Resolving the pharmacological redox-sensitivity of SARS-CoV-2 PLpro in drug repurposing screening enabled identification of the competitive GRL-0617 binding site inhibitor CPI-169 (preprint)

The SARS CoV-2 Papain-Like protease has multiple roles in the viral replication cycle, related to both its polypeptide cleavage function and its capacity to antagonize host immune response. Targeting PLpro function is recognized as a promising mechanism to modulate viral replication whilst supporting host immune responses. However, development of PLpro specific inhibitors remains challenging. Upcoming studies revealed the limitation of reported inhibitors by profiling them through a pipeline of enzymatic, binding and cellular activity assays showing unspecific activity. GRL-0617 remained the only validated molecule with demonstrated anti-viral activity in cells. In this study we refer to the pitfalls of redox-sensitivity of PLpro. Using a screening-based approach to identify inhibitors of PLpro proteolytic activity, we made extensive efforts to validate the active compounds over a range of conditions and readouts, emphasising the need for comprehensive orthogonal data when profiling putative PLpro inhibitors. The remaining active compound CPI-169, showed to compete with GRL-0617 in NMR-based experiments, suggesting to share a similar binding mode, opening novel design opportunities for further developments as antiviral agents.

DHFR Inhibitors Display a Pleiotropic Anti-viral Activity Against SARS-CoV-2: Insights Into the Mechanisms of Action (preprint)

During COVID-19 pandemic, drug repurposing represented an effective strategy to obtain quick answers to medical emergencies. Basing on previous data on Methotrexate (MTX), we evaluated the anti-viral activity of several DHFR inhibitors in two cell lines. We observed that this class of compounds showed a significant influence on the virus-induced cytopathic effect (CPE) partly associated to the intrinsic antimetabolic activity of these drugs, but also to a specific antiviral function. To elucidate the molecular mechanisms, we took advantage of our EXSCALATE platform for in-silico molecular modelling and further validated the influence of these inhibitors on nsp13 and viral entry. Interestingly, Pralatrexate and Trimetrexate showed superior effects in counteracting the viral infection compared to other DHFR inhibitors. Our results indicate that their higher activity is due to their polypharmacological and pleiotropic profile. These compounds can thus potentially give a clinical advantage in the management of SARS-CoV-2 infection in patients already treated with this class of drugs.

Nirmatrelvir treatment blunts the development of antiviral adaptive immune responses in SARS-CoV-2 infected mice (preprint)

Alongside vaccines, antiviral drugs are becoming an integral part of our response to the SARS-CoV-2 pandemic. Nirmatrelvir, an orally available inhibitor of the 3- chymotrypsin-like cysteine protease, has been shown to reduce the risk of progression to severe COVID-19. However, the impact of nirmatrelvir treatment on the development of SARS-CoV-2-specific adaptive immune responses is unknown. Here, by using a mouse model of SARS-CoV-2 infection, we show that nirmatrelvir administration early after infection blunts the development of SARS-CoV-2-specific antibody and T cell responses. Accordingly, upon secondary challenge, nirmatrelvir-treated mice recruited significantly fewer memory T and B cells to the infected lungs and to mediastinal lymph nodes, respectively. Together, the data highlight a potential negative impact of nirmatrelvir treatment with important implications for clinical management and might help explain the virological and/or symptomatic relapse after treatment completion reported in some individuals.

Identification of inhibitors of SARS-CoV-2 3CL-Pro enzymatic activity using a small molecule in-vitro repurposing screen (preprint)

Compound repurposing is an important strategy for the identification of effective treatment options against SARS-CoV-2 infection and COVID-19 disease. In this regard, SARS-CoV-2 main protease (3CL-Pro), also termed M-Pro, is an attractive drug target as it plays a central role in viral replication by processing the viral polyproteins pp1a and pp1ab at multiple distinct cleavage sites. We here report the results of a repurposing program involving 8.7 K compounds containing marketed drugs, clinical and preclinical candidates, and small molecules regarded as safe in humans. We confirmed previously reported inhibitors of 3CL-Pro, and have identified 62 additional compounds with IC50 values below 1 uM and profiled their selectivity towards Chymotrypsin and 3CL-Pro from the MERS virus. A subset of 8 inhibitors showed anti-cytopathic effect in a Vero-E6 cell line and the compounds thioguanosine and MG-132 were analysed for their predicted binding characteristics to SARS-CoV-2 3CL-Pro. The X-ray crystal structure of the complex of myricetin and SARS-Cov-2 3CL-Pro was solved at a resolution of 1.77 Angs., showing that myricetin is covalently bound to the catalytic Cys145 and therefore inhibiting its enzymatic activity.

