Crystal structures of SARS-CoV-2 ADP-ribose phosphatase: from the apo form to ligand complexes

In silico-based screening of natural products as potential inhibitors of SARS-CoV-2 macrodomain 1

The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide has led to over 600 million cases of coronavirus disease 2019 (COVID-19). Identifying effective molecules that can counteract the virus is imperative. SARS-CoV-2 macrodomain 1 (Mac1) represents a promising antiviral drug target. In this study, we predicted potential inhibitors of SARS-CoV-2 Mac1 from natural products using in silico-based screening. Based on the high-resolution crystal structure of Mac1 bound to its endogenous ligand ADP-ribose (ADPr), we first performed a docking-based virtual screening of Mac1 inhibitors against a natural product library and obtained five representative compounds (MC1-MC5) by clustering analysis. All five compounds were stably bound to Mac1 during 500 ns long molecular dynamics simulations. The binding free energy of these compounds to Mac1 was calculated using molecular mechanics generalized Born surface area and further refined with localized volume-based metadynamics. The results demonstrated that both MC1 (-9.8 ± 0.3 kcal/mol) and MC5 (-9.6 ± 0.3 kcal/mol) displayed more favorable affinities to Mac1 with respect to ADPr (-8.9 ± 0.3 kcal/mol), highlighting their potential as potent SARS-CoV-2 Mac1 inhibitors. Overall, this study provides potential SARS-CoV-2 Mac1 inhibitors, which may pave the way for developing effective therapeutics for COVID-19.Communicated by Ramaswamy H. Sarma.

Discovery of 2-Amide-3-methylester Thiophenes that Target SARS-CoV-2 Mac1 and Repress Coronavirus Replication, Validating Mac1 as an Antiviral Target

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has made it clear that further development of antiviral therapies will be needed. Here, we describe small-molecule inhibitors for SARS-CoV-2 Mac1, which counters ADP-ribosylation-mediated innate immune responses. Three high-throughput screening hits had the same 2-amide-3-methylester thiophene scaffold. We studied the compound binding mode using X-ray crystallography, allowing us to design analogues. Compound 27 (MDOLL-0229) had an IC50 of 2.1 μM and was selective for CoV Mac1 proteins after profiling for activity against a panel of viral and human proteins. The improved potency allowed testing of its effect on virus replication, and indeed, 27 inhibited replication of both murine hepatitis virus (MHV) prototypes CoV and SARS-CoV-2. Sequencing of a drug-resistant MHV identified mutations in Mac1, further demonstrating the specificity of 27. Compound 27 is the first Mac1-targeted small molecule demonstrated to inhibit coronavirus replication in a cell model.

Crystal structure and biochemical activity of the macrodomain from rubella virus p150

Rubella virus encodes a nonstructural polyprotein with RNA polymerase, methyltransferase, and papain-like cysteine protease activities, along with a putative macrodomain of unknown function. Macrodomains bind ADP-ribose adducts, a post-translational modification that plays a key role in host-virus conflicts. Some macrodomains can also remove the mono-ADP-ribose adduct or degrade poly-ADP-ribose chains. Here, we report high-resolution crystal structures of the macrodomain from rubella virus nonstructural protein p150, with and without ADP-ribose binding. The overall fold is most similar to macroD-type macrodomains from various nonviral species. The specific composition and structure of the residues that coordinate ADP-ribose in the rubella virus macrodomain are most similar to those of macrodomains from alphaviruses. Isothermal calorimetry shows that the rubella virus macrodomain binds ADP-ribose in solution. Enzyme assays show that the rubella virus macrodomain can hydrolyze both mono- and poly-ADP-ribose adducts. Site-directed mutagenesis identifies Asn39 and Cys49 required for mono-ADP-ribosylhydrolase (de-MARylation) activity.IMPORTANCERubella virus remains a global health threat. Rubella infections during pregnancy can cause serious congenital pathology, for which no antiviral treatments are available. Our work demonstrates that, like alpha- and coronaviruses, rubiviruses encode a mono-ADP-ribosylhydrolase with a structurally conserved macrodomain fold to counteract MARylation by poly (ADP-ribose) polymerases (PARPs) in the host innate immune response. Our structural data will guide future efforts to develop novel antiviral therapeutics against rubella or infections with related viruses.

Classification, replication, and transcription of Nidovirales

Nidovirales is one order of RNA virus, with the largest single-stranded positive sense RNA genome enwrapped with membrane envelope. It comprises four families (Arterividae, Mesoniviridae, Roniviridae, and Coronaviridae) and has been circulating in humans and animals for almost one century, posing great threat to livestock and poultry，as well as to public health. Nidovirales shares similar life cycle: attachment to cell surface, entry, primary translation of replicases, viral RNA replication in cytoplasm, translation of viral proteins, virion assembly, budding, and release. The viral RNA synthesis is the critical step during infection, including genomic RNA (gRNA) replication and subgenomic mRNAs (sg mRNAs) transcription. gRNA replication requires the synthesis of a negative sense full-length RNA intermediate, while the sg mRNAs transcription involves the synthesis of a nested set of negative sense subgenomic intermediates by a discontinuous strategy. This RNA synthesis process is mediated by the viral replication/transcription complex (RTC), which consists of several enzymatic replicases derived from the polyprotein 1a and polyprotein 1ab and several cellular proteins. These replicases and host factors represent the optimal potential therapeutic targets. Hereby, we summarize the Nidovirales classification, associated diseases, "replication organelle," replication and transcription mechanisms, as well as related regulatory factors.

Mutation of highly conserved residues in loop 2 of the coronavirus macrodomain demonstrates that enhanced ADP-ribose binding is detrimental to infection

All coronaviruses (CoVs) encode for a conserved macrodomain (Mac1) located in nonstructural protein 3 (nsp3). Mac1 is an ADP-ribosylhydrolase that binds and hydrolyzes mono-ADP-ribose from target proteins. Previous work has shown that Mac1 is important for virus replication and pathogenesis. Within Mac1, there are several regions that are highly conserved across CoVs, including the GIF (glycine-isoleucine-phenylalanine) motif. To determine how the biochemical activities of these residues impact CoV replication, the isoleucine and the phenylalanine residues were mutated to alanine (I-A/F-A) in both recombinant Mac1 proteins and recombinant CoVs, including murine hepatitis virus (MHV), Middle East respiratory syndrome coronavirus (MERS-CoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The F-A mutant proteins had ADP-ribose binding and/or hydrolysis defects that led to attenuated replication and pathogenesis in cell culture and mice. In contrast, the I-A mutations had normal enzyme activity and enhanced ADP-ribose binding. Despite increased ADP-ribose binding, I-A mutant MERS-CoV and SARS-CoV-2 were highly attenuated in both cell culture and mice, indicating that this isoleucine residue acts as a gate that controls ADP-ribose binding for efficient virus replication. These results highlight the function of this highly conserved residue and provide unique insight into how macrodomains control ADP-ribose binding and hydrolysis to promote viral replication and pathogenesis.

Targeting SARS-CoV-2 nonstructural protein 3: Function, structure, inhibition, and perspective in drug discovery

As a highly contagious human pathogen, severe acute respiratory syndrome-associated coronavirus-2 (SARS-CoV-2) has infected billions of people worldwide with more than 6 million deaths. With several effective vaccines and antiviral drugs now available, the SARS-CoV-2 pandemic been brought under control. However, a new pathogenic coronavirus could emerge in the future, given the zoonotic nature of this virus. Natural evolution and drug-induced mutations of SARS-CoV-2 also require continued efforts for new anti-coronavirus drugs. Nonstructural protein (nsp) 3 of CoVs is a large, multifunctional protein, containing a papain-like protease (PLpro) and a macrodomain (Mac1), which are essential for viral replication. Here, we provide a comprehensive review of the function, structure, and inhibition of SARS-CoV/-CoV-2 PLpro and Mac1. We also discuss advances in, and challenges to, the discovery of drugs against these targets.

