The World Health Organization declared monkeypox a global public health emergency on 23 July 2022. This disease was caused by the monkeypox virus (MPXV), which was first identified in 1958 in Denmark. The MPXV is a member of the Poxviridae family, the Chordopoxvirinae subfamily, and the genus Orthopoxvirus, which share high similarities with the vaccinia virus (the virus used to produce the smallpox vaccine). For the initial stage of infection, the MPXV needs to attach to the human cell surface glycosaminoglycan (GAG) adhesion molecules using its E8 protein. However, up until now, neither a structure for the MPXV E8 protein nor a specific cure for the MPXV exists. This study aimed to search for small molecules that inhibit the MPXV E8 protein, using computational approaches. In this study, a high-quality three-dimensional structure of the MPXV E8 protein was retrieved by homology modeling using the AlphaFold deep learning server. Subsequent molecular docking and molecular dynamics simulations (MDs) for a cumulative duration of 2.1 microseconds revealed that ZINC003977803 (Diosmin) and ZINC008215434 (Flavin adenine dinucleotide-FAD) could be potential inhibitors against the E8 protein with the MM/GBSA binding free energies of −38.19 ± 9.69 and −35.59 ± 7.65 kcal·mol−1, respectively.
Traditional/herbal medicine has gained increasing interests recently, especially in Asian countries such as Vietnam, due to its diverse therapeutic actions. In the treasure of Vietnamese medicinal plants, one of the potential herbs is the roots of Sophora flavescens Ait. (SF, “Kho sam” in Vietnamese). However, limited information has been reported on the Vietnamese SF compositions and their respective alkaloids’ anti-acetylcholinesterase action. Thus, this study investigated the extractions, isolations, identifications, and in-vitro antioxidant, cytotoxicity, and acetylcholinesterase inhibitory activities, of the SF root extracts and their purified alkaloid compounds. To this end, four pure compounds were successfully isolated, purity-tested by HPLC, and structurally identified by spectroscopic techniques of FTIR, MS, and NMR. These compounds, confirmed to be oxysophocarpine, oxymatrine, matrine, and sophoridine, were then determined their therapeutic actions. The SF extracts and the compounds did not possess significant antioxidant activity using the DPPH and MDA assays, and cytotoxicity action using the MTT assay on the MDA-MB-231 breast cancer cell line. On the other hand, the SF total extract yielded a moderate acetylcholinesterase inhibition effect, with an IC50 of 0.1077 ± 0.0023 mg/mL. In summary, the SF extract demonstrated potential effects as an anti-acetylcholinesterase agent and could be further researched to become a pharmaceutical product for diseases related to acetylcholine deficiency, such as dementia.
We propose to improve unconditional Generative Adversarial Networks (GAN) by training the self-supervised learning with the adversarial process. In particular, we apply self-supervised learning via the geometric transformation on input images and assign the pseudo-labels to these transformed images. (i) In addition to the GAN task, which distinguishes data (real) versus generated (fake) samples, we train the discriminator to predict the correct pseudolabels of real transformed samples (classification task). Importantly, we find out that simultaneously training the discriminator to classify the fake class from the pseudo-classes of real samples for the classification task will improve the discriminator and subsequently lead better guides to train generator. (ii) The generator is trained by attempting to confuse the discriminator for not only the GAN task but also the classification task. For the classification task, the generator tries to confuse the discriminator recognizing the transformation of its output as one of the real transformed classes. Especially, we exploit that when the generator creates samples that result in a similar loss (via cross-entropy) as that of the real ones, the training is more stable and the generator distribution tends to match better the data distribution. When integrating our techniques into a state-ofthe-art Auto-Encoder (AE) based-GAN model, they help to significantly boost the model's performance and also establish new state-of-the-art Fréchet Inception Distance (FID) scores in the literature of unconditional GAN for CIFAR-10 and STL-10 datasets.
The main protease 3CL pro is one of the potential targets against coronavirus. Inhibiting this enzyme leads to the interruption of viral replication. Chalcone and its derivatives were reported to possess the ability to bind to 3CL pro protease in the binding pocket. This study explored an in-house database of 269 chalcones as 3CL pro inhibitors using in silico screening models, including molecular docking, molecular dynamics simulation, binding free energy calculation, and ADME prediction. C264 and C235 stand out as the two most potential structures. The top hit compound C264 was with the Jamda score of −2.8329 and the MM/GBSA binding energy mean value of −28.23 ± 3.53 kcal/mol, which was lower than the reference ligand. Despite the lower mean binding energy (−22.07 ± 3.39 kcal/mol), in-depth analysis of binding interaction suggested C235 could be another potential candidate. Further, in vitro and in vivo experiments are required to confirm the inhibitory ability. Supplementary Information The online version contains supplementary material available at 10.1007/s11224-022-02000-3.
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