicity profiles. Therefore, the models developed in this study hold promise as critical tools for early drug candidate screening and selection.

Gap junction is essential for the antidepressant effects of fluoxetine.

OBJECTIVES: Fluoxetine has been used as the first line for the therapy of depression. However, lack of therapeutic efficacy and time lag still limit the application of fluoxetine. Gap junction dysfunction is a potentially novel pathogenic mechanism for depression. To clarify the mechanism underlying these limitations, we investigated whether gap junction was related to the antidepressant effects of fluoxetine. METHODS AND KEY FINDINGS: After chronic unpredictable stress (CUS), animals showed decreases in gap junction intracellular communication (GJIC). Treatment with fluoxetine 10 mg/kg significantly improved GJIC and anhedonia of rats until six days. These results indicated that fluoxetine improved gap junction indirectly. Furthermore, to test the role of gap junction on antidepressant effects of fluoxetine, we blocked gap junction using carbenoxolone (CBX) infusion in the prefrontal cortex. CBX dampened fluoxetine-induced decrease in immobility time of mice in tail suspension test (TST). CONCLUSIONS: Our study suggested that gap junction dysfunction blocks antidepressant effects of fluoxetine, contributing to understanding the mechanism underlying the time lag of fluoxetine.

Z16b, a natural compound from Ganoderma cochlear is a novel RyR2 stabilizer preventing catecholaminergic polymorphic ventricular tachycardia.

Catecholaminergic polymorphic ventricular tachycardia (CPVT) is an inherited, lethal ventricular arrhythmia triggered by catecholamines. Mutations in genes that encode cardiac ryanodine receptor (RyR2) and proteins that regulate RyR2 activity cause enhanced diastolic Ca2+ release (leak) through the RyR2 channels, resulting in CPVT. Current therapies for CPVT are limited. We found that Z16b, a meroterpenoid isolated from Ganoderma cochlear, inhibited Ca2+ spark frequency (CaSF) in R2474S/ + cardiomyocytes in a dose-dependent manner, with an IC50 of 3.2 µM. Z16b also dose-dependently suppressed abnormal post-pacing Ca2+ release events. Intraperitoneal injection (i.p.) of epinephrine and caffeine stimulated sustained ventricular tachycardia in all R2474S/+ mice, while pretreatment with Z16b (0.5 mg/kg, i.p.) prevented ventricular arrhythmia in 9 of 10 mice, and Z16b administration immediately after the onset of VT abolished sVT in 9 of 12 mice. Of translational significance, Z16b significantly inhibited CaSF and abnormal Ca2+ release events in human CPVT iPS-CMs. Mechanistically, Z16b interacts with RyR2, enhancing the "zipping" state of the N-terminal and central domains of RyR2. A molecular docking simulation and point mutation and pulldown assays identified Z16b forms hydrogen bonds with Arg626, His1670, and Gln2126 in RyR2 as a triangle shape that anchors the NTD and CD interaction and thus stabilizes RyR2 in a tight "zipping" conformation. Our findings support that Z16b is a novel RyR2 stabilizer that can prevent CPVT. It may also serve as a lead compound with a new scaffold for the design of safer and more efficient drugs for treating CPVT.

Ursodeoxycholic acid protects interstitial Cajal-like cells in the gallbladder from undergoing apoptosis by inhibiting TNF-α expression.

Hypomotility is a common symptom of gallstone disease, which is accompanied by a loss of interstitial Cajal-like cells (ICLCs) in the gallbladder. Ursodeoxycholic acid (UDCA) is widely used in treating gallstone disease, and has shown anti-apoptotic and anti-inflammatory effects apart from its ability to dissolve gallstones. In this study, we investigated the anti-apoptotic and anti-inflammatory effects of UDCA on ICLCs in guinea pigs with gallstones. Guinea pigs were fed a high-cholesterol diet for 8 weeks to induce the formation of gallstones. A group of animals was administered UDCA (50 mg·kg-1·d-1, ig) simultaneously. At the end of 8 weeks, the animals were euthanized with anesthesia, cholecystectomy was performed immediately and gallbladder was collected for further analysis. We showed that in the model group the contractility of gallbladder muscle strips in response to both acetylcholine (ACh) and CCK-8 was severely impaired, which was significantly improved by UDCA administration. Furthermore, UDCA administration significantly reduced the apoptotic ratio of ICLCs, based on the observation of co-localization imaging of apoptotic cells and c-kit-positive cells. Western blotting analysis and real-time PCR results revealed that the TNF-α/Caspase8/Caspase3 pathway was suppressed in the UDCA-treated animals, confirming the anti-apoptotic effect of UDCA in the gallbladder. The H&E staining showed that UDCA administration significantly attenuated inflammatory cell infiltration in the gallbladder wall. In conclusion, UDCA can protect ICLCs in the gallbladder from undergoing apoptosis by inhibiting the TNF-α/Caspase8/caspase3 pathway.

[Research status of natural compounds combine with antifungal agents against drug-resistent Candida albicans].

To against the emergence of drug-resistent candidiasis, the studys of synergism of natural compounds combine with antifungal agents in vitro showed a continuous growth in recent years. The paper reviewed recent progresses to compare the synergetic effect by FICI method, and to conclude the synergetic mechanisms which have been confirmed as a reference for futher study.