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Voltage‐dependent K+ (Kv) channels play an important role in restoring the membrane potential to its resting state, thereby maintaining vascular tone. In this study, native smooth muscle cells from rabbit coronary arteries were used to investigate the inhibitory effect of quetiapine, an atypical antipsychotic agent, on Kv channels. Quetiapine showed a concentration‐dependent inhibition of Kv channels, with an IC50 of 47.98 ± 9.46 μM. Although quetiapine (50 μM) did not alter the steady‐state activation curve, it caused a negative shift in the steady‐state inactivation curve. The application of 1 and 2 Hz train steps in the presence of quetiapine significantly increased the inhibition of Kv current. Moreover, the recovery time constants from inactivation were prolonged in the presence of quetiapine, suggesting that its inhibitory action on Kv channels is use (state)‐dependent. The inhibitory effects of quetiapine were not significantly affected by pretreatment with Kv1.5, Kv2.1, and Kv7 subtype inhibitors. Based on these findings, we conclude that quetiapine inhibits Kv channels in both a concentration‐ and use (state)‐dependent manner. Given the physiological significance of Kv channels, caution is advised in the use of quetiapine as an antipsychotic due to its potential side effects on cardiovascular Kv channels. The primary goal of this study was to examine the direct effect of quetiapine on vascular Kv channels. Our results indicate that quetiapine reduces Kv currents in both concentration‐ and use (state)‐dependent manners. This inhibition is characterized by a shift in the steady‐state inactivation curve, with no effect on the activation curve. [ABSTRACT FROM AUTHOR]

The increasing utilization of artificial intelligence algorithms in drug development has proven to be highly efficient and effective. One area where deep learning-based approaches have made significant contributions is in drug repositioning, enabling the identification of new therapeutic applications for existing drugs. In the present study, a trained deep-learning model was employed to screen a library of FDA-approved drugs to discover novel inhibitors targeting JAK2. To accomplish this, reference datasets containing active and decoy compounds specific to JAK2 were obtained from the DUD-E database. RDKit, a cheminformatic toolkit, was utilized to extract molecular features from the compounds. The DeepChem framework's GraphConvMol, based on graph convolutional network models, was applied to build a predictive model using the DUD-E datasets. Subsequently, the trained deep-learning model was used to predict the JAK2 inhibitory potential of FDA-approved drugs. Based on these predictions, ribociclib, topiroxostat, amodiaquine, and gefitinib were identified as potential JAK2 inhibitors. Notably, several known JAK2 inhibitors demonstrated high potential according to the prediction results, validating the reliability of our prediction model. To further validate these findings and confirm their JAK2 inhibitory activity, molecular docking experiments were conducted using tofacitinib—an FDA-approved drug for JAK2 inhibition. Experimental validation successfully confirmed our computational analysis results by demonstrating that these novel drugs exhibited comparable inhibitory activity against JAK2 compared to tofacitinib. In conclusion, our study highlights how deep learning models can significantly enhance virtual screening efforts in drug discovery by efficiently identifying potential candidates for specific targets such as JAK2. These newly discovered drugs hold promises as novel JAK2 inhibitors deserving further exploration and investigation. [ABSTRACT FROM AUTHOR]

The regulation of membrane potential and the contractility of vascular smooth muscle cells (VSMCs) by voltage‐dependent K+ (Kv) potassium channels are well‐established. In this study, native VSMCs from rabbit coronary arteries were used to investigate the inhibitory effect of sertindole, an atypical antipsychotic agent, on Kv channels. Sertindole induced dose‐dependent inhibition of Kv channels, with an IC50 of 3.13 ± 0.72 μM. Although sertindole did not cause a change in the steady‐state activation curve, it did lead to a negative shift in the steady‐state inactivation curve. The application of 1‐ or 2‐Hz train pulses failed to alter the sertindole‐induced inhibition of Kv channels, suggesting use‐independent effects of the drug. The inhibitory response to sertindole was significantly diminished by pretreatment with a Kv1.5 inhibitor but not by Kv2.1 and Kv7 subtype inhibitors. These findings demonstrate the sertindole dose‐dependent and use‐independent inhibition of vascular Kv channels (mainly the Kv1.5 subtype) through a mechanism that involves altering steady‐state inactivation curves. Therefore, the use of sertindole as an antipsychotic drug may have adverse effects on the cardiovascular system. Native VSMCs from rabbit coronary arteries were used to investigate the inhibitory effect of sertindole, an atypical antipsychotic agent, on Kv channels. Our findings demonstrate the sertindole dose‐dependent and use‐independent inhibition of vascular Kv channels (mainly the Kv1.5 subtype) through a mechanism that involves altering steady‐state inactivation curves. [ABSTRACT FROM AUTHOR]

