In silico investigation of potential small molecule inhibitors of the SARS-CoV-2 nsp10-nsp16 methyltransferase complex

Viral RNA capping: Mechanisms and antiviral therapy

RNA capping is an essential trigger for protein translation in eukaryotic cells. Many viruses have evolved various strategies for initiating the translation of viral genes and generating progeny virions in infected cells via synthesizing cap structure or stealing the RNA cap from nascent host messenger ribonucleotide acid (mRNA). In addition to protein translation, a new understanding of the role of the RNA cap in antiviral innate immunity has advanced the field of mRNA synthesis in vitro and therapeutic applications. Recent studies on these viral RNA capping systems have revealed startlingly diverse ways and molecular machinery. A comprehensive understanding of how viruses accomplish the RNA capping in infected cells is pivotal for designing effective broad-spectrum antiviral therapies. Here we systematically review the contemporary insights into the RNA-capping mechanisms employed by viruses causing human and animal infectious diseases, while also highlighting its impact on host antiviral innate immune response. The therapeutic applications of targeting RNA capping against viral infections and the development of RNA-capping inhibitors are also summarized.

A repository of COVID-19 related molecular dynamics simulations and utilisation in the context of nsp10-nsp16 antivirals

The coronavirus disease 2019 (COVID-19) pandemic highlighted the importance of establishing systems and infrastructure to develop vaccines, antiviral drugs, and therapeutic antibodies against emerging pathogens. Typical drug discovery processes involve targeting suitable proteins to effect pathogen replication or to attenuate host responses, by examining either large chemical databases or protein-protein interactions. Following initial screens, molecular dynamics (MD) simulations are critical for gaining further insight into molecular interactions. During the COVID-19 pandemic, many research groups made their simulations widely available, as highlighted by the comprehensive D.E. Shaw Research trajectory database. To investigate protein target sites and evaluate potential lead compounds, we performed over 300 MD simulations relating to COVID-19. We organised our simulations into a repository, which is publicly available at https://epimedlab.org/trajectories/. The trajectories cover a large part of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteome, and the majority of our MD simulations focused on the identification of potential antivirals. For example, we focused on the S-adenosyl-l-methionine binding site of the nsp10-nsp16 complex, a critical component of viral replication, revealing verbascoside as a potential lead. Moreover, we utilised MD trajectories to explore the interface between the spike protein receptor binding domain and human angiotensin-converting enzyme 2 receptor, with the ultimate aim being investigation of new variants in real-time. Overall, MD simulations are a critical component of the in silico drug discovery process and as highlighted throughout the pandemic, data sharing enables accelerated progress. We have organised our extensive collection of COVID-19 related MD trajectories into an easily accessible repository.

Identifying inhibitors of NSP16-NSP10 of SARS-CoV-2 from large databases

The COVID-19 pandemic, which has already claimed millions of lives, continues to pose a serious threat to human health, requiring the development of new effective drugs. Non-structural proteins of SARS-CoV-2 play an important role in viral replication and infection. Among them, NSP16 (non-structured protein 16) and its cofactor NSP10 (non-structured protein 10) perform C2'-O methylation at the 5' end of the viral RNA, which promotes efficient virus replication. Therefore, the NSP16-NSP10 complex becomes an attractive target for drug development. Using a multi-step virtual screening protocol which includes Lipinski's rule, docking, steered molecular dynamics and umbrella sampling, we searched for potential inhibitors from the PubChem and anti-HIV databases. It has been shown that CID 135566620 compound from PubChem is the best candidate with an inhibition constant in the sub-μM range. The Van der Waals interaction was found to be more important than the electrostatic interaction in the binding affinity of this compound to NSP16-NSP10. Further in vitro and in vivo studies are needed to test the activity of the identified compound against COVID-19.Communicated by Ramaswamy H. Sarma.

Computational exploration of the dual role of the phytochemical fortunellin: Antiviral activities against SARS-CoV-2 and immunomodulatory abilities against the host