One Year of SARS-CoV-2: How Much Has the Virus Changed? (preprint)

SARS-CoV-2 coronavirus has caused a world-wide crisis with profound effects on both healthcare and the economy. In order to combat the COVID-19 pandemic, research groups have shared viral genome sequence data through the GISAID initiative. We collected and computationally profiled ~223,000 full SARS-CoV-2 proteome sequences from GISAID over one year for emergent nonsynonymous mutations. Our analysis shows that SARS-CoV-2 proteins are mutating at substantially different rates, with most viral proteins exhibiting little mutational variability. As anticipated, our calculations capture previously reported mutations occurred in the first period of the pandemic, such as D614G (Spike), P323L (NSP12), and R203K/G204R (Nucleocapsid), but also identify recent mutations like A222V and L18F (Spike) and A220V (Nucleocapsid). Our comprehensive temporal and geographical analyses show two periods with different mutations in the SARS-CoV-2 proteome: December 2019 to June 2020 and July to November 2020. Some mutation rates differ also by geography; the main mutations in the second period occurred in Europe. Furthermore, our structure-based molecular analysis provides an exhaustive assessment of mutations in the context of 3D protein structure. Emerging sequence-to-structure data is beginning to reveal the site-specific mutational tolerance of SARS-CoV2 proteins as the virus continues to spread around the globe.

EXPERIMENTAL INVESTIGATION OF PULSE STERILIZATION OF VIRAL INFECTION (preprint)

The results of experimental investigations of the effect of high-intensity pulsed UV radiation on the influenza virus type A (H1N1) are presented. The research methodology is developed and the structure of the experiments is described. An end-face plasma accelerator was used as a radiation source, which provides a power pulsed discharge in an open atmosphere. The high efficiency of inactivation of the infectiousness of the virus was shown within a short period of time. The possibility of providing urgent 100% sterilization of a viral infection has been shown for the first time. A model for calculating the efficiency of pulse sterilization has been developed. The prospects for the application of pulse sterilization technology to combat coronavirus infection are considered.

Rapid SARS-CoV-2 Detection and Classification Using Phase Imaging with Computational Specificity (preprint)

Efforts to mitigate the COVID-19 crisis revealed that fast, accurate, and scalable testing is crucial for curbing the current impact and that of future pandemics. We propose an optical method for directly imaging unlabeled viral particles and using deep learning for detection and classification. An ultrasensitive interferometric method was used to image four virus types with nanoscale optical pathlength sensitivity. Pairing these data with fluorescence images for ground truth, we trained semantic segmentation models based on U-Net, a particular type of convolutional neural network. The trained network was applied to classify the viruses from the interferometric images only, containing simultaneously SARS-CoV-2, H1N1 (influenza-A), HAdV (adenovirus), and ZIKV (Zika). Remarkably, due to the nanoscale sensitivity in the input data, the neural network was able to identify SARS-CoV-2 vs. the other viruses with 96% accuracy. The inference time for each image is 60 ms, on a common graphic processing unit. This approach of directly imaging unlabeled viral particles may provide an extremely fast test, of less than a minute per patient. As the imaging instrument operates on regular glass slides, we envision this method as potentially testing on patient breath condensates. The necessary high throughput can be achieved by translating concepts from digital pathology, where a microscope can scan hundreds of slides automatically.

