Structural insight into the binding interactions of NTPs and nucleotide analogues to RNA dependent RNA polymerase of SARS-CoV-2

Markov State Models: To Optimize or Not to Optimize

Markov state models (MSM) are a popular statistical method for analyzing the conformational dynamics of proteins including protein folding. With all statistical and machine learning (ML) models, choices must be made about the modeling pipeline that cannot be directly learned from the data. These choices, or hyperparameters, are often evaluated by expert judgment or, in the case of MSMs, by maximizing variational scores such as the VAMP-2 score. Modern ML and statistical pipelines often use automatic hyperparameter selection techniques ranging from the simple, choosing the best score from a random selection of hyperparameters, to the complex, optimization via, e.g., Bayesian optimization. In this work, we ask whether it is possible to automatically select MSM models this way by estimating and analyzing over 16,000,000 observations from over 280,000 estimated MSMs. We find that differences in hyperparameters can change the physical interpretation of the optimization objective, making automatic selection difficult. In addition, we find that enforcing conditions of equilibrium in the VAMP scores can result in inconsistent model selection. However, other parameters that specify the VAMP-2 score (lag time and number of relaxation processes scored) have only a negligible influence on model selection. We suggest that model observables and variational scores should be only a guide to model selection and that a full investigation of the MSM properties should be undertaken when selecting hyperparameters.

Trapping a non-cognate nucleotide upon initial binding for replication fidelity control in SARS-CoV-2 RNA dependent RNA polymerase

The RNA dependent RNA polymerase (RdRp) in SARS-CoV-2 is a highly conserved enzyme responsible for viral genome replication/transcription. To understand how the viral RdRp achieves fidelity control during such processes, here we computationally investigate the natural non-cognate vs. cognate nucleotide addition and selectivity during viral RdRp elongation. We focus on the nucleotide substrate initial binding (RdRp active site open) to the prechemical insertion (active site closed) of the RdRp. The current studies were first carried out using microsecond ensemble equilibrium all-atom molecular dynamics (MD) simulations. Due to the slow conformational changes (from open to closed) during nucleotide insertion and selection, enhanced or umbrella sampling methods have been further employed to calculate the free energy profiles of the nucleotide insertion. Our studies find notable stability of noncognate dATP and GTP upon initial binding in the active-site open state. The results indicate that while natural cognate ATP and Remdesivir drug analogue (RDV-TP) are biased toward stabilization in the closed state to facilitate insertion, the natural non-cognate dATP and GTP can be well trapped in off-path initial binding configurations and prevented from insertion so that to be further rejected. The current work thus presents the intrinsic nucleotide selectivity of SARS-CoV-2 RdRp for natural substrate fidelity control, which should be considered in antiviral drug design.

Identification of potential targets against SARS-CoV-2 of antiviral drugs based on photoaffinity probes

Facing the sudden outbreak of coronavirus disease 2019 (COVID-19), it is extremely urgent to develop effective antiviral drugs against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Drug repurposing is a promising strategy for the treatment of COVID-19. To identify the precise target protein of marketed medicines, we initiate a chemical biological program to identify precise target of potential antivirus drugs. In this study, two types of recombinant human coronavirus SARS-CoV-2 RdRp protein capturing probes with various photoaffinity labeling units were designed and synthesized based on the structure of FDA-approved drugs stavudine, remdesivir, acyclovir, and aladenosine. Fortunately, it was found that one novel photoaffinity probe, RD-1, could diaplayed good affinity with SARS-CoV-2 RdRp around the residue ARG_553. In addition, RD-1 probe also exhibited potent inhibitory activity against 3CLpro protease. Taken together, our findings will elucidate the structural basis for the efficacy of marketed drugs, and explore a rapid and efficient strategy of drug repurposing based on the identification of new targets. Moreover, these results could also provide a scientific basis for the clinical application of marketed drugs.