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infections generate approximately one million virions per day, and the majority of available antivirals are ineffective against it due to the virus's inherent genetic mutability. This necessitates the investigation of concurrent inhibition of multiple SARS-CoV-2 targets. We show that fortunellin (acacetin 7-O-neohesperidoside), a phytochemical, is a promising candidate for preventing and treating coronavirus disease (COVID-19) by targeting multiple key viral target proteins. Fortunellin supports protective immunity while inhibiting pro-inflammatory cytokines and apoptosis pathways and protecting against tissue damage. Fortunellin is a phytochemical found in Gojihwadi kwath, an Indian traditional Ayurvedic formulation with an antiviral activity that is effective in COVID-19 patients. The mechanistic action of its antiviral activity, however, is unknown. The current study comprehensively evaluates the potential therapeutic mechanisms of fortunellin in preventing and treating COVID-19. We have used molecular docking, molecular dynamics simulations, free-energy calculations, host target mining of fortunellin, gene ontology enrichment, pathway analyses, and protein-protein interaction analysis. We discovered that fortunellin reliably binds to key targets that are necessary for viral replication, growth, invasion, and infectivity including Nucleocapsid (N-CTD) (-54.62 kcal/mol), Replicase-monomer at NSP-8 binding site (-34.48 kcal/mol), Replicase-dimer interface (-31.29 kcal/mol), Helicase (-30.02 kcal/mol), Papain-like-protease (-28.12 kcal/mol), 2'-O-methyltransferase (-23.17 kcal/mol), Main-protease (-21.63 kcal/mol), Replicase-monomer at dimer interface (-22.04 kcal/mol), RNA-dependent-RNA-polymerase (-19.98 kcal/mol), Nucleocapsid-NTD (-16.92 kcal/mol), and Endoribonuclease (-16.81 kcal/mol). Furthermore, we identify and evaluate the potential human targets of fortunellin and its effect on the SARS-CoV-2 infected tissues, including normal-human-bronchial-epithelium (NHBE) and lung cells and organoids such as pancreatic, colon, liver, and cornea using a network pharmacology approach. Thus, our findings indicate that fortunellin has a dual role; multi-target antiviral activities against SARS-CoV-2 and immunomodulatory capabilities against the host.

SARS-CoV-2 Non-Structural Proteins and Their Roles in Host Immune Evasion

Coronavirus disease 2019 (COVID-19) has caused an unprecedented global crisis and continues to threaten public health. The etiological agent of this devastating pandemic outbreak is the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). COVID-19 is characterized by delayed immune responses, followed by exaggerated inflammatory responses. It is well-established that the interferon (IFN) and JAK/STAT signaling pathways constitute the first line of defense against viral and bacterial infections. To achieve viral replication, numerous viruses are able to antagonize or hijack these signaling pathways to attain productive infection, including SARS-CoV-2. Multiple studies document the roles of several non-structural proteins (NSPs) of SARS-CoV-2 that facilitate the establishment of viral replication in host cells via immune escape. In this review, we summarize and highlight the functions and characteristics of SARS-CoV-2 NSPs that confer host immune evasion. The molecular mechanisms mediating immune evasion and the related potential therapeutic strategies for controlling the COVID-19 pandemic are also discussed.

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.

Chemical biology and medicinal chemistry of RNA methyltransferases

RNA methyltransferases (MTases) are ubiquitous enzymes whose hitherto low profile in medicinal chemistry, contrasts with the surging interest in RNA methylation, the arguably most important aspect of the new field of epitranscriptomics. As MTases become validated as drug targets in all major fields of biomedicine, the development of small molecule compounds as tools and inhibitors is picking up considerable momentum, in academia as well as in biotech. Here we discuss the development of small molecules for two related aspects of chemical biology. Firstly, derivates of the ubiquitous cofactor S-adenosyl-l-methionine (SAM) are being developed as bioconjugation tools for targeted transfer of functional groups and labels to increasingly visible targets. Secondly, SAM-derived compounds are being investigated for their ability to act as inhibitors of RNA MTases. Drug development is moving from derivatives of cosubstrates towards higher generation compounds that may address allosteric sites in addition to the catalytic centre. Progress in assay development and screening techniques from medicinal chemistry have led to recent breakthroughs, e.g. in addressing human enzymes targeted for their role in cancer. Spurred by the current pandemic, new inhibitors against coronaviral MTases have emerged at a spectacular rate, including a repurposed drug which is now in clinical trial.

In-silico evaluation of bioactive compounds from tea as potential SARS-CoV-2 nonstructural protein 16 inhibitors

BACKGROUND AND AIM

A novel coronavirus, called the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been found to cause COVID-19 in humans and some other mammals. The nonstructural protein 16 (NSP16) of SARS-CoV-2 plays a significant part in the replication of viruses and suppresses the ability of innate immune system to detect the virus. Therefore, inhibiting NSP16 can be a secure path towards identifying a potent medication against SARS-CoV-2. Tea (Camellia sinensis) polyphenols have been reported to exhibit potential treatment options against various viral diseases.

METHODS

We conducted molecular docking and structural dynamics studies with a set of 65 Tea bioactive compounds to illustrate their ability to inhibit NSP16 of SARS-CoV-2. Moreover, post-simulations end state thermodynamic free energy calculations were estimated to strengthen our results.

RESULTS AND CONCLUSION

Six bioactive tea molecules showed better docking scores than the standard molecule sinefungin. These results were further validated by MD simulations, where Theaflavin compound demonstrated lower binding free energy in comparison to the standard molecule sinefungin. The compound theaflavin could be considered as a novel lead compound for further evaluation by in-vitro and in-vivo studies.