Discovery of 2-amide-3-methylester thiophenes that target SARS-CoV-2 Mac1 and repress coronavirus replication, validating Mac1 as an anti-viral target

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has made it clear that further development of antiviral therapies will be needed to combat additional SARS-CoV-2 variants or novel CoVs. Here, we describe small molecule inhibitors for SARS-CoV-2 Mac1, which counters ADP-ribosylation mediated innate immune responses. The compounds inhibiting Mac1 were discovered through high-throughput screening (HTS) using a protein FRET-based competition assay and the best hit compound had an IC50 of 14 μM. Three validated HTS hits have the same 2-amide-3-methylester thiophene scaffold and the scaffold was selected for structure-activity relationship (SAR) studies through commercial and synthesized analogs. We studied the compound binding mode in detail using X-ray crystallography and this allowed us to focus on specific features of the compound and design analogs. Compound 27 (MDOLL-0229) had an IC50 of 2.1 μM and was generally selective for CoV Mac1 proteins after profiling for activity against a panel of viral and human ADP-ribose binding proteins. The improved potency allowed testing of its effect on virus replication and indeed, 27 inhibited replication of both MHVa prototype CoV, and SARS-CoV-2. Furthermore, sequencing of a drug-resistant MHV identified mutations in Mac1, further demonstrating the specificity of 27. Compound 27 is the first Mac1 targeted small molecule demonstrated to inhibit coronavirus replication in a cell model. This, together with its well-defined binding mode, makes 27 a good candidate for further hit/lead-optimization efforts.

In silico evaluation of S-adenosyl-L-homocysteine analogs as inhibitors of nsp14-viral cap N7 methyltranferase and PLpro of SARS-CoV-2: synthesis, molecular docking, physicochemical data, ADMET and molecular dynamics simulations studies

A series of S-adenosyl-L-homosysteine (SAH) analogs, with modification in the base and sugar moiety, have been designed, synthesized and screened as nsp14 and PLpro inhibitors of severe acute respiratory syndrome corona virus (SARS-CoV-2). The outcomes of ADMET (Adsorption, Distribution, Metabolism, Excretion, and Toxicity) studies demonstrated that the physicochemical properties of all analogs were permissible for development of these SAH analogs as antiviral agents. All molecules were screened against different SARS-CoV-2 targets using molecular docking. The docking results revealed that the SAH analogs interacted well in the active site of nsp14 protein having H-bond interactions with the amino acid residues Arg289, Val290, Asn388, Arg400, Phe401 and π-alkyl interactions with Arg289, Val290 and Phe426 of Nsp14-MTase site. These analogs also formed stable H-bonds with Leu163, Asp165, Arg167, Ser246, Gln270, Tyr274 and Asp303 residues of PLpro proteins and found to be quite stable complexes therefore behaved as probable nsp14 and PLpro inhibitors. Interestingly, analog 3 showed significant in silico activity against the nsp14 N7 methyltransferase of SARS-CoV-2. The molecular dynamics (MD) and post-MD results of analog 3 unambiguously established the higher stability of the nsp14 (N7 MTase):3 complex and also indicated its behavior as probable nsp14 inhibitor like the reference sinefungin. The docking and MD simulations studies also suggested that sinefungin did act as SARS-CoV-2 PLpro inhibitor as well. This study's findings not only underscore the efficacy of the designed SAH analogs as potent inhibitors against crucial SARS-CoV-2 proteins but also pinpoint analog 3 as a particularly promising candidate. All the study provides valuable insights, paving the way for potential advancements in antiviral drug development against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Structure-Based High-Throughput Virtual Screening and Molecular Dynamics Simulation for the Discovery of Novel SARS-CoV-2 NSP3 Mac1 Domain Inhibitors

Since the emergence of SARS-CoV-2, many genetic variations within its genome have been identified, but only a few mutations have been found in nonstructural proteins (NSPs). Among this class of viral proteins, NSP3 is a multidomain protein with 16 different domains, and its largest domain is known as the macrodomain or Mac1 domain. In this study, we present a virtual screening campaign in which we computationally evaluated the NCI anticancer library against the NSP3 Mac1 domain, using Molegro Virtual Docker. The top hits with the best MolDock and Re-Rank scores were selected. The physicochemical analysis and drug-like potential of the top hits were analyzed using the SwissADME data server. The binding stability and affinity of the top NSC compounds against the NSP3 Mac1 domain were analyzed using molecular dynamics (MD) simulation, using Desmond software, and their interaction energies were analyzed using the MM/GBSA method. In particular, by applying subsequent computational filters, we identified 10 compounds as possible NSP3 Mac1 domain inhibitors. Among them, after the assessment of binding energies (ΔGbind) on the whole MD trajectories, we identified the four most interesting compounds that acted as strong binders of the NSP3 Mac1 domain (NSC-358078, NSC-287067, NSC-123472, and NSC-142843), and, remarkably, it could be further characterized for developing innovative antivirals against SARS-CoV-2.

Macro1 domain residue F156: A hallmark of SARS-CoV-2 de-MARylation specificity

SARS-CoV-2 is a large, enveloped and positive sense single stranded RNA virus. Its genome codes for 16 non-structural proteins. The largest protein of this complex is nsp3, that contains a well conserved Macro1 domain. Viral Macro domains were shown to bind to mono-ADP-ribose (MAR) and poly-ADP-ribose (PAR) in their free form or conjugated to protein substrates. They carry ADP-ribose hydrolase activities implicated in the regulation of innate immunity. SARS-CoV-2 and SARS-CoV show widely different induction and handling of the host interferon response. Herein, we have conducted a mutational study on the key amino-acid residue F156 in SARS-CoV-2, pinpointed by bioinformatic and structural studies, and its cognate residue N157 in SARS-CoV. Our data suggest that the exchange of these residues slightly modifies ADP-ribose binding, but drastically impacts de-MARylation activity. Alanine substitutions at this position hampers PAR binding, abolishes MAR hydrolysis of SARS-CoV-2, and reduces by 70% this activity in the case of SARS-CoV.

PARPs and ADP-Ribosylation in Chronic Inflammation: A Focus on Macrophages

Aberrant adenosine diphosphate-ribose (ADP)-ribosylation of proteins and nucleic acids is associated with multiple disease processes such as infections and chronic inflammatory diseases. The poly(ADP-ribose) polymerase (PARP)/ADP-ribosyltransferase (ART) family members promote mono- or poly-ADP-ribosylation. Although evidence has linked PARPs/ARTs and macrophages in the context of chronic inflammation, the underlying mechanisms remain incompletely understood. This review provides an overview of literature focusing on the roles of PARP1/ARTD1, PARP7/ARTD14, PARP9/ARTD9, and PARP14/ARTD8 in macrophages. PARPs/ARTs regulate changes in macrophages during chronic inflammatory processes not only via catalytic modifications but also via non-catalytic mechanisms. Untangling complex mechanisms, by which PARPs/ARTs modulate macrophage phenotype, and providing molecular bases for the development of new therapeutics require the development and implementation of innovative technologies.

