Mechanism of Inhibition of the Reproduction of SARS-CoV-2 and Ebola Viruses by Remdesivir.

Remdesivir is an antiviral drug initially designed against the Ebola virus. The results obtained with it both in biochemical studies in vitro and in cell line assays in vivo were very promising, but it proved to be ineffective in clinical trials. Remdesivir exhibited far better efficacy when repurposed against SARS-CoV-2. The chemistry that accounts for this difference is the subject of this study. Here, we examine the hypothesis that remdesivir monophosphate (RMP)-containing RNA functions as a template at the polymerase site for the second run of RNA synthesis, and as mRNA at the decoding center for protein synthesis. Our hypothesis is supported by the observation that RMP can be incorporated into RNA by the RNA-dependent RNA polymerases (RdRps) of both viruses, although some of the incorporated RMPs are subsequently removed by exoribonucleases. Furthermore, our hypothesis is consistent with the fact that RdRp of SARS-CoV-2 selects RMP for incorporation over AMP by 3-fold in vitro, and that RMP-added RNA can be rapidly extended, even though primer extension is often paused when the added RMP is translocated at the i + 3 position (with i the nascent base pair at an initial insertion site of RMP) or when the concentrations of the subsequent nucleoside triphosphates (NTPs) are below their physiological concentrations. These observations have led to the hypothesis that remdesivir might be a delayed chain terminator. However, that hypothesis is challenged under physiological concentrations of NTPs by the observation that approximately three-quarters of RNA products efficiently overrun the pause.

Development of a Simple In Vitro Assay To Identify and Evaluate Nucleotide Analogs against SARS-CoV-2 RNA-Dependent RNA Polymerase.

Nucleotide analogs targeting viral RNA polymerase have been proved to be an effective strategy for antiviral treatment and are promising antiviral drugs to combat the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. In this study, we developed a robust in vitro nonradioactive primer extension assay to quantitatively evaluate the efficiency of incorporation of nucleotide analogs by SARS-CoV-2 RNA-dependent RNA polymerase (RdRp). Our results show that many nucleotide analogs can be incorporated into RNA by SARS-CoV-2 RdRp and that the incorporation of some of them leads to chain termination. The discrimination values of nucleotide analogs over those of natural nucleotides were measured to evaluate the incorporation efficiency of nucleotide analog by SARS-CoV-2 RdRp. In agreement with the data published in the literature, we found that the incorporation efficiency of remdesivir-TP is higher than that of ATP and incorporation of remdesivir-TP caused delayed chain termination, which can be overcome by higher concentrations of the next nucleotide to be incorporated. Our data also showed that the delayed chain termination pattern caused by remdesivir-TP incorporation is different for different template sequences. Multiple incorporations of remdesivir-TP caused chain termination under our assay conditions. Incorporation of sofosbuvir-TP is very low, suggesting that sofosbuvir may not be very effective in treating SARS-CoV-2 infection. As a comparison, 2'-C-methyl-GTP can be incorporated into RNA efficiently, and the derivative of 2'-C-methyl-GTP may have therapeutic application in treating SARS-CoV-2 infection. This report provides a simple screening method that should be useful for evaluating nucleotide-based drugs targeting SARS-CoV-2 RdRp and for studying the mechanism of action of selected nucleotide analogs.

Markov state modeling reveals alternative unbinding pathways for peptide-MHC complexes.

Peptide binding to major histocompatibility complexes (MHCs) is a central component of the immune system, and understanding the mechanism behind stable peptide-MHC binding will aid the development of immunotherapies. While MHC binding is mostly influenced by the identity of the so-called anchor positions of the peptide, secondary interactions from nonanchor positions are known to play a role in complex stability. However, current MHC-binding prediction methods lack an analysis of the major conformational states and might underestimate the impact of secondary interactions. In this work, we present an atomically detailed analysis of peptide-MHC binding that can reveal the contributions of any interaction toward stability. We propose a simulation framework that uses both umbrella sampling and adaptive sampling to generate a Markov state model (MSM) for a coronavirus-derived peptide (QFKDNVILL), bound to one of the most prevalent MHC receptors in humans (HLA-A24:02). While our model reaffirms the importance of the anchor positions of the peptide in establishing stable interactions, our model also reveals the underestimated importance of position 4 (p4), a nonanchor position. We confirmed our results by simulating the impact of specific peptide mutations and validated these predictions through competitive binding assays. By comparing the MSM of the wild-type system with those of the D4A and D4P mutations, our modeling reveals stark differences in unbinding pathways. The analysis presented here can be applied to any peptide-MHC complex of interest with a structural model as input, representing an important step toward comprehensive modeling of the MHC class I pathway.