Malaria eradication efforts in resource-limited areas require a rapid, economical, and accurate tool for detecting of the low parasitemia. The malaria rapid diagnostic test (mRDT) is the most suitable for on-site detection of the deadliest form of malaria, Plasmodium falciparum. However, the deletions of histidine rich protein 2 and 3 genes are known to compromise the effectiveness of mRDT. One of the approaches that have been explored intensively for on-site diagnostics is the loop-mediated isothermal amplification (LAMP). LAMP is a one-step amplification that allows the detection of Plasmodium species in less than an hour. Thus, this study aims to present a new primer set to enhance the performance of a colorimetric LAMP (cLAMP) for field application. The primer binding regions were selected within the A-type of P. falciparum 18S rRNA genes, which presents a dual gene locus in the genome. The test result of the newly designed primer indicates that the optimal reaction condition for cLAMP was 30 minutes incubation at 65°C, a shorter incubation time compared to previous LAMP detection methods that typically takes 45 to 60 minutes. The limit of detection (LoD) for the cLAMP using our designed primers and laboratory-grown P. falciparum (3D7) was estimated to be 0.21 parasites/μL which was 1,000-fold higher than referencing primers. Under optimal reaction condition, the new primer sets showed the sensitivity (100%, 95% CI: 80.49–100%) and specificity (100%, 95% CI: 94.64–100%) with 100% (95% CI: 95.70–100%) accuracy on the detection of dried blood spots from Malawi (n = 84). Briefly, the newly designed primer set for P. falciparum detection exhibited high sensitivity and specificity compared to referenced primers. One great advantage of this tool is its ability to be detected by the naked eye, enhancing field approaches. Thus, this tool has the potential to be effective for accurate early parasite detection in resource-limited endemic areas. [ABSTRACT FROM AUTHOR]

γ-Aminobutyric acid aminotransferase (GABA-AT) is a pyridoxal 5′-phosphate (PLP)-dependent enzyme that degrades γ-aminobutyric (GABA) in the brain. GABA is an important inhibitory neurotransmitter that plays important neurological roles in the brain. Therefore, GABA-AT is an important drug target that regulates GABA levels. Novel and potent drug development to inhibit GABA-AT is still a very challenging task. In this study, we aimed to devise novel and potent inhibitors against GABA-AT using computer-aided drug design (CADD) tools. Since the crystal structure of human GABA-AT was not yet available, we utilized a homologous structure derived from our previously published paper. To identify highly potent compounds relative to vigabatrin, an FDA-approved drug against human GABA-AT, we developed a pharmacophore analysis protocol for 530,000 Korea Chemical Bank (KCB) compounds and selected the top 50 compounds for further screening. Preliminary biological analysis was carried out for these 50 compounds and 16 compounds were further assessed. Subsequently, molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations were carried out. In the results, four predicted compounds, A07, B07, D08, and H08, were found to be highly potent and were further evaluated by a biological activity assay to confirm the results of the GABA-AT activity inhibition assay. [ABSTRACT FROM AUTHOR]

Paliperidone, an atypical antipsychotic, is widely used to treat schizophrenia. In this study, we explored whether paliperidone inhibited the voltage‐dependent K+ (Kv) channels of rabbit coronary arterial smooth muscle cells. Paliperidone reduced Kv channel activity in a concentration‐dependent manner with a half‐maximal inhibitory concentration (IC50) of 16.58 ± 3.03 μM and a Hill coefficient of 0.60 ± 0.04. It did not significantly shift the steady‐state activation or inactivation curves, suggesting that the drug did not affect the gating properties of Kv channels. In the presence of paliperidone, the application of 20 repetitive depolarizing pulses at 1 and 2 Hz gradually increased the inhibition of the Kv current. Further, the recovery time constant after Kv channel inactivation was increased by paliperidone, indicating that it inhibited the Kv channel in a use (state)‐dependent manner. Its inhibitory effects were reduced by pretreatment with a Kv1.5 subtype inhibitor. However, pretreatment with a Kv2.1 or Kv7 inhibitor did not reduce its inhibitory effect. We conclude that paliperidone inhibits Kv channels (mainly Kv1.5 subtype channels) in a concentration‐ and use (state)‐dependent manner without changing channel gating. Paliperidone, an atypical antipsychotic, is widely used to treat schizophrenia. In this study, we explored whether paliperidone inhibited the voltage‐dependent K+ (Kv) channels of rabbit coronary arterial smooth muscle cells. Our results indicate that paliperidone inhibits Kv channels (mainly Kv1.5 subtype channels) in a concentration‐ and use (state)‐dependent manner without changing channel gating. [ABSTRACT FROM AUTHOR]