Deep learning identified genetic variants for COVID-19-related mortality among 28,097 affected cases in UK Biobank

Analysis of host genetic components provides insights into the susceptibility and response to viral infection such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). To reveal genetic determinants of susceptibility to COVID-19 related mortality, we train a deep learning model to identify groups of genetic variants and their interactions that contribute to the COVID-19 related mortality risk using the UK Biobank data (28,097 affected cases and 1656 deaths). We refer to such groups of variants as super variants. We identify 15 super variants with various levels of significance as susceptibility loci for COVID-19 mortality. Specifically, we identify a super variant (odds ratio [OR] = 1.594, p = 5.47 × 10-9 ) on Chromosome 7 that consists of the minor allele of rs76398985, rs6943608, rs2052130, 7:150989011_CT_C, rs118033050, and rs12540488. We also discover a super variant (OR = 1.353, p = 2.87 × 10-8 ) on Chromosome 5 that contains rs12517344, rs72733036, rs190052994, rs34723029, rs72734818, 5:9305797_GTA_G, and rs180899355.

Genetic conservation across SARS-CoV-2 non-structural proteins - Insights into possible targets for treatment of future viral outbreaks

The majority of SARS-CoV-2 therapeutic development work has focussed on targeting the spike protein, viral polymerase and proteases. As the pandemic progressed, many studies reported that these proteins are prone to high levels of mutation and can become drug resistant. Thus, it is necessary to not only target other viral proteins such as the non-structural proteins (NSPs) but to also target the most conserved residues of these proteins. In order to understand the level of conservation among these viruses, in this review, we have focussed on the conservation across RNA viruses, conservation across the coronaviruses and then narrowed our focus to conservation of NSPs across coronaviruses. We have also discussed the various treatment options for SARS-CoV-2 infection. A synergistic melding of bioinformatics, computer-aided drug-design and in vitro/vivo studies can feed into better understanding of the virus and therefore help in the development of small molecule inhibitors against the viral proteins.

Innate immune evasion strategies of SARS-CoV-2

SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has been associated with substantial global morbidity and mortality. Despite a tropism that is largely confined to the airways, COVID-19 is associated with multiorgan dysfunction and long-term cognitive pathologies. A major driver of this biology stems from the combined effects of virus-mediated interference with the host antiviral defences in infected cells and the sensing of pathogen-associated material by bystander cells. Such a dynamic results in delayed induction of type I and III interferons (IFN-I and IFN-III) at the site of infection, but systemic IFN-I and IFN-III priming in distal organs and barrier epithelial surfaces, respectively. In this Review, we examine the relationship between SARS-CoV-2 biology and the cellular response to infection, detailing how antagonism and dysregulation of host innate immune defences contribute to disease severity of COVID-19.

Iterative computational design and crystallographic screening identifies potent inhibitors targeting the Nsp3 macrodomain of SARS-CoV-2

The nonstructural protein 3 (NSP3) of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) contains a conserved macrodomain enzyme (Mac1) that is critical for pathogenesis and lethality. While small-molecule inhibitors of Mac1 have great therapeutic potential, at the outset of the COVID-19 pandemic, there were no well-validated inhibitors for this protein nor, indeed, the macrodomain enzyme family, making this target a pharmacological orphan. Here, we report the structure-based discovery and development of several different chemical scaffolds exhibiting low- to sub-micromolar affinity for Mac1 through iterations of computer-aided design, structural characterization by ultra-high-resolution protein crystallography, and binding evaluation. Potent scaffolds were designed with in silico fragment linkage and by ultra-large library docking of over 450 million molecules. Both techniques leverage the computational exploration of tangible chemical space and are applicable to other pharmacological orphans. Overall, 160 ligands in 119 different scaffolds were discovered, and 153 Mac1-ligand complex crystal structures were determined, typically to 1 Å resolution or better. Our analyses discovered selective and cell-permeable molecules, unexpected ligand-mediated conformational changes within the active site, and key inhibitor motifs that will template future drug development against Mac1.

Efficacy of selected Nigerian tropical plants in the treatment of COVID-19: in silico and in vitro investigations

The whole world is still challenged with COVID-19 pandemic caused by Coronavirus-2 (SARS-CoV-2) which has affected millions of individuals around the globe. Although there are prophylactic vaccines being used, till now, there is ongoing research into discovery of drug candidates for total eradication of all types of coronaviruses. In this context, this study sought to investigate the inhibitory effects of six selected tropical plants against four pathogenic proteins of Coronavirus-2. The medicinal plants used in this study were selected based on their traditional applications in herbal medicine to treat COVID-19 and related symptoms. The biological activities (antioxidant, free radical scavenging, and anti-inflammatory activities) of the extracts of the plants were assessed using different standard procedures. The phytochemicals present in the extracts were identified using GCMS and further screened via in silico molecular docking. The data from this study demonstrated that the phytochemicals of the selected tropical medicinal plants displayed substantial binding affinity to the binding pockets of the four main pathogenic proteins of Coronavirus-2 indicating them as putative inhibitors of Coronavirus-2 and as potential anti-coronavirus drug candidates. The reaction between these phytocompounds and proteins of Coronavirus-2 could alter the pathophysiology of COVID-19, thus mitigating its pathogenic reactions/activities. In conclusion, phytocompounds of these plants exhibited promising binding efficiency with target proteins of SARS-COV-2. Nevertheless, in vitro and in vivo studies are important to potentiate these findings. Other drug techniques or models are vital to elucidate their compatibility and usage as adjuvants in vaccine development against the highly contagious COVID-19 infection.

Computational Bioprospecting Guggulsterone against ADP Ribose Phosphatase of SARS-CoV-2

Coronavirus Disease-2019 (COVID-19) is a highly contagious disease caused by Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2). The World Health Organization (WHO) classified the disease a as global public health hazard on 11 March 2020. Currently, there are no adequate measures to combat viral infections, including COVID-19, and the medication guidelines for the management of COVID-19 are dependent on previous findings from SARS-CoV and MERS-CoV research. Natural products have achieved widespread acceptance around the world as a means of enhancing healthcare and disease prevention. Plants are a potential source of antiviral factors such as flavonoids, phenolic acids, terpenoids, and others. Some of these agents exhibit a broad spectrum of antiviral activity. This study aimed to screen herbal leads for possible inhibitors of the SARS-CoV-2 ADP Ribose Phosphatase enzyme (ARP). Guggulsterone was found to be highly stabilized within the active site of the viral ARP enzyme by molecular dynamic simulation with very little fluctuation throughout the simulation timeframe of 100 ns. Thus, guggulsterone can be further used to develop a safe and competent medication for evolving therapy against SARS-CoV-2 in post-preclinical and clinical trials.

Cytokines and microRNAs in SARS-CoV-2: What do we know?

The coronavirus disease 2019 (COVID-19) pandemic constitutes a global health emergency. Currently, there are no completely effective therapeutic medications for the management of this outbreak. The cytokine storm is a hyperinflammatory medical condition due to excessive and uncontrolled release of pro-inflammatory cytokines in patients suffering from severe COVID-19, leading to the development of acute respiratory distress syndrome (ARDS) and multiple organ dysfunction syndrome (MODS) and even mortality. Understanding the pathophysiology of COVID-19 can be helpful for the treatment of patients. Evidence suggests that the levels of tumor necrosis factor alpha (TNF-α) and interleukin (IL)-1 and IL-6 are dramatically different between mild and severe patients, so they may be important contributors to the cytokine storm. Several serum markers can be predictors for the cytokine storm. This review discusses the cytokines involved in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, focusing on interferons (IFNs) and ILs, and whether they can be used in COVID-19 treatment. Moreover, we highlight several microRNAs that are involved in these cytokines and their role in the cytokine storm caused by COVID-19.

