Saquinavir: From HIV to COVID-19 and Cancer Treatment.

Saquinavir was the first protease inhibitor developed for HIV therapy, and it changed the standard of treatment for this disease to a combination of drugs that ultimately led to increased survival of this otherwise deadly condition. Inhibiting the HIV protease impedes the virus from maturing and replicating. With this in mind, since the start of the COVID-19 outbreak, the research for already approved drugs (mainly antivirals) to repurpose for treatment of this disease has increased. Among the drugs tested, saquinavir showed promise in silico and in vitro in the inhibition of the SARS-CoV-2 main protease (3CLpro). Another field for saquinavir repurposing has been in anticancer treatment, in which it has shown effects in vitro and in vivo in several types of cancer, from Kaposi carcinoma to neuroblastoma, demonstrating cytotoxicity, apoptosis, inhibition of cell invasion, and improvement of radiosensibility of cancer cells. Despite the lack of follow-up in clinical trials for cancer use, there has been a renewed interest in this drug recently due to COVID-19, which shows similar pharmacological pathways and has developed superior in silico models that can be translated to oncologic research. This could help further testing and future approval of saquinavir repurposing for cancer treatment.

Identification of saquinavir as a potent inhibitor of dimeric SARS-CoV2 main protease through MM/GBSA.

Among targets selected for studies aimed at identifying potential inhibitors against COVID-19, SARS-CoV2 main proteinase (Mpro) is highlighted. Mpro is indispensable for virus replication and is a promising target of potential inhibitors of COVID-19. Recently, monomeric SARS-CoV2 Mpro, drug repurposing, and docking methods have facilitated the identification of several potential inhibitors. Results were refined through the assessment of dimeric SARS-CoV2 Mpro, which represents the functional state of enzyme. Docking and molecular dynamics (MD) simulations combined with molecular mechanics/generalized Born surface area (MM/GBSA) studies indicated that dimeric Mpro most significantly impacts binding affinity tendency compared with the monomeric state, which suggests that dimeric state is most useful when performing studies aimed at identifying drugs targeting Mpro. In this study, we extend previous research by performing docking and MD simulation studies coupled with an MM/GBSA approach to assess binding of dimeric SARS-CoV2 Mpro to 12 FDA-approved drugs (darunavir, indinavir, saquinavir, tipranavir, diosmin, hesperidin, rutin, raltegravir, velpatasvir, ledipasvir, rosuvastatin, and bortezomib), which were identified as the best candidates for the treatment of COVID-19 in some previous dockings studies involving monomeric SARS-CoV2 Mpro. This analysis identified saquinavir as a potent inhibitor of dimeric SARS-CoV2 Mpro; therefore, the compound may have clinical utility against COVID-19. Graphical abstract.

Drug binding dynamics of the dimeric SARS-CoV-2 main protease, determined by molecular dynamics simulation.

We performed molecular dynamics simulation of the dimeric SARS-CoV-2 (severe acute respiratory syndrome corona virus 2) main protease (Mpro) to examine the binding dynamics of small molecular ligands. Seven HIV inhibitors, darunavir, indinavir, lopinavir, nelfinavir, ritonavir, saquinavir, and tipranavir, were used as the potential lead drugs to investigate access to the drug binding sites in Mpro. The frequently accessed sites on Mpro were classified based on contacts between the ligands and the protein, and the differences in site distributions of the encounter complex were observed among the ligands. All seven ligands showed binding to the active site at least twice in 28 simulations of 200 ns each. We further investigated the variations in the complex structure of the active site with the ligands, using microsecond order simulations. Results revealed a wide variation in the shapes of the binding sites and binding poses of the ligands. Additionally, the C-terminal region of the other chain often interacted with the ligands and the active site. Collectively, these findings indicate the importance of dynamic sampling of protein-ligand complexes and suggest the possibilities of further drug optimisations.

Molecular Docking and Virtual Screening Based Prediction of Drugs for COVID-19.

AIMS: To predict potential drugs for COVID-19 by using molecular docking for virtual screening of drugs approved for other clinical applications. BACKGROUND: SARS-CoV-2 is the betacoronavirus responsible for the COVID-19 pandemic. It was listed as a potential global health threat by the WHO due to high mortality, high basic reproduction number, and lack of clinically approved drugs and vaccines. The genome of the virus responsible for COVID-19 has been sequenced. In addition, the three-dimensional structure of the main protease has been determined experimentally. OBJECTIVE: To identify potential drugs that can be repurposed for treatment of COVID-19 by using molecular docking based virtual screening of all approved drugs. METHODS: A list of drugs approved for clinical use was obtained from the SuperDRUG2 database. The structure of the target in the apo form, as well as structures of several target-ligand complexes, were obtained from RCSB PDB. The structure of SARS-CoV-2 Mpro determined from X-ray diffraction data was used as the target. Data regarding drugs in clinical trials for COVID-19 was obtained from clinicaltrials.org. Input for molecular docking based virtual screening was prepared by using Obabel and customized python, bash, and awk scripts. Molecular docking calculations were carried out with Vina and SMINA, and the docked conformations were analyzed and visualized with PLIP, Pymol, and Rasmol. RESULTS: Among the drugs that are being tested in clinical trials for COVID-19, Danoprevir and Darunavir were predicted to have the highest binding affinity for the Main protease (Mpro) target of SARS-CoV-2. Saquinavir and Beclabuvir were identified as the best novel candidates for COVID-19 therapy by using Virtual Screening of drugs approved for other clinical indications. CONCLUSION: Protease inhibitors approved for treatment of other viral diseases have the potential to be repurposed for treatment of COVID-19.

Transcriptome-based drug repositioning for coronavirus disease 2019 (COVID-19).

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) around the world has led to a pandemic with high morbidity and mortality. However, there are no effective drugs to prevent and treat the disease. Transcriptome-based drug repositioning, identifying new indications for old drugs, is a powerful tool for drug development. Using bronchoalveolar lavage fluid transcriptome data of COVID-19 patients, we found that the endocytosis and lysosome pathways are highly involved in the disease and that the regulation of genes involved in neutrophil degranulation was disrupted, suggesting an intense battle between SARS-CoV-2 and humans. Furthermore, we implemented a coexpression drug repositioning analysis, cogena, and identified two antiviral drugs (saquinavir and ribavirin) and several other candidate drugs (such as dinoprost, dipivefrine, dexamethasone and (-)-isoprenaline). Notably, the two antiviral drugs have also previously been identified using molecular docking methods, and ribavirin is a recommended drug in the diagnosis and treatment protocol for COVID pneumonia (trial version 5-7) published by the National Health Commission of the P.R. of China. Our study demonstrates the value of the cogena-based drug repositioning method for emerging infectious diseases, improves our understanding of SARS-CoV-2-induced disease, and provides potential drugs for the prevention and treatment of COVID-19 pneumonia.