An approach combining deep learning and molecule docking for drug discovery of cathepsin L.

OBJECTIVES: Cathepsin L (CTSL) is a promising therapeutic target for metabolic disorders and COVID-19. However, there are still no clinically available CTSL inhibitors. Our objective is to develop an approach for the discovery of potential reversible covalent CTSL inhibitors. METHODS: The authors combined Chemprop, a deep learning-based strategy, and the Schrödinger CovDock algorithm to identify potential CTSL inhibitors. First, they used Chemprop to train a deep learning model capable of predicting whether a molecule would inhibit the activity of CTSL and performed predictions on ZINC20 in-stock librarie (~9.2 million molecules). Then, they selected the top-200 predicted molecules and performed the Schrödinger covalent docking algorithm to explore the binding patterns to CTSL (PDB: 5MQY). The authors then calculated the binding energies using Prime MM/GBSA and examined the stability between the best two molecules and CTSL using 100ns molecular dynamics simulations. RESULTS: The authors found five molecules that showed better docking results than the well-known cathepsin inhibitor odanacatib. Notably, two of these molecules, ZINC-35287427 and ZINC-1857528743, showed better docking results with CTSL compared to other cathepsins. CONCLUSION: Our approach enables drug discovery from large-scale databases with little computational consumption, which will save the cost and time required for drug discovery.

The mechanism and effects of remdesivir-induced developmental toxicity in zebrafish: Blood flow dysfunction and behavioral alterations.

The antiviral drug remdesivir has been used to treat the growing number of coronavirus disease 2019 (COVID-19) patients. However, the drug is mainly excreted through urine and feces and introduced into the environment to affect non-target organisms, including fish, which has raised concerns about potential ecotoxicological effects on aquatic organisms. Moreover, studies on the ecological impacts of remdesivir on aquatic environments have not been reported. Here, we aimed to explore the toxicological impacts of microinjection of remdesivir on zebrafish early embryonic development and larvae and the associated mechanism. We found that 100 µM remdesivir delayed epiboly and impaired convergent movement of embryos during gastrulation, and dose-dependent increases in mortality and malformation were observed in remdesivir-treated embryos. Moreover, 10-100 µM remdesivir decreased blood flow and swimming velocity and altered the behavior of larvae. In terms of molecular mechanisms, 80 differentially expressed genes (DEGs) were identified by transcriptome analysis in the remdesivir-treated group. Some of these DEGs, such as manf, kif3a, hnf1ba, rgn, prkcz, egr1, fosab, nr4a1, and ptgs2b, were mainly involved in early embryonic development, neuronal developmental disorders, vascular disease and the blood flow pathway. These data reveal that remdesivir can impair early embryonic development, blood flow and behavior of zebrafish embryos/larvae, probably due to alterations at the transcriptome level. This study suggests that it is important to avoid the discharge of remdesivir to aquatic ecosystems and provides a theoretical foundation to hinder remdesivir-induced ecotoxicity to aquatic environments.

Potential drug discovery for COVID-19 treatment targeting Cathepsin L using a deep learning-based strategy.

Cathepsin L (CTSL), a cysteine protease that can cleave and activate the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein, could be a promising therapeutic target for coronavirus disease 2019 (COVID-19). However, there is still no clinically available CTSL inhibitor that can be used. Here, we applied Chemprop, a newly trained directed-message passing deep neural network approach, to identify small molecules and FDA-approved drugs that can block CTSL activity to expand the discovery of CTSL inhibitors for drug development and repurposing for COVID-19. We found 5 molecules (Mg-132, Z-FA-FMK, leupeptin hemisulfate, Mg-101 and calpeptin) that were able to significantly inhibit the activity of CTSL in the nanomolar range and inhibit the infection of both pseudotype and live SARS-CoV-2. Notably, we discovered that daptomycin, an FDA-approved antibiotic, has a prominent CTSL inhibitory effect and can inhibit SARS-CoV-2 pseudovirus infection. Further, molecular docking calculation showed stable and robust binding of these compounds with CTSL. In conclusion, this study suggested for the first time that Chemprop is ideally suited to predict additional inhibitors of enzymes and revealed the noteworthy strategy for screening novel molecules and drugs for the treatment of COVID-19 and other diseases with unmet needs.

Cathepsin L plays a key role in SARS-CoV-2 infection in humans and humanized mice and is a promising target for new drug development.

To discover new drugs to combat COVID-19, an understanding of the molecular basis of SARS-CoV-2 infection is urgently needed. Here, for the first time, we report the crucial role of cathepsin L (CTSL) in patients with COVID-19. The circulating level of CTSL was elevated after SARS-CoV-2 infection and was positively correlated with disease course and severity. Correspondingly, SARS-CoV-2 pseudovirus infection increased CTSL expression in human cells in vitro and human ACE2 transgenic mice in vivo, while CTSL overexpression, in turn, enhanced pseudovirus infection in human cells. CTSL functionally cleaved the SARS-CoV-2 spike protein and enhanced virus entry, as evidenced by CTSL overexpression and knockdown in vitro and application of CTSL inhibitor drugs in vivo. Furthermore, amantadine, a licensed anti-influenza drug, significantly inhibited CTSL activity after SARS-CoV-2 pseudovirus infection and prevented infection both in vitro and in vivo. Therefore, CTSL is a promising target for new anti-COVID-19 drug development.