Phytochemical drug discovery for COVID-19 using high-resolution computational docking and machine learning assisted binder prediction

The COVID-19 pandemic has resulted in millions of deaths around the world. Multiple vaccines are in use, but there are many underserved locations that do not have adequate access to them. Variants may emerge that are highly resistant to existing vaccines, and therefore cheap and readily obtainable therapeutics are needed. Phytochemicals, or plant chemicals, can possibly be such therapeutics. Phytochemicals can be used in a polypharmacological approach, where multiple viral proteins are inhibited and escape mutations are made less likely. Finding the right phytochemicals for viral protein inhibition is challenging, but in-silico screening methods can make this a more tractable problem. In this study, we screen a wide range of natural drug products against a comprehensive set of SARS-CoV-2 proteins using a high-resolution computational workflow. This workflow consists of a structure-based virtual screening (SBVS), where an initial phytochemical library was docked against all selected protein structures. Subsequently, ligand-based virtual screening (LBVS) was employed, where chemical features of 34 lead compounds obtained from the SBVS were used to predict 53 lead compounds from a larger phytochemical library via supervised learning. A computational docking validation of the 53 predicted leads obtained from LBVS revealed that 28 of them elicit strong binding interactions with SARS-CoV-2 proteins. Thus, the inclusion of LBVS resulted in a 4-fold increase in the lead discovery rate. Of the total 62 leads, 18 showed promising pharmacokinetic properties in a computational ADME screening. Collectively, this study demonstrates the advantage of incorporating machine learning elements into a virtual screening workflow.Communicated by Ramaswamy H. Sarma.

Molecular basis for the repurposing of histamine H2-receptor antagonist to treat COVID-19

With the world threatened by a second surge in the number of Coronavirus cases, there is an urgent need for the development of effective treatment for the novel coronavirus (COVID-19). Recently, global attention has turned to preliminary reports on the promising anti-COVID-19 effect of histamine H2-receptor antagonists (H2RAs), most especially Famotidine. Therefore, this study was designed to exploit a possible molecular basis for the efficacy of H2RAs against coronavirus. Molecular docking was performed between four H2RAs, Cimetidine, Famotidine, Nizatidine, Ranitidine, and three non-structural proteins viz. NSP3, NSP7/8 complex, and NSP9. Thereafter, a 100 ns molecular dynamics simulation was carried out with the most outstanding ligands to determine the stability. Thereafter, Famotidine and Cimetidine were subjected to gene target prediction analysis using HitPickV2 and eXpression2Kinases server to determine the possible network of genes associated with their anti-COVID activities. Results obtained from molecular docking showed the superiority of Famotidine and Cimetidine compared to other H2RAs with a higher binding affinity to all selected targets. Molecular dynamic simulation and MMPBSA results revealed that Famotidine as well as Cimetidine bind to non-structural proteins more efficiently with high stability over 100 ns. Results obtained suggest that Famotidine and Cimetidine could be a viable option to treat COVID-19 with a mechanism of action that involves the inhibition of viral replication through the inhibition of non-structural proteins. Therefore, Famotidineand Cimetidine qualify for further study as a potential treatment for COVID-19.

Iterative computational design and crystallographic screening identifies potent inhibitors targeting the Nsp3 Macrodomain of SARS-CoV-2

The nonstructural protein 3 (NSP3) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) contains a conserved macrodomain enzyme (Mac1) that is critical for pathogenesis and lethality. While small molecule inhibitors of Mac1 have great therapeutic potential, at the outset of the COVID-19 pandemic there were no well-validated inhibitors for this protein nor, indeed, the macrodomain enzyme family, making this target a pharmacological orphan. Here, we report the structure-based discovery and development of several different chemical scaffolds exhibiting low- to sub-micromolar affinity for Mac1 through iterations of computer-aided design, structural characterization by ultra-high resolution protein crystallography, and binding evaluation. Potent scaffolds were designed with in silico fragment linkage and by ultra-large library docking of over 450 million molecules. Both techniques leverage the computational exploration of tangible chemical space and are applicable to other pharmacological orphans. Overall, 160 ligands in 119 different scaffolds were discovered, and 152 Mac1-ligand complex crystal structures were determined, typically to 1 Å resolution or better. Our analyses discovered selective and cell-permeable molecules, unexpected ligand-mediated protein dynamics within the active site, and key inhibitor motifs that will template future drug development against Mac1.

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.

The mechanisms of catalysis and ligand binding for the SARS-CoV-2 NSP3 macrodomain from neutron and x-ray diffraction at room temperature

The nonstructural protein 3 (NSP3) macrodomain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (Mac1) removes adenosine diphosphate (ADP) ribosylation posttranslational modifications, playing a key role in the immune evasion capabilities of the virus responsible for the coronavirus disease 2019 pandemic. Here, we determined neutron and x-ray crystal structures of the SARS-CoV-2 NSP3 macrodomain using multiple crystal forms, temperatures, and pHs, across the apo and ADP-ribose-bound states. We characterize extensive solvation in the Mac1 active site and visualize how water networks reorganize upon binding of ADP-ribose and non-native ligands, inspiring strategies for displacing waters to increase the potency of Mac1 inhibitors. Determining the precise orientations of active site water molecules and the protonation states of key catalytic site residues by neutron crystallography suggests a catalytic mechanism for coronavirus macrodomains distinct from the substrate-assisted mechanism proposed for human MacroD2. These data provoke a reevaluation of macrodomain catalytic mechanisms and will guide the optimization of Mac1 inhibitors.

In silico evaluation of food-derived carotenoids against SARS-CoV-2 drug targets: Crocin is a promising dietary supplement candidate for COVID-19

The current COVID‐19 pandemic is severely threatening public healthcare systems around the globe. Some supporting therapies such as remdesivir, favipiravir, and ivermectin are still under the process of a clinical trial, it is thus urgent to find alternative treatment and prevention options for SARS‐CoV‐2. In this regard, although many natural products have been tested and/or suggested for the treatment and prophylaxis of COVID‐19, carotenoids as an important class of natural products were underexplored. The dietary supplementation of some carotenoids was already suggested to be potentially effective in the treatment of COVID‐19 due to their strong antioxidant properties. In this study, we performed an in silico screening of common food‐derived carotenoids against druggable target proteins of SARS‐CoV‐2 including main protease, helicase, replication complex, spike protein and its mutants for the recent variants of concern, and ADP‐ribose phosphatase. Molecular docking results revealed that some of the carotenoids had low binding energies toward multiple receptors. Particularly, crocin had the strongest binding affinity (−10.5 kcal/mol) toward the replication complex of SARS‐CoV‐2 and indeed possessed quite low binding energy scores for other targets as well. The stability of crocin in the corresponding receptors was confirmed by molecular dynamics simulations. Our study, therefore, suggests that carotenoids, especially crocin, can be considered an effective alternative therapeutics and a dietary supplement candidate for the prophylaxis and treatment of SARS‐CoV‐2.