Unveiling the "Template-Dependent" Inhibition on the Viral Transcription of SARS-CoV-2

Remdesivir is one nucleotide analogue prodrug capable to terminate RNA synthesis in SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) by two distinct mechanisms. Although the "delayed chain termination" mechanism has been extensively investigated, the "template-dependent" inhibitory mechanism remains elusive. In this study, we have demonstrated that remdesivir embedded in the template strand seldom directly disrupted the complementary NTP incorporation at the active site. Instead, the translocation of remdesivir from the +2 to the +1 site was hindered due to the steric clash with V557. Moreover, we have elucidated the molecular mechanism characterizing the drug resistance upon V557L mutation. Overall, our studies have provided valuable insight into the "template-dependent" inhibitory mechanism exerted by remdesivir on SARS-CoV-2 RdRp and paved venues for an alternative antiviral strategy for the COVID-19 pandemic. As the "template-dependent" inhibition occurs across diverse viral RdRps, our findings may also shed light on a common acting mechanism of inhibitors.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

Putative Repurposing of Lamivudine, a Nucleoside/Nucleotide Analogue and Antiretroviral to Improve the Outcome of Cancer and COVID-19 Patients

Lamivudine, also widely known as 3TC belongs to a family of nucleotide/nucleoside analogues of cytidine or cytosine that inhibits the Reverse Transcriptase (RT) of retroviruses such as HIV. Lamivudine is currently indicated in combination with other antiretroviral agents for the treatment of HIV-1 infection or for chronic Hepatitis B (HBV) virus infection associated with evidence of hepatitis B viral replication and active liver inflammation. HBV reactivation in patients with HBV infections who receive anticancer chemotherapy can be a life-threatening complication during and after the completion of chemotherapy. Lamivudine is used, as well as other antiretrovirals, to prevent the reactivation of the Hepatitis B virus during and after chemotherapy. In addition, Lamivudine has been shown to sensitize cancer cells to chemotherapy. Lamivudine and other similar analogues also have direct positive effects in the prevention of cancer in hepatitis B or HIV positive patients, independently of chemotherapy or radiotherapy. Recently, it has been proposed that Lamivudine might be also repurposed against SARS-CoV-2 in the context of the COVID-19 pandemic. In this review we first examine recent reports on the re-usage of Lamivudine or 3TC against the SARS-CoV-2, and we present docking evidence carried out in silico suggesting that Lamivudine may bind and possibly work as an inhibitor of the SARS-CoV-2 RdRp RNA polymerase. We also evaluate and propose assessment of repurposing Lamivudine as anti-SARS-CoV-2 and anti-COVID-19 antiviral. Secondly, we summarize the published literature on the use of Lamivudine or (3TC) before or during chemotherapy to prevent reactivation of HBV, and examine reports of enhanced effectiveness of radiotherapy in combination with Lamivudine treatment against the cancerous cells or tissues. We show that the anti-cancer properties of Lamivudine are well established, whereas its putative anti-COVID effect is under investigation. The side effects of lamivudine and the appearance of resistance to 3TC are also discussed.

N. M, Sonavane U, Joshi R. Natural plant products as potential inhibitors of RNA dependent RNA polymerase of Severe Acute Respiratory Syndrome Coronavirus-2

Drug repurposing studies targeting inhibition of RNA dependent RNA polymerase (RdRP) of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) have exhibited the potential effect of small molecules. In the present work a detailed interaction study between the phytochemicals from Indian medicinal plants and the RdRP of SARS-CoV-2 has been performed. The top four phytochemicals obtained through molecular docking were, swertiapuniside, cordifolide A, sitoindoside IX, and amarogentin belonging to Swertia chirayita, Tinospora cordifolia and Withania somnifera. These ligands bound to the RdRP were further studied using molecular dynamics simulations. The principal component analysis of these systems showed significant conformational changes in the finger and thumb subdomain of the RdRP. Hydrogen bonding, salt-bridge and water mediated interactions supported by MM-GBSA free energy of binding revealed strong binding of cordifolide A and sitoindoside IX to RdRP. The ligand-interacting residues belonged to either of the seven conserved motifs of the RdRP. These residues were polar and charged amino acids, namely, ARG 553, ARG 555, ASP 618, ASP 760, ASP 761, GLU 811, and SER 814. The glycosidic moieties of the phytochemicals were observed to form favourable interactions with these residues. Hence, these phytochemicals may hold the potential to act as RdRP inhibitors owing to their stability in binding to the druggable site.