The ongoing pandemic of COVID-19 caused by the novel coronavirus Syndrome-Coronavirus-2 (SARS-CoV-2) is an emerging, rapidly evolving situation. 1 Coronaviruses (CoV) are enveloped viruses with a positive single-stranded RNA virus, which are widely distributed in humans and animals and cause respiratory infections in humans. 2 Study reported that SARS-CoV-2 enters the cells through its predicated receptor angiotensin converting enzyme 2 (ACE2). 3 Unfortunately, until now, there are no specific/targeted drugs or vaccines, and in many parts of the world, the number of SARS-CoV-2-positive patients are increasing. As of 20 April 2020, in total, 2 486 597 cases and 170 582 deaths have been confirmed around the world, suggesting that the overall death rate of COVID-19 was 6.86%. D-dimer is a specific degradation product produced by fibrin monomer cross-linking with activated factor XIII and then hydrolysed by plasmin, and is a specific marker of fibrinolysis process. 4 Excluded typical manifestation of pneumonia and acute respiratory symptoms, COVID-19 patients also have abnormal D-dimer concentration in the serum, but the results are controversial. A recent

G-protein-coupled receptor (GPCR) is an important target class of proteins for drug discovery, with over 27% of FDA-approved drugs targeting GPCRs. However, being a membrane protein, it is difficult to obtain the 3D crystal structures of GPCRs for virtual screening of ligands by molecular docking. Thus, we evaluated the virtual screening performance of homology models of human GPCRs with respect to the corresponding crystal structures. Among the 19 GPCRs involved in this study, we observed that 10 GPCRs have homology models that have better or comparable performance with respect to the corresponding X-ray structures, making homology models a viable choice for virtual screening. For a small subset of GPCRs, we also explored how certain methods like consensus enrichment and sidechain perturbation affect the utility of homology models in virtual screening, as well as the selectivity between agonists and antagonists. Most notably, consensus enrichment across multiple homology models often yields results comparable to the best performing model, suggesting that ligand candidates predicted with consensus scores from multiple models can be the optimal option in practical applications where the performance of each model cannot be estimated.

G-protein-coupled receptor (GPCR) is an important target class of proteins for drug discovery, with over 27% of FDA-approved drugs targeting GPCRs. However, being a membrane protein, it is difficult to obtain the 3D crystal structures of GPCRs for virtual screening of ligands by molecular docking. Thus, we evaluated the virtual screening performance of homology models of human GPCRs with respect to the corresponding crystal structures. Among the 19 GPCRs involved in this study, we observed that 10GPCRs have homology models that have better or comparable performance with respect to the corresponding X-ray structures, making homology models a viable choice for virtual screening. For a small subset of GPCRs, we also explored how certain methods like consensus enrichment and sidechain perturbation affect the utility of homology models in virtual screening, as well as the selectivity between agonists and antagonists. Most notably, consensus enrichment across multiple homology models often yields results comparable to the best performing model, suggesting that ligand candidates predicted with consensus scores from multiple models can be the optimal option in practical applications where the performance of each model cannot be estimated.

Background: Recent studies have found that programmed death ligand 1 (PD-L1) might be involved in chemotherapy resistance in non-small cell lung cancer (NSCLC). Arsenic sulfide (As 4 S 4 ) has been recognized to have antitumor activities and enhance the cytotoxic effect of chemotherapy drugs. In this study, we aimed to verify the relationship between PD-L1 and cisplatin (DDP) resistance and identify whether As 4 S 4 could reverse DDP resistance through targeting PD-L1 in NSCLC. Methods: The effect of As 4 S 4 and DDP on cell proliferation and apoptosis was investigated in NSCLC cell lines. The expression of p53 and PD-L1 proteins was measured by western blotting analysis. The levels of miR-34a-5p, miR-34a-3p and PD-L1 in cells were measured by real-time qPCR analysis. Mouse xenograft models were established by inoculation with A549/DDP (DDP-resistant) cells. Results: Depletion of PD-L1 inhibited DDP resistance in A549/DDP and H1299/DDP cells. As 4 S 4 was capable of sensitizing A549/DDP cells to DDP by enhancing apoptosis. As 4 S 4 upregulated p53 expression and downregulated PD-L1 expression in A549/DDP cells. As 4 S 4 increased miR-34a-5p level in A549/DDP cells. Inhibition of p53 by PFT-α partially restored the levels of PD-L1 and miR-34a-5p. Pretreatment with PFT-α suppressed the apoptosis rate induced by cotreatment of As 4 S 4 and DDP in A549/DDP cells. Cotreatment of DDP and As 4 S 4 notably reduced the tumor size when compared with DDP treatment alone in vivo. Conclusions: Upregulation of PD-L1 was correlated with DDP resistance in NSCLC cells. Mechanistic analyses indicated that As 4 S 4 might sensitize NSCLC cells to DDP through targeting p53/miR-34a-5p/PD-L1 axis.