Intracellular mono-ADP-ribosyltransferases at the host-virus interphase

The innate immune system, the primary defense mechanism of higher organisms against pathogens including viruses, senses pathogen-associated molecular patterns (PAMPs). In response to PAMPs, interferons (IFNs) are produced, allowing the host to react swiftly to viral infection. In turn the expression of IFN-stimulated genes (ISGs) is induced. Their products disseminate the antiviral response. Among the ISGs conserved in many species are those encoding mono-ADP-ribosyltransferases (mono-ARTs). This prompts the question whether, and if so how, mono-ADP-ribosylation affects viral propagation. Emerging evidence demonstrates that some mono-ADP-ribosyltransferases function as PAMP receptors and modify both host and viral proteins relevant for viral replication. Support for mono-ADP-ribosylation in virus–host interaction stems from the findings that some viruses encode mono-ADP-ribosylhydrolases, which antagonize cellular mono-ARTs. We summarize and discuss the evidence linking mono-ADP-ribosylation and the enzymes relevant to catalyze this reversible modification with the innate immune response as part of the arms race between host and viruses.

In silico analysis of SARS-CoV-2 proteins as targets for clinically available drugs

The ongoing pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires treatments with rapid clinical translatability. Here we develop a multi-target and multi-ligand virtual screening method to identify FDA-approved drugs with potential activity against SARS-CoV-2 at traditional and understudied viral targets. 1,268 FDA-approved small molecule drugs were docked to 47 putative binding sites across 23 SARS-CoV-2 proteins. We compared drugs between binding sites and filtered out compounds that had no reported activity in an in vitro screen against SARS-CoV-2 infection of human liver (Huh-7) cells. This identified 17 "high-confidence", and 97 "medium-confidence" drug-site pairs. The "high-confidence" group was subjected to molecular dynamics simulations to yield six compounds with stable binding poses at their optimal target proteins. Three drugs-amprenavir, levomefolic acid, and calcipotriol-were predicted to bind to 3 different sites on the spike protein, domperidone to the Mac1 domain of the non-structural protein (Nsp) 3, avanafil to Nsp15, and nintedanib to the nucleocapsid protein involved in packaging the viral RNA. Our "two-way" virtual docking screen also provides a framework to prioritize drugs for testing in future emergencies requiring rapidly available clinical drugs and/or treating diseases where a moderate number of targets are known.

The mechanisms of catalysis and ligand binding for the SARS-CoV-2 NSP3 macrodomain from neutron and X-ray diffraction at room temperature

The NSP3 macrodomain of SARS CoV 2 (Mac1) removes ADP-ribosylation post-translational modifications, playing a key role in the immune evasion capabilities of the virus responsible for the COVID-19 pandemic. Here, we determined neutron and X-ray crystal structures of the SARS-CoV-2 NSP3 macrodomain using multiple crystal forms, temperatures, and pHs, across the apo and ADP-ribose-bound states. We characterize extensive solvation in the Mac1 active site, and visualize how water networks reorganize upon binding of ADP-ribose and non-native ligands, inspiring strategies for displacing waters to increase potency of Mac1 inhibitors. Determining the precise orientations of active site water molecules and the protonation states of key catalytic site residues by neutron crystallography suggests a catalytic mechanism for coronavirus macrodomains distinct from the substrate-assisted mechanism proposed for human MacroD2. These data provoke a re-evaluation of macrodomain catalytic mechanisms and will guide the optimization of Mac1 inhibitors.

Structural biology of SARS-CoV-2: open the door for novel therapies

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the causative agent of the pandemic disease COVID-19, which is so far without efficacious treatment. The discovery of therapy reagents for treating COVID-19 are urgently needed, and the structures of the potential drug-target proteins in the viral life cycle are particularly important. SARS-CoV-2, a member of the Orthocoronavirinae subfamily containing the largest RNA genome, encodes 29 proteins including nonstructural, structural and accessory proteins which are involved in viral adsorption, entry and uncoating, nucleic acid replication and transcription, assembly and release, etc. These proteins individually act as a partner of the replication machinery or involved in forming the complexes with host cellular factors to participate in the essential physiological activities. This review summarizes the representative structures and typically potential therapy agents that target SARS-CoV-2 or some critical proteins for viral pathogenesis, providing insights into the mechanisms underlying viral infection, prevention of infection, and treatment. Indeed, these studies open the door for COVID therapies, leading to ways to prevent and treat COVID-19, especially, treatment of the disease caused by the viral variants are imperative.

Computational anti-COVID-19 drug design: progress and challenges

Vaccines have made gratifying progress in preventing the 2019 coronavirus disease (COVID-19) pandemic. However, the emergence of variants, especially the latest delta variant, has brought considerable challenges to human health. Hence, the development of robust therapeutic approaches, such as anti-COVID-19 drug design, could aid in managing the pandemic more efficiently. Some drug design strategies have been successfully applied during the COVID-19 pandemic to create and validate related lead drugs. The computational drug design methods used for COVID-19 can be roughly divided into (i) structure-based approaches and (ii) artificial intelligence (AI)-based approaches. Structure-based approaches investigate different molecular fragments and functional groups through lead drugs and apply relevant tools to produce antiviral drugs. AI-based approaches usually use end-to-end learning to explore a larger biochemical space to design antiviral drugs. This review provides an overview of the two design strategies of anti-COVID-19 drugs, the advantages and disadvantages of these strategies and discussions of future developments.

Databases, DrugBank, and virtual screening platforms for therapeutic development

The upsurge of the severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) has turned into a global health disaster. Many remodeled medications were suggested for treatment in the early stages of this pandemic, but these dosages afterward came across with distinct offshoots. Thus, these consequences compelled the scientists to develop new drugs using various antiviral, antiinflammatory, antibacterial, and phytochemical compounds. A handful of drugs have been scrutinized in silico, in vitro, plus through human trials such as anti-SARS-CoV-2 agents and made available as various databases by various scientific communities. The SARS-CoV-2 pandemic databases are designed to allay difficulties associated with this scenario. Some of the popular databases are GESS (global evaluation of SARS-CoV-2/HCoV-19 sequences) which gives a thorough study of data based on tenfold of thousands of complete coverage and quality of SARS-CoV-2 genomes, CORona Drug InTERactions (CORDITE) database for SARS-CoV-2 which profoundly combines the understanding of potential drugs and make it available for scientists and medicos. SARSCOVIDB set one’s sights to merge all differential gene expression data, at mRNA and protein levels, helping to accelerate analysis and research on the molecular impact of covid-19. This chapter aims to provide a piece of complete information about the SARS-CoV-2 virus databases, potentially available drugs, and virtual screening methods. And also provides a different webserver to reach out for information related to the COVID-19 pandemic and its future.

Virtual screening of phytochemicals by targeting multiple proteins of severe acute respiratory syndrome coronavirus 2: Molecular docking and molecular dynamics simulation studies

OBJECTIVE

Medicinal herbs are being investigated for medicationhg development against SARS-CoV-2 as a rich source of bioactive chemicals. One of the finest approaches for finding therapeutically effective drug molecules in real time is virtual screening scheme such as molecular docking in conjunction with molecular dynamics (MD) simulation. These virtual techniques provide an ample opportunity for the screening of plausible inhibitors of SARS-CoV-2 different target proteins from a comprehensive and extensive phytochemical library. The study was designed to identify potential phytochemicals by virtual screening against different receptor proteins.

METHODS

In the current study, a library of plant secondary metabolites was created by manually curating 120 phytochemicals known to have antimicrobial as well as antiviral properties. In the current study, different potential phytochemicals were identified by virtual screening against various selected receptor proteins (i.e., viral main proteases, RNA-dependent RNA polymerase (RdRp), ADP ribose phosphatase, nonstructural proteins NSP7, NSP8, and NSP9) which are key proteins responsible for transcription, replication and maturation of SARS-CoV-2 in the host. Top three phytochemicals were selected against each viral receptor protein based on their best S-scores, RMSD values, molecular interactions, binding patterns and drug-likeness properties.

