Design, synthesis and biological evaluation of novel 3C-like protease inhibitors as lead compounds against SARS-CoV-2.

Background: The epidemic caused by SARS-CoV-2 swept the world in 2019. The 3C-like protease (3CLpro) of SARS-CoV-2 plays a key role in viral replication, and its inhibition could inhibit viral replication. Materials & methods: The virtual screen based on receptor-ligand pharmacophore models and molecular docking were conducted to obtain the novel scaffolds of the 3CLpro. The molecular dynamics simulation was also carried out. All compounds were synthesized and evaluated in biochemical assays. Results: The compound C2 could inhibit 3CLpro with a 72% inhibitory rate at 10 µM. The covalent docking showed that C2 could form a covalent bond with the Cys145 in 3CLpro. Conclusion: C2 could be a potent lead compound of 3CLpro inhibitors against SARS-CoV-2.

Discovery of Covalent Lead Compounds Targeting 3CL Protease with a Lateral Interactions Spiking Neural Network.

Covalent drugs exhibit advantages in that noncovalent drugs cannot match, and covalent docking is an important method for screening covalent lead compounds. However, it is difficult for covalent docking to screen covalent compounds on a large scale because covalent docking requires determination of the covalent reaction type of the compound. Here, we propose to use deep learning of a lateral interactions spiking neural network to construct a covalent lead compound screening model to quickly screen covalent lead compounds. We used the 3CL protease (3CL Pro) of SARS-CoV-2 as the screen target and constructed two classification models based on LISNN to predict the covalent binding and inhibitory activity of compounds. The two classification models were trained on the covalent complex data set targeting cysteine (Cys) and the compound inhibitory activity data set targeting 3CL Pro, respected, with good prediction accuracy (ACC > 0.9). We then screened the screening compound library with 6 covalent binding screening models and 12 inhibitory activity screening models. We tested the inhibitory activity of the 32 compounds, and the best compound inhibited SARS-CoV-2 3CL Pro with an IC50 value of 369.5 nM. Further assay implied that dithiothreitol can affect the inhibitory activity of the compound to 3CL Pro, indicating that the compound may covalently bind 3CL Pro. The selectivity test showed that the compound had good target selectivity to 3CL Pro over cathepsin L. These correlation assays can prove the rationality of the covalent lead compound screening model. Finally, covalent docking was performed to demonstrate the binding conformation of the compound with 3CL Pro. The source code can be obtained from the GitHub repository (https://github.com/guzh970630/Screen_Covalent_Compound_by_LISNN).

Understanding Correlation between Magnetism and Electrocatalytic Hydrogen Evolution Based on Intrinsic Properties of Single MoS2 Entity.

Few-layered molybdenum chalcogenide (MoS2) has attracted considerable attention due to its defect-rich structure and active edge sites, triggering distinctive electrocatalysis and magnetism properties. Quantifying the intrinsic properties of a single entity is of paramount importance for clarifying the structure-activity correlation. Here, the intrinsic activities of single MoS2 flakes toward the hydrogen evolution reaction (HER) were investigated by single nanoparticle collision electrochemical measurements with and without a moderate magnetic field. Our results demonstrate that single bilayer MoS2 flakes show the highest HER performance and the greatest magnetic enhancement among bilayer-, trilayer-, and multilayer-MoS2 flakes. This is because bilayer MoS2 flakes possess abundantly exposed edge sites and sulfur vacancies, which simultaneously accelerate the reaction kinetics of HER and increase the ferromagnetism properties. This work gives new insight into providing specific guidance for the magnetic modulation of few-layered MoS2 and the design of highly effective MoS2-based electrocatalysts.

Confined Electrochemical Behaviors of Single Platinum Nanoparticles Revealing Ultrahigh Density of Gas Molecules inside a Nanobubble.

Understanding the basic physicochemical properties of gas molecules confined within nanobubbles is of fundamental importance for chemical and biological processes. Here, we successfully monitored the nanobubble-confined electrochemical behaviors of single platinum nanoparticles (PtNPs) at a carbon fiber ultramicroelectrode in HClO4 and H2O2 solution. Due to the catalytic decomposition of H2O2, a single oxygen nanobubble was formed on individual PtNPs to block the active surface of particles for proton reduction and to suppress their stochastic motion, resulting in significantly distinguished current traces. Furthermore, the combination of theoretical calculations and high-resolution electrochemical measurements allowed the nanobubble size and the oxygen gas density inside a single nanobubble to be quantified. Moreover, the ultrahigh oxygen density inside (1046 kg/m3) was revealed, indicating that gas molecules in a nanosized space existed with a high state of aggregation. Our approach sheds light on the gas aggregation behaviors of nanoscale bubbles using single-entity electrochemical measurements.

