Discovery of Potential Inhibitors of SARS-CoV-2 Main Protease by a Transfer Learning Method.

The COVID-19 pandemic caused by SARS-CoV-2 remains a global public health threat and has prompted the development of antiviral therapies. Artificial intelligence may be one of the strategies to facilitate drug development for emerging and re-emerging diseases. The main protease (Mpro) of SARS-CoV-2 is an attractive drug target due to its essential role in the virus life cycle and high conservation among SARS-CoVs. In this study, we used a data augmentation method to boost transfer learning model performance in screening for potential inhibitors of SARS-CoV-2 Mpro. This method appeared to outperform graph convolution neural network, random forest and Chemprop on an external test set. The fine-tuned model was used to screen for a natural compound library and a de novo generated compound library. By combination with other in silico analysis methods, a total of 27 compounds were selected for experimental validation of anti-Mpro activities. Among all the selected hits, two compounds (gyssypol acetic acid and hyperoside) displayed inhibitory effects against Mpro with IC50 values of 67.6 µM and 235.8 µM, respectively. The results obtained in this study may suggest an effective strategy of discovering potential therapeutic leads for SARS-CoV-2 and other coronaviruses.

Retrorectal mucinous adenocarcinoma arising from a tailgut cyst: A case report and review of literature.

BACKGROUND: Tailgut cysts are defined as congenital cysts that develop in the rectosacral space from the residue of the primitive tail. As a congenital disease, caudal cysts are very rare, and their canceration is even rarer, which makes the disease prone to misdiagnosis and delayed treatment. We describe a case of caudal cyst with adenocarcinogenesis and summarize in detail the characteristics of cases with analytical value reported since 1990. CASE SUMMARY: A 35-year-old woman found a mass in her lower abdomen 2 mo ago. She was asymptomatic at that time and was not treated because of the coronavirus disease 2019 pandemic. Two weeks ago, the patient developed abdominal distension and right waist discomfort and came to our hospital. Except for the high level of serum carcinoembryonic antigen, the medical history and laboratory tests were not remarkable. Magnetic resonance imaging showed a well-defined, slightly lobulated cystic-solid mass with a straight diameter of approximately 10 cm × 9 cm in the presacral space, slightly high signal intensity on T2-weighted imaging, and moderate signal intensity on T1-weighted imaging. The mass was completely removed by laparoscopic surgery. Histopathological examination showed that the lesion was an intestinal mucinous adenocarcinoma, and the multidisciplinary team decided to implement postoperative chemotherapy. The patient recovered well, the tumor marker levels returned to normal, and tumor-free survival has been achieved thus far. CONCLUSION: The case and literature summary can help clinicians and researchers develop appropriate examination and therapeutic methods for diagnosis and treatment of this rare disease.

Fast and Effective Prediction of the Absolute Binding Free Energies of Covalent Inhibitors of SARS-CoV-2 Main Protease and 20S Proteasome.

The COVID-19 pandemic has been a public health emergency with continuously evolving deadly variants around the globe. Among many preventive and therapeutic strategies, the design of covalent inhibitors targeting the main protease (Mpro) of SARS-CoV-2 that causes COVID-19 has been one of the hotly pursued areas. Currently, about 30% of marketed drugs that target enzymes are covalent inhibitors. Such inhibitors have been shown in recent years to have many advantages that counteract past reservation of their potential off-target activities, which can be minimized by modulation of the electrophilic warhead and simultaneous optimization of nearby noncovalent interactions. This process can be greatly accelerated by exploration of binding affinities using computational models, which are not well-established yet due to the requirement of capturing the chemical nature of covalent bond formation. Here, we present a robust computational method for effective prediction of absolute binding free energies (ABFEs) of covalent inhibitors. This is done by integrating the protein dipoles Langevin dipoles method (in the PDLD/S-LRA/ß version) with quantum mechanical calculations of the energetics of the reaction of the warhead and its amino acid target, in water. This approach evaluates the combined effects of the covalent and noncovalent contributions. The applicability of the method is illustrated by predicting the ABFEs of covalent inhibitors of SARS-CoV-2 Mpro and the 20S proteasome. Our results are found to be reliable in predicting ABFEs for cases where the warheads are significantly different. This computational protocol might be a powerful tool for designing effective covalent inhibitors especially for SARS-CoV-2 Mpro and for targeted protein degradation.

A new class of α-ketoamide derivatives with potent anticancer and anti-SARS-CoV-2 activities.

Inhibitors of the proteasome have been extensively studied for their applications in the treatment of human diseases such as hematologic malignancies, autoimmune disorders, and viral infections. Many of the proteasome inhibitors reported in the literature target the non-primed site of proteasome's substrate binding pocket. In this study, we designed, synthesized and characterized a series of novel α-keto phenylamide derivatives aimed at both the primed and non-primed sites of the proteasome. In these derivatives, different substituted phenyl groups at the head group targeting the primed site were incorporated in order to investigate their structure-activity relationship and optimize the potency of α-keto phenylamides. In addition, the biological effects of modifications at the cap moiety, P1, P2 and P3 side chain positions were explored. Many derivatives displayed highly potent biological activities in proteasome inhibition and anticancer activity against a panel of six cancer cell lines, which were further rationalized by molecular modeling analyses. Furthermore, a representative α-ketoamide derivative was tested and found to be active in inhibiting the cellular infection of SARS-CoV-2 which causes the COVID-19 pandemic. These results demonstrate that this new class of α-ketoamide derivatives are potent anticancer agents and provide experimental evidence of the anti-SARS-CoV-2 effect by one of them, thus suggesting a possible new lead to develop antiviral therapeutics for COVID-19.