RESULTS

The results of molecular docking study revealed that phytochemicals (i.e., baicalin, betaxanthin, epigallocatechin, fomecin A, gallic acid, hortensin, ichangin, kaempferol, limonoic acid, myricetin hexaacetat, pedalitin, quercetin, quercitrin, and silvestrol) have strong antiviral potential against SARS-CoV-2. Additionally, the reported preeminent reliable phytochemicals also revealed toxicity by no means during the evaluation through ADMET profiling. Moreover, the MD simulation study also exhibited thermal stability and stable binding affinity of the pedalitin with SARS-CoV-2 RdRp and SARS-CoV-2 main protease which suggests appreciable efficacy of the lead optimization.

CONCLUSION

The biological activity and pharmacologically distinguishing characteristics of these lead compounds also satisfied as repurposing antiviral drug contenders and are worth substantial evaluation in the biological laboratory for the recommendation of being plausible antiviral drug candidates against SARS-CoV-2.

Novel inhibitors to ADP ribose phosphatase of SARS-CoV-2 identified by structure-based high throughput virtual screening and molecular dynamics simulations

The outbreak of a new coronavirus (SARS-CoV-2) was first identified in Wuhan, People's Republic of China, in 2019, which has led to a severe, life-threatening form of pneumonia (COVID-19). Research scientists all around the world have been trying to find small molecule drugs to treat COVID-19. In the present study, a conserved macrodomain, ADP Ribose phosphatase (ADRP), of a critical non-structural protein (Nsp3) in all coronaviruses was probed using large-scale Molecular Dynamics (MD) simulations to identify novel inhibitors. In our virtual screening workflow, the recently-solved X-ray complex structure, 6W6Y, with a substrate-mimics was used to screen 17 million ZINC15 compounds using drug property filters and Glide docking scores. The top twenty output compounds each underwent 200 ns MD simulations (i.e. 20 × 200 ns) to validate their individual stability as potential inhibitors. Eight out of the twenty compounds showed stable binding modes in the MD simulations, as well as favorable drug properties from our predctions. Therefore, our computational data suggest that the resulting top eight out of twenty compounds could potentially be novel inhibitors to ADRP of SARS-CoV-2.

A molecular toolbox for ADP-ribosyl binding proteins

Proteins interacting with ADP-ribosyl groups are often involved in disease-related pathways or viral infections, making them attractive drug targets. We present a robust and accessible assay applicable to both hydrolyzing or non-hydrolyzing binders of mono- and poly-ADP-ribosyl groups. This technology relies on a C-terminal tag based on a Gi protein alpha subunit peptide (GAP), which allows for site-specific introduction of cysteine-linked mono- and poly-ADP-ribosyl groups or analogs. By fusing the GAP-tag and ADP-ribosyl binders to fluorescent proteins, we generate robust FRET partners and confirm the interaction with 22 known ADP-ribosyl binders. The applicability for high-throughput screening of inhibitors is demonstrated with the SARS-CoV-2 nsp3 macrodomain, for which we identify suramin as a moderate-affinity yet non-specific inhibitor. High-affinity ADP-ribosyl binders fused to nanoluciferase complement this technology, enabling simple blot-based detection of ADP-ribosylated proteins. All these tools can be produced in Escherichia coli and will help in ADP-ribosylation research and drug discovery.

pyKVFinder: an efficient and integrable Python package for biomolecular cavity detection and characterization in data science

BACKGROUND

Biomolecular interactions that modulate biological processes occur mainly in cavities throughout the surface of biomolecular structures. In the data science era, structural biology has benefited from the increasing availability of biostructural data due to advances in structural determination and computational methods. In this scenario, data-intensive cavity analysis demands efficient scripting routines built on easily manipulated data structures. To fulfill this need, we developed pyKVFinder, a Python package to detect and characterize cavities in biomolecular structures for data science and automated pipelines.

RESULTS

pyKVFinder efficiently detects cavities in biomolecular structures and computes their volume, area, depth and hydropathy, storing these cavity properties in NumPy arrays. Benefited from Python ecosystem interoperability and data structures, pyKVFinder can be integrated with third-party scientific packages and libraries for mathematical calculations, machine learning and 3D visualization in automated workflows. As proof of pyKVFinder's capabilities, we successfully identified and compared ADRP substrate-binding site of SARS-CoV-2 and a set of homologous proteins with pyKVFinder, showing its integrability with data science packages such as matplotlib, NGL Viewer, SciPy and Jupyter notebook.

CONCLUSIONS

We introduce an efficient, highly versatile and easily integrable software for detecting and characterizing biomolecular cavities in data science applications and automated protocols. pyKVFinder facilitates biostructural data analysis with scripting routines in the Python ecosystem and can be building blocks for data science and drug design applications.

Pandemic drugs at pandemic speed: infrastructure for accelerating COVID-19 drug discovery with hybrid machine learning- and physics-based simulations on high-performance computers

The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottleneck screening the vast number of potential small molecules to shortlist lead compounds for antiviral drug development. New opportunities to accelerate drug discovery lie at the interface between machine learning methods, in this case, developed for linear accelerators, and physics-based methods. The two in silico methods, each have their own advantages and limitations which, interestingly, complement each other. Here, we present an innovative infrastructural development that combines both approaches to accelerate drug discovery. The scale of the potential resulting workflow is such that it is dependent on supercomputing to achieve extremely high throughput. We have demonstrated the viability of this workflow for the study of inhibitors for four COVID-19 target proteins and our ability to perform the required large-scale calculations to identify lead antiviral compounds through repurposing on a variety of supercomputers.

A structural view of the SARS-CoV-2 virus and its assembly

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Structural biology plays a vital role in SARS-CoV-2 vaccine and treatment.

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High-resolution structures of SARS-CoV-2 proteins and complexes have been obtained.

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In situ structures of SARS-CoV-2 virus and its assembly are visualized by cryoET.

The SARS-CoV-2 pandemic that struck in 2019 has left the world crippled with hundreds of millions of cases and millions of people dead. During this time, we have seen unprecedented support and collaboration amongst scientists to respond to this deadly disease. Advances in the field of structural biology, in particular cryoEM and cryo-electron tomography, have allowed unprecedented structural analysis of SARS-CoV-2. Here, we review the structural work on the SARS-CoV-2 virus and viral components, as well as its cellular assembly process, highlighting some important structural findings that have made significant impact on the protection from and treatment of emerging viral infections.

Special Features of COVID-19 in the FMODB: Fragment Molecular Orbital Calculations and Interaction Energy Analysis of SARS-CoV-2-Related Proteins

SARS-CoV-2 is the causative agent of coronavirus (known as COVID-19), the virus causing the current pandemic. There are ongoing research studies to develop effective therapeutics and vaccines against COVID-19 using various methods and many results have been published. The structure-based drug design of SARS-CoV-2-related proteins is promising, however, reliable information regarding the structural and intra- and intermolecular interactions is required. We have conducted studies based on the fragment molecular orbital (FMO) method for calculating the electronic structures of protein complexes and analyzing their quantitative molecular interactions. This enables us to extensively analyze the molecular interactions in residues or functional group units acting inside the protein complexes. Such precise interaction data are available in the FMO database (FMODB) (https://drugdesign.riken.jp/FMODB/). Since April 2020, we have performed several FMO calculations on the structures of SARS-CoV-2-related proteins registered in the Protein Data Bank. We have published the results of 681 structures, including three structural proteins and 11 nonstructural proteins, on the COVID-19 special page (as of June 8, 2021). In this paper, we describe the entire COVID-19 special page of the FMODB and discuss the calculation results for various proteins. These data not only aid the interpretation of experimentally determined structures but also the understanding of protein functions, which is useful for rational drug design for COVID-19.