In-situ decoration of tin sulfide on Niobium carbide MXene with robust electronic coupling for improved sodium storage performance.

Tin sulfide (SnS) has been considered as one of the most promising sodium storage materials because of its excellent electrochemical activity, low cost, and low-dimensional structure. However, owing to the serious volume change upon discharging/charging and poor electronic conductivity, the SnS-based electrodes often suffer from electrode pulverization and sluggish reaction kinetics, thus resulting in serious capacity fading and degraded rate capability. In this work, SnS nanoparticles uniformly distributed on the surface of the layered Niobium carbide MXene (SnS/Nb2CTx) were fabricated through a facile solvothermal approach followed by calcination, endowing the SnS/Nb2CTx with a three-dimensional interconnected framework as well as fast charge transfer. Benefitting from the excellent electronic/ionic conductivity, efficient buffering matrix, abundant active sites, and high sodium storage activity inherited from the structure design, the robust electronic coupling between SnS nanoparticle and Nb2CTx MXene results in excellent electrochemical output, which demonstrates superior reversible capacities of 479.6 (0.1 A/g up to 100 cycles) and 278.9 mAh/g (0.5 A/g up to 500 cycles) upon sodium storage, respectively. The excellent electrochemical performance manifests the promise of the combination of metal sulfides with Nb2CTx MXene to fabricate high-performance electrodes for sodium storage.

Targeting the LPA1 signaling pathway for fibrosis therapy: a patent review (2010-present).

INTRODUCTION: Fibrosis is a disease that damages organs and even causes death. Because of the complicated pathogenesis, the development of drugs for fibrosis is challenging. In the lysophosphatidic acid receptor type 1 (LPA1) signaling pathway, LPA1 and its downstream Rho-associated coiled-coil forming protein kinase (ROCK) are related to the process of fibrosis. Targeting LPA1 signaling pathway is a potential strategy for the treatment of fibrosis. AREA COVERED: This review describes the process of fibrosis mediated by the LPA1 signaling pathway and then summarizes LPA1 antagonist patents reported since 2010 and ROCK inhibitor patents since 2017 according to their scaffolds based on the Cortellis Drug Discovery Intelligence database. Information on LPA1 antagonists entering clinical trials is integrated. EXPERT OPINION: Over the past decade, a large number of antagonists targeting the LPA1 signaling pathway have been patented for fibrosis therapy. A limited number of compounds have entered clinical trials. Different companies and research groups have used different scaffolds when designing compounds for fibrosis therapy. Therefore, LPA1 and ROCK are competitive targets for the development of new therapies for fibrosis to provide a potential treatment method for fibrosis in the future.

Private Face Image Generation Method Based on Deidentification in Low Light.

The existing face image recognition algorithm can accurately identify underexposed facial images, but the abuse of face image recognition technology can associate face features with personally identifiable information, resulting in privacy disclosure of the users. The paper puts forward a method for private face image generation based on deidentification under low light. First of all, the light enhancement and attenuation networks are pretrained using the training set, and low-light face images in the test set are input into the light enhancement network for photo enhancement. Then the facial area is captured by the face interception network, and corresponding latent code will be created through the latent code generation network and feature disentanglement will be done. Tiny noise will be added to the latent code by the face generation network to create deidentified face images which will be input in a light attenuation network to generate private facial images in a low-lighting style. At last, experiments show that, compared with other state-of-the-art algorithms, this method is more successful in generating low-light private face images with the most similar structure to original photos. It protects users' privacy effectively by reducing the accuracy of the face recognition network, while also ensuring the practicability of the images.

A Novel Retinex-Based Fractional-Order Variational Model for Images with Severely Low Light.

In this paper, we propose a novel Retinex-based fractional-order variational model for severely low-light images. The proposed method is more flexible in controlling the regularization extent than the existing integer-order regularization methods. Specifically, we decompose directly in the image domain and perform the fractional-order gradient total variation regularization on both the reflectance component and the illumination component to get more appropriate estimated results. The merits of the proposed method are as follows: 1) small-magnitude details are maintained in the estimated reflectance. 2) illumination components are effectively removed from the estimated reflectance. 3) the estimated illumination is more likely piecewise smooth. We compare the proposed method with other closely related Retinex-based methods. Experimental results demonstrate the effectiveness of the proposed method.