The Extracts of Polygonum cuspidatum Root and Rhizome Block the Entry of SARS-CoV-2 Wild-Type and Omicron Pseudotyped Viruses via Inhibition of the S-Protein and 3CL Protease

COVID-19, resulting from infection by the SARS-CoV-2 virus, caused a contagious pandemic. Even with the current vaccines, there is still an urgent need to develop effective pharmacological treatments against this deadly disease. Here, we show that the water and ethanol extracts of the root and rhizome of Polygonum cuspidatum (Polygoni Cuspidati Rhizoma et Radix), a common Chinese herbal medicine, blocked the entry of wild-type and the omicron variant of the SARS-CoV-2 pseudotyped virus into fibroblasts or zebrafish larvae, with IC₅₀ values ranging from 0.015 to 0.04 mg/mL. The extracts were shown to inhibit various aspects of the pseudovirus entry, including the interaction between the spike protein (S-protein) and the angiotensin-converting enzyme II (ACE2) receptor, and the 3CL protease activity. Out of the chemical compounds tested in this report, gallic acid, a phytochemical in P. cuspidatum, was shown to have a significant anti-viral effect. Therefore, this might be responsible, at least in part, for the anti-viral efficacy of the herbal extract. Together, our data suggest that the extracts of P. cuspidatum inhibit the entry of wild-type and the omicron variant of SARS-CoV-2, and so they could be considered as potent treatments against COVID-19.     

Identification of New Non-BBB Permeable Tryptophan Hydroxylase Inhibitors for Treating Obesity and Fatty Liver Disease

Serotonin (5-hydroxytryptophan) is a hormone that regulates emotions in the central nervous system. However, serotonin in the peripheral system is associated with obesity and fatty liver disease. Because serotonin cannot cross the blood-brain barrier (BBB), we focused on identifying new tryptophan hydroxylase type I (TPH1) inhibitors that act only in peripheral tissues for treating obesity and fatty liver disease without affecting the central nervous system. Structural optimization inspired by para-chlorophenylalanine (pCPA) resulted in the identification of a series of oxyphenylalanine and heterocyclic phenylalanine derivatives as TPH1 inhibitors. Among these compounds, compound 18i with an IC₅₀ value of 37 nM was the most active in vitro. Additionally, compound 18i showed good liver microsomal stability and did not significantly inhibit CYP and Herg. Furthermore, this TPH1 inhibitor was able to actively interact with the peripheral system without penetrating the BBB. Compound 18i and its prodrug reduced body weight gain in mammals and decreased in vivo fat accumulation.     

MolE8: finding DFT potential energy surface minima values from force-field optimised organic molecules with new machine learning representations

The use of machine learning techniques in computational chemistry has gained significant momentum since large molecular databases are now readily available. Predictions of molecular properties using machine learning have advantages over the traditional quantum mechanics calculations because they can be cheaper computationally without losing the accuracy. We present a new extrapolatable and explainable molecular representation based on bonds, angles and dihedrals that can be used to train machine learning models. The trained models can accurately predict the electronic energy and the free energy of small organic molecules with atom types C, H N and O, with a mean absolute error of 1.2 kcal mol⁻¹. The models can be extrapolated to larger organic molecules with an average error of less than 3.7 kcal mol⁻¹ for 10 or fewer heavy atoms, which represent a chemical space two orders of magnitude larger. The rapid energy predictions of multiple molecules, up to 7 times faster than previous ML models of similar accuracy, has been achieved by sampling geometries around the potential energy surface minima. Therefore, the input geometries do not have to be located precisely on the minima and we show that accurate density functional theory energy predictions can be made from force-field optimised geometries with a mean absolute error 2.5 kcal mol⁻¹.

New representations and machine learning calculate DFT minima from force field geometries.     

Reaction dynamics studied via femtosecond X-ray liquidography at X-ray free-electron lasers

X-ray free-electron lasers (XFELs) provide femtosecond X-ray pulses suitable for pump–probe time-resolved studies with a femtosecond time resolution. Since the advent of the first XFEL in 2009, recent years have witnessed a great number of applications with various pump–probe techniques at XFELs. Among these, time-resolved X-ray liquidography (TRXL) is a powerful method for visualizing structural dynamics in the liquid solution phase. Here, we classify various chemical and biological molecular systems studied via femtosecond TRXL (fs-TRXL) at XFELs, depending on the focus of the studied process, into (i) bond cleavage and formation, (ii) charge distribution and electron transfer, (iii) orientational dynamics, (iv) solvation dynamics, (v) coherent nuclear wavepacket dynamics, and (vi) protein structural dynamics, and provide a brief review on each category. We also lay out a plausible roadmap for future fs-TRXL studies for areas that have not been explored yet.

Femtosecond X-ray liquidography using X-ray free-electron lasers (XFELs) visualizes various aspects of reaction dynamics.     

Development of a Quantitative Method for Detection of Multiclass Veterinary Drugs in Feed Using Modified QuPPe Extraction and LC–MS/MS

A method was developed for the rapid and quantitative analysis of 30 veterinary drugs belonging to 17 classes (amphenicols (1), anthelmintics (1), cephalosporins (4), coccidiostats (1), lincosamides (1), macrolide (1), nitroimidazole (1), penicillins (3), phenylhydrazines (1), polypeptides (1), pyrethrins (1), quinolones (5), sulfonamides (3), tetracycline (3), neuroleptic agents (1), triazene trypanocidal agents (1), other. (1)) in feeds. The proposed method with a modified Quick Polar Pesticides (QuPPe) sample preparation was validated for the determination of 30 veterinary drugs in feed samples by liquid chromatography triple-quadrupole mass spectrometry (LC–MS/MS). The sample was extracted with methanol containing 1% acetic acid and purified by dispersive solid-phase extraction (d-SPE) with C18. Good linearity (r² ≥ 0.98) was observed, and the LOQ values ranged from 10 to 200 µg/kg. Average recoveries ranged from 70.8 to 118.4%, and the relative standard deviation was ≤ 18.7%. This validated method was used in the determination of 30 veterinary drugs in 142 feed samples obtained from South Korea. The results show that lincomycin was present in only one of the tested feed samples, although it was detected at a value lower than the LOQ. In conclusion, this multi-residue method can be used for screening through the detection and quantitation of residual multiclass veterinary drugs in feed samples.     