An overview of potential inhibitors targeting non-structural proteins 3 (PLpro and Mac1) and 5 (3CLpro/Mpro) of SARS-CoV-2

There is an urgent need to develop effective treatments for coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The rapid spread of SARS-CoV-2 has resulted in a global pandemic that has not only affected the daily lives of individuals but also had a significant impact on the global economy and public health. Although extensive research has been conducted to identify inhibitors targeting SARS-CoV-2, there are still no effective treatment strategies to combat COVID-19. SARS-CoV-2 comprises two important proteolytic enzymes, namely, the papain-like proteinase, located within non-structural protein 3 (nsp3), and nsp5, both of which cleave large replicase polypeptides into multiple fragments that are required for viral replication. Moreover, a domain within nsp3, known as the macrodomain (Mac1), also plays an important role in viral replication. Inhibition of their functions should be able to significantly interfere with the replication cycle of the virus, and therefore these key proteins may serve as potential therapeutic targets. The functions of the above viral targets and their corresponding inhibitors have been summarized in the current review. This review provides comprehensive updates of nsp3 and nsp5 inhibitor development and would help advance the discovery of novel anti-viral therapeutics against SARS-CoV-2.

A critical overview of computational approaches employed for COVID-19 drug discovery

COVID-19 has resulted in huge numbers of infections and deaths worldwide and brought the most severe disruptions to societies and economies since the Great Depression. Massive experimental and computational research effort to understand and characterize the disease and rapidly develop diagnostics, vaccines, and drugs has emerged in response to this devastating pandemic and more than 130 000 COVID-19-related research papers have been published in peer-reviewed journals or deposited in preprint servers. Much of the research effort has focused on the discovery of novel drug candidates or repurposing of existing drugs against COVID-19, and many such projects have been either exclusively computational or computer-aided experimental studies. Herein, we provide an expert overview of the key computational methods and their applications for the discovery of COVID-19 small-molecule therapeutics that have been reported in the research literature. We further outline that, after the first year the COVID-19 pandemic, it appears that drug repurposing has not produced rapid and global solutions. However, several known drugs have been used in the clinic to cure COVID-19 patients, and a few repurposed drugs continue to be considered in clinical trials, along with several novel clinical candidates. We posit that truly impactful computational tools must deliver actionable, experimentally testable hypotheses enabling the discovery of novel drugs and drug combinations, and that open science and rapid sharing of research results are critical to accelerate the development of novel, much needed therapeutics for COVID-19.

Dynamic landscape mapping of humoral immunity to SARS-CoV-2 identifies non-structural protein antibodies associated with the survival of critical COVID-19 patients

A comprehensive analysis of the humoral immune response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential in understanding COVID-19 pathogenesis and developing antibody-based diagnostics and therapy. In this work, we performed a longitudinal analysis of antibody responses to SARS-CoV-2 proteins in 104 serum samples from 49 critical COVID-19 patients using a peptide-based SARS-CoV-2 proteome microarray. Our data show that the binding epitopes of IgM and IgG antibodies differ across SARS-CoV-2 proteins and even within the same protein. Moreover, most IgM and IgG epitopes are located within nonstructural proteins (nsps), which are critical in inactivating the host's innate immune response and enabling SARS-CoV-2 replication, transcription, and polyprotein processing. IgM antibodies are associated with a good prognosis and target nsp3 and nsp5 proteases, whereas IgG antibodies are associated with high mortality and target structural proteins (Nucleocapsid, Spike, ORF3a). The epitopes targeted by antibodies in patients with a high mortality rate were further validated using an independent serum cohort (n = 56) and using global correlation mapping analysis with the clinical variables that are associated with COVID-19 severity. Our data provide fundamental insight into humoral immunity during SARS-CoV-2 infection. SARS-CoV-2 immunogenic epitopes identified in this work could also help direct antibody-based COVID-19 treatment and triage patients.

The SARS-CoV-2 Nsp3 macrodomain reverses PARP9/DTX3L-dependent ADP-ribosylation induced by interferon signaling

SARS-CoV-2 nonstructural protein 3 (Nsp3) contains a macrodomain that is essential for coronavirus pathogenesis and is thus an attractive target for drug development. This macrodomain is thought to counteract the host interferon (IFN) response, an important antiviral signalling cascade, via the reversal of protein ADP-ribosylation, a posttranslational modification catalyzed by host poly(ADP-ribose) polymerases (PARPs). However, the main cellular targets of the coronavirus macrodomain that mediate this effect are currently unknown. Here, we use a robust immunofluorescence-based assay to show that activation of the IFN response induces ADP-ribosylation of host proteins and that ectopic expression of the SARS-CoV-2 Nsp3 macrodomain reverses this modification in human cells. We further demonstrate that this assay can be used to screen for on-target and cell-active macrodomain inhibitors. This IFN-induced ADP-ribosylation is dependent on PARP9 and its binding partner DTX3L, but surprisingly the expression of the Nsp3 macrodomain or the deletion of either PARP9 or DTX3L does not impair IFN signaling or the induction of IFN-responsive genes. Our results suggest that PARP9/DTX3L-dependent ADP-ribosylation is a downstream effector of the host IFN response and that the cellular function of the SARS-CoV-2 Nsp3 macrodomain is to hydrolyze this end product of IFN signaling, rather than to suppress the IFN response itself.

Production of Proteins of the SARS-CoV-2 Proteome for Drug Discovery

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the causative agent of the coronavirus disease of 2019 (COVID-19). Its genome encodes two open reading frames for two large proteins, PP1a and PP1ab. Within the two polypeptide stretches, there are two proteases that process the large proteins into 15 discrete proteins essential for the assembly of the virion during its replication. We describe herein the cloning of the genes for these discrete proteins optimized for expression in Escherichia coli, production of the proteins, and their purification to homogeneity. These included all but six: NSP6, which possesses eight transmembrane regions, and five that are small proteins/peptides (E, ORF3b, ORF6, ORF7b, and ORF10). These proteins are intended for experimental validation of small-molecule binders as molecular template hits. The proof of concept was established with the ADP-ribosylhydrolase (ARH) domain of NSP3 in discovery of small-molecule templates that could serve as the basis for further optimization. The hit molecules include one submicromolar and a few low-micromolar binders to the ARH domain. Availability of these proteins in soluble forms opens up the opportunity for discoveries of novel templates with the potential for anti-COVID-19 pharmaceuticals.

Evolution trace of SARS-CoV-2 from January 19 to March 12, 2020, in the United States

As a kind of human betacoronavirus, SARS‐CoV‐2 has endangered globally public health. As of January 2021, the virus had resulted in 2,209,195 deaths. By studying the evolution trend and characteristics of 265 SARS‐CoV‐2 strains in the United States from January to March, it is found that the strains can be divided into six clades, USA clade‐1, USA clade‐2, USA clade‐3, USA clade‐4, USA clade‐5, and USA clade‐6, in which US clade‐1 may be the most ancestral clade, USA clade‐2 is an interim clade of USA clade‐1 and USA clade‐3, the other three clades have similar codon usage pattern, while USA clade‐6 is the newest and most adaptable clade. Mismatch analysis and protein alignment showed that the evolution of the clades arises from some special mutations in viral proteins, which may help the strain to invade, replicate, transcribe and so on. Compared with previous research and classifications, we suggest that clade O in GISAID should not be an independent clade and Wuhan‐Hu‐1 (EPI_ISL_402125) should not be an ancestral reference sequence. Our study decoded the evolutionary dynamic of SARS‐CoV‐2 in the early stage from the United States, which give some clues to infer the current evolution trend of SARS‐CoV‐2 and study the function of viral mutational protein.