A blueprint for high affinity SARS-CoV-2 Mpro inhibitors from activity-based compound library screening guided by analysis of protein dynamics (preprint)

The SARS-CoV-2 coronavirus outbreak continues to spread at a rapid rate worldwide. The main protease (Mpro) is an attractive target for anti-COVID-19 agents. Unfortunately, unexpected difficulties have been encountered in the design of specific inhibitors. Here, by analyzing an ensemble of ~30,000 SARS-CoV-2 Mpro conformations from crystallographic studies and molecular simulations, we show that small structural variations in the binding site dramatically impact ligand binding properties. Hence, traditional druggability indices fail to adequately discriminate between highly and poorly druggable conformations of the binding site. By performing ~200 virtual screenings of compound libraries on selected protein structures, we redefine the protein's druggability as the consensus chemical space arising from the multiple conformations of the binding site formed upon ligand binding. This procedure revealed a unique SARS-CoV-2 Mpro blueprint that led to a definition of a specific structure-based pharmacophore. The latter explains the poor transferability of potent SARS-CoV Mpro inhibitors to SARS-CoV-2 Mpro, despite the identical sequences of the active sites. Importantly, application of the pharmacophore predicted novel high affinity inhibitors of SARS-CoV-2 Mpro, that were validated by in vitro assays performed here and by a newly solved X-ray crystal structure. These results provide a strong basis for effective rational drug design campaigns against SARS-CoV-2 Mpro and a new computational approach to screen protein targets with malleable binding sites.

Transfer Learning with MotifTransformers for Predicting Protein-Protein Interactions Between a Novel Virus and Humans (preprint)

The novel coronavirus SARS-CoV-2, which causes Coronavirus disease 2019 (COVID19), is a significant threat to worldwide public health. Viruses such as SARS-CoV-2 infect the human body by forming interactions between virus proteins and human proteins that compromise normal human protein-protein interactions (PPI). Current in vivo methods to identify PPIs between a novel virus and humans are slow, costly, and difficult to cover the vast interaction space. We propose a novel deep learning architecture designed for in silico PPI prediction and a transfer learning approach to predict interactions between novel virus proteins and human proteins. We show that our approach outperforms the state of the art methods significantly in predicting Virus-Human protein interactions for SARS-CoV-2, H1N1, and Ebola.

No detectable signal for ongoing genetic recombination in SARS-CoV-2 (preprint)

The COVID-19 pandemic has led to an unprecedented global sequencing effort of its viral agent SARS-CoV-2. The first whole genome assembly of SARS-CoV-2 was published on January 5 2020. Since then, over 150,000 high-quality SARS-CoV-2 genomes have been made available. This large genomic resource has allowed tracing of the emergence and spread of mutations and phylogenetic reconstruction of SARS-CoV-2 lineages in near real time. Though, whether SARS-CoV-2 undergoes genetic recombination has been largely overlooked to date. Recombination-mediated rearrangement of variants that arose independently can be of major evolutionary importance. Moreover, the absence of recombination is a key assumption behind the application of phylogenetic inference methods. Here, we analyse the extant genomic diversity of SARS-CoV-2 and show that, to date, there is no detectable hallmark of recombination. We assess our detection power using simulations and validate our method on the related MERS-CoV for which we report evidence for widespread genetic recombination.

Genomic diversity analysis of SARS-CoV-2 genomes in Rwanda (preprint)

COVID-19 (Coronavirus disease 2019) is an emerging pneumonia-like respiratory disease of humans and is recently spreading across the globe. To analyze the genome sequence of SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) isolated from Rwanda with other viral strains from African countries. We downloaded 75 genomes sequences of clinical SARS-CoV-2 from the GISAID (global initiative on sharing all influenza data) database and we comprehensively analyzed these SARS-CoV-2 genomes sequences alongside with Wuhan SARS-CoV-2 sequences as the reference strains. We analyzed 75 genomes sequences of SARS-CoV-2 isolated in different African countries including 10 samples of SARS-CoV-2 isolated in Rwanda between July and August 2020. The phylogenetic analysis of the genome sequence of SARS-CoV-2 revealed a strong identity with reference strains between 90-95%. We identified a missense mutation in four proteins including orf1ab polyprotein, NSP2, 2'-O-ribose methyltransferase and orf1a polyprotein. The most common changes in the base are C > T. We also found that all clinically SARS-CoV-2 isolated from Rwanda had genomes belonging to clade G and lineage B.1. Tracking the genetic evolution of SARS-CoV-2 over time is important to understand viral evolution pathogenesis. These findings may help to implement public health measures in curbing COVID-19 in Rwanda.