The Influence of Tyrosol-Enriched Rhodiola sachalinensis Extracts Bioconverted by the Mycelium of Bovista plumbe on Scopolamine-Induced Cognitive,Behavioral, and Physiological Responses in Mice

Alzheimer’s disease (AD) is an age-related neurodegenerative disorder characterized by cognitive deficits, which are accompanied by memory loss and cognitive disruption. Rhodiola sachalinensis (RSE) is a medicinal plant that has been used in northeastern Asia for various pharmacological activities. We attempted to carry out the bioconversion of RSE (Bio-RSE) using the mycelium of Bovista plumbe to obtain tyrosol-enriched Bio-RSE. The objective of this study was to investigate the effects of Bio-RSE on the activation of the cholinergic system and the inhibition of oxidative stress in mice with scopolamine (Sco)-induced memory impairment. Sco (1 mg/kg body weight, i.p.) impaired the mice’s performance on the Y-maze test, passive avoidance test, and water maze test. However, the number of abnormal behaviors was reduced in the groups supplemented with Bio-RSE. Bio-RSE treatment improved working memory and avoidance times against electronic shock, increased step-through latency, and reduced the time to reach the escape zone in the water maze test. Bio-RSE dramatically improved the cholinergic system by decreasing acetylcholinesterase activity and regulated oxidative stress by increasing antioxidant enzymes (superoxide dismutase (SOD) and catalase (CAT)). The reduction in nuclear factor erythroid 2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) signaling in the brain tissue due to scopolamine was restored by the administration of Bio-RSE. Bio-RSE also significantly decreased amyloid-beta 1–42 (Aβ1–42) and amyloid precursor protein (APP) expression. Moreover, the increased malondialdehyde (MDA) level and low total antioxidant capacity in Sco-treated mouse brains were reversed by Bio-RSE, and an increase in Nrf2 and HO-1 was also observed. In conclusion, Bio-RSE protected against Sco-induced cognitive impairment by activating Nrf2/HO-1 signaling and may be developed as a potential beneficial material for AD.     

In Vitro–In Vivo Correlation of Tianeptine Sodium Sustained-Release Dual-Layer Tablets

Tianeptine tablets are currently marketed to be designed for immediate-release tablets. The tianeptine has a short half-life, making it difficult to design for sustained-release tablets and achieve bioequivalence with the tianeptine immediate-release tablet (Stablon^®). We established the in vitro–in vivo correlation (IVIVC) of three formulations of tianeptine sustained-release tablets according to their granule size. To evaluate sustained drug release, in vitro tests were performed in pH 1.2 media for 24 h. In vivo pharmacokinetic analysis was performed following oral administration of reference drug and test drug to beagle dogs. The dissolution profile revealed delayed release as the size of the granules increased. The dissolution results were confirmed in pharmacokinetic analysis, showing that the half-life was delayed as granule size increased. The final formulation and reference drug showed an equivalent area under the curve (AUC). Through this, IVIVC was established according to the size of the tianeptine sodium granules, which is the purpose of this study, and was used to predict in vivo pharmacokinetics from the formulation composition. This approach may be useful for determining optimal formulation compositions to achieve the desired pharmacokinetics when developing new formulations.     

Improvement of Biological Effects of Root-Filling Materials for Primary Teeth by Incorporating Sodium Iodide

Therapeutic iodoform (CHI₃) is commonly used as a root-filling material for primary teeth; however, the side effects of iodoform-containing materials, including early root resorption, have been reported. To overcome this problem, a water-soluble iodide (NaI)-incorporated root-filling material was developed. Calcium hydroxide, silicone oil, and NaI were incorporated in different weight proportions (30:30:X), and the resulting material was denoted DX (D5~D30), indicating the NaI content. As a control, iodoform instead of NaI was incorporated at a ratio of 30:30:30, and the material was denoted I30. The physicochemical (flow, film thickness, radiopacity, viscosity, water absorption, solubility, and ion releases) and biological (cytotoxicity, TRAP, ARS, and analysis of osteoclastic markers) properties were determined. The amount of iodine, sodium, and calcium ion releases and the pH were higher in D30 than I30, and the highest level of unknown extracted molecules was detected in I30. In the cell viability test, all groups except 100% D30 showed no cytotoxicity. In the 50% nontoxic extract, D30 showed decreased osteoclast formation compared with I30. In summary, NaI-incorporated materials showed adequate physicochemical properties and low osteoclast formation compared to their iodoform-counterpart. Thus, NaI-incorporated materials may be used as a substitute for iodoform-counterparts in root-filling materials after further (pre)clinical investigation.     

Multistage homotopy perturbation method for nonlinear reaction networks

In this paper, we present the multistage homotopy perturbation method for finding the solution of the chemical kinetics with nonlinear reactions. We develop a general scheme for finding the analytic solution of chemical reaction networks and apply it to motivating chemical examples such as the enzyme kinetics model and the Brusselator model. We illustrate the numerical result for the models and show the accuracy of the method.