Basing on decoding the characteristics and evolution process of SARS‐CoV‐2 in the early stage of the USA, it is suggested that the clade O in GISAID should not be as an independent evolutionary clade by phylogenetic analysis or protein alignment. Secondly, Wuhan‐Hu‐1 (EPI_ISL_402125) should not be as an ancestral reference sequence and its candidate should be EPI_ISL_529213. Thirdly, many unique mutation sites in viral proteins were found to lay foundation to study the function of the mutational protein and to reveal the evolution trend of SARS‐CoV‐2 in coming days.

Unique Mutations in the Murine Hepatitis Virus Macrodomain Differentially Attenuate Virus Replication, Indicating Multiple Roles for the Macrodomain in Coronavirus Replication

All coronaviruses (CoVs) contain a macrodomain, also termed Mac1, in nonstructural protein 3 (nsp3) that binds and hydrolyzes mono-ADP-ribose (MAR) covalently attached to proteins. Despite several reports demonstrating that Mac1 is a prominent virulence factor, there is still a limited understanding of its cellular roles during infection. Currently, most of the information regarding the role of CoV Mac1 during infection is based on a single point mutation of a highly conserved asparagine residue, which makes contact with the distal ribose of ADP-ribose. To determine if additional Mac1 activities contribute to CoV replication, we compared the replication of murine hepatitis virus (MHV) Mac1 mutants, D1329A and N1465A, to the previously mentioned asparagine mutant, N1347A. These residues contact the adenine and proximal ribose in ADP-ribose, respectively. N1465A had no effect on MHV replication or pathogenesis, while D1329A and N1347A both replicated poorly in bone marrow-derived macrophages (BMDMs), were inhibited by PARP enzymes, and were highly attenuated in vivo. Interestingly, D1329A was also significantly more attenuated than N1347A in all cell lines tested. Conversely, D1329A retained some ability to block beta interferon (IFN-β) transcript accumulation compared to N1347A, indicating that these mutations have different effects on Mac1 functions. Combining these two mutations resulted in a virus that was unrecoverable, suggesting that the combined activities of Mac1 are essential for MHV replication. We conclude that Mac1 has multiple functions that promote the replication of MHV, and that these results provide further evidence that Mac1 is a prominent target for anti-CoV therapeutics. IMPORTANCE In the wake of the COVID-19 epidemic, there has been a surge to better understand how CoVs replicate and to identify potential therapeutic targets that could mitigate disease caused by SARS-CoV-2 and other prominent CoVs. The highly conserved macrodomain, also termed Mac1, is a small domain within nonstructural protein 3. It has received significant attention as a potential drug target, as previous studies demonstrated that it is essential for CoV pathogenesis in multiple animal models of infection. However, the functions of Mac1 during infection remain largely unknown. Here, using targeted mutations in different regions of Mac1, we found that Mac1 has multiple functions that promote the replication of MHV, a model CoV, and, therefore, is more important for MHV replication than previously appreciated. These results will help guide the discovery of these novel functions of Mac1 and the development of inhibitory compounds targeting this domain.

Reappraisal of trifluperidol against Nsp3 as a potential therapeutic for novel COVID-19: a molecular docking and dynamics study

Novel COVID-19 is a highly infectious disease that is caused by the recently discovered SARS-CoV-2. It is a fast-spreading disease that urgently requires therapeutics. The current study employed computational regression methods to target the ADP-ribose phosphatase (ADRP) domain of Nsp3 using FDA-approved drugs. Identified leads were further investigated using molecular dynamics simulation (MDS). The screening and MDS results suggest that trifluperidol could be a novel inhibitor of the ADRP domain of Nsp3. Trifluperidol could, therefore, be used to help control the spread of COVID-19, either alone or in combination with antiviral agents.

The search for inhibitors of macrodomains for targeting the readers and erasers of mono-ADP-ribosylation

Macrodomains are evolutionarily conserved structural elements. Many macrodomains feature as binding modules of ADP-ribose, thus participating in the recognition and removal of mono- and poly-ADP-ribosylation. Macrodomains are involved in the regulation of a variety of physiological processes and represent valuable therapeutic targets. Moreover, as part of the nonstructural proteins of certain viruses, macrodomains are also pivotal for viral replication and pathogenesis. Thus, targeting viral macrodomains with inhibitors is considered to be a promising antiviral intervention. In this review, we summarize our current understanding of human and viral macrodomains that are related to mono-ADP-ribosylation, with emphasis on the search for inhibitors. The advances summarized here will be helpful for the design of macrodomain-specific agents for therapeutic and diagnostic applications.

Cnicin as an Anti-SARS-CoV-2: An Integrated In Silico and In Vitro Approach for the Rapid Identification of Potential COVID-19 Therapeutics

Since the emergence of the SARS-CoV-2 pandemic in 2019, it has remained a significant global threat, especially with the newly evolved variants. Despite the presence of different COVID-19 vaccines, the discovery of proper antiviral therapeutics is an urgent necessity. Nature is considered as a historical trove for drug discovery, especially in global crises. During our efforts to discover potential anti-SARS CoV-2 natural therapeutics, screening our in-house natural products and plant crude extracts library led to the identification of C. benedictus extract as a promising candidate. To find out the main chemical constituents responsible for the extract's antiviral activity, we utilized recently reported SARS CoV-2 structural information in comprehensive in silico investigations (e.g., ensemble docking and physics-based molecular modeling). As a result, we constructed protein-protein and protein-compound interaction networks that suggest cnicin as the most promising anti-SARS CoV-2 hit that might inhibit viral multi-targets. The subsequent in vitro validation confirmed that cnicin could impede the viral replication of SARS CoV-2 in a dose-dependent manner, with an IC50 value of 1.18 µg/mL. Furthermore, drug-like property calculations strongly recommended cnicin for further in vivo and clinical experiments. The present investigation highlighted natural products as crucial and readily available sources for developing antiviral therapeutics. Additionally, it revealed the key contributions of bioinformatics and computer-aided modeling tools in accelerating the discovery rate of potential therapeutics, particularly in emergency times like the current COVID-19 pandemic.

Structural genomics and the Protein Data Bank

The field of Structural Genomics arose over the last 3 decades to address a large and rapidly growing divergence between microbial genomic, functional, and structural data. Several international programs took advantage of the vast genomic sequence information and evaluated the feasibility of structure determination for expanded and newly discovered protein families. As a consequence, structural genomics has developed structure-determination pipelines and applied them to a wide range of novel, uncharacterized proteins, often from “microbial dark matter,” and later to proteins from human pathogens. Advances were especially needed in protein production and rapid de novo structure solution. The experimental three-dimensional models were promptly made public, facilitating structure determination of other members of the family and helping to understand their molecular and biochemical functions. Improvements in experimental methods and databases resulted in fast progress in molecular and structural biology. The Protein Data Bank structure repository played a central role in the coordination of structural genomics efforts and the structural biology community as a whole. It facilitated development of standards and validation tools essential for maintaining high quality of deposited structural data.