Future COVID-19 surges prediction based on SARS-CoV-2 mutations surveillance

COVID19 has aptly revealed that airborne viruses such as SARS-CoV-2 with the ability to rapidly mutate, combined with high rates of transmission and fatality can cause a deadly world-wide pandemic in a matter of weeks.1 Apart from vaccines and post-infection treatment options, strategies for preparedness will be vital in responding to the current and future pandemics. Therefore, there is wide interest in approaches that allow predictions of increase in infections ("surges") before they occur. We describe here real time genomic surveillance particularly based on mutation analysis, of viral proteins as a methodology for a priori determination of surge in number of infection cases. The full results are available for SARS-CoV-2 at http://pandemics.okstate.edu/covid19/, and are updated daily as new virus sequences become available. This approach is generic and will also be applicable to other pathogens.

Two ligand-binding sites on SARS-CoV-2 non-structural protein 1 revealed by fragment-based x-ray screening

The regular reappearance of coronavirus (CoV) outbreaks over the past 20 years has caused significant health consequences and financial burdens worldwide. The most recent and still ongoing novel CoV pandemic, caused by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) has brought a range of devastating consequences. Due to the exceptionally fast development of vaccines, the mortality rate of the virus has been curbed to a significant extent. However, the limitations of vaccination efficiency and applicability, coupled with the still high infection rate, emphasise the urgent need for discovering safe and effective antivirals against SARS-CoV-2 through suppressing its replication and or attenuating its virulence. Non-structural protein 1 (nsp1), a unique viral and conserved leader protein, is a crucial virulence factor for causing host mRNA degradation, suppressing interferon (IFN) expression and host antiviral signalling pathways. In view of the essential role of nsp1 in the CoV life cycle, it is regarded as an exploitable target for antiviral drug discovery. Here, we report a variety of fragment hits against SARS-CoV-2 nsp1 identified by fragment-based screening via X-ray crystallography. We also determined the structure of nsp1 at atomic resolution (0.95 [A]). Binding affinities of hits against nsp1 were determined by orthogonal biophysical assays such as microscale thermophoresis and thermal sift assays. We identified two ligand-binding sites on nsp1, one deep and one shallow pocket, which are not conserved between the three medially relevant SARS, SARS-CoV-2 and MERS coronaviruses. Our study provides an excellent starting point for the development of more potent nsp1-targeting inhibitors and functional studies on SARS-CoV-2 nsp1.

Revealing druggable cryptic pockets in the Nsp-1 of SARS-CoV-2 and other β-coronaviruses by simulations and crystallography

Non-structural protein 1 (Nsp1) is a main pathogenicity factor of - and {beta}-coronaviruses. Nsp1 of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) suppresses the host gene expression by sterically blocking 40S host ribosomal subunits and promoting host mRNA degradation. This mechanism leads to the downregulation of the translation-mediated innate immune response in host cells, ultimately mediating the observed immune evasion capabilities of SARS-CoV-2. Here, by combining extensive Molecular Dynamics simulations, fragment screening and crystallography, we reveal druggable pockets in Nsp1. Structural and computational solvent mapping analyses indicate the partial crypticity of these newly discovered and druggable binding sites. The results of fragment-based screening via X-ray crystallography confirm the druggability of the major pocket of Nsp1. Finally, we show how the targeting of this pocket could disrupt the Nsp1-mRNA complex and open a novel avenue to design new inhibitors for other Nsp1s present in homologous {beta}-coronaviruses.

Structural dynamics of the β-coronavirus Mpro protease ligand binding sites

{beta}-coronaviruses alone have been responsible for three major global outbreaks in the 21st century. The current crisis has led to an urgent requirement to develop therapeutics. Even though a number of vaccines are available, alternative strategies targeting essential viral components are required as a back-up against the emergence of lethal viral variants. One such target is the main protease (Mpro) that plays an indispensible role in viral replication. The availability of over 270 Mpro X-ray structures in complex with inhibitors provides unique insights into ligand-protein interactions. Herein, we provide a comprehensive comparison of all non-redundant ligand-binding sites available for SARS-CoV2, SARS-CoV and MERS-CoV Mpro. Extensive adaptive sampling has been used to explore conformational dynamics employing convolutional variational auto encoder-based deep learning, and investigates structural conservation of the ligand binding sites using Markov state models across {beta}-coronavirus homologs. Our results indicate that not all ligand-binding sites are dynamically conserved despite high sequence and structural conservation across {beta}-coronavirus homologs. This highlights the complexity in targeting all three Mpro enzymes with a single pan inhibitor.