N6-methyladenosine (m6A) is the most prevalent post-transcriptional modification in eukaryotic RNA and is also present in various viral RNAs, where it plays a crucial role in regulating the viral life cycle. However, the molecular mechanisms through which viruses regulate host RNA m6A methylation are not fully understood. In this study, we reveal that SARS-CoV-2 and HCoV-OC43 infection enhance host m6A modification by activating the mTORC1 signalling pathway. Specifically, the viral non-structural protein nsp14 upregulates the expression of S-adenosylmethionine synthase MAT2A in an mTORC1-dependent manner. This mTORC1-MAT2A axis subsequently stimulates the synthesis of S-adenosylmethionine (SAM). The increase of SAM then enhances the m6A methylation of host RNA and facilitates viral replication. Our findings uncover a molecular mechanism by which viruses regulate host m6A methylation and provide insights into how SARS-CoV-2 hijacks host cellular epitranscriptomic modifications to promote its replication.

Complement hyperactivation and thrombotic microangiopathy are closely associated with severe COVID-19. Endothelial dysfunction is a key mechanism underlying thrombotic microangiopathy. To address the relationship between endothelial injury, complement activation and thrombotic microangiopathy of severe COVID-19, we wonder whether, and if so, what and how SARS-CoV-2 factors make endothelial cells (ECs) sensitive to complement-mediated cytotoxicity. We revealed that multiple SARS-CoV-2 proteins enhanced complement-mediated cytotoxicity to ECs by inhibiting membrane complement regulatory proteins (CRPs) and enhancing the deposition of complement-recognizing component FCN1. By screening with CRISPR/Cas9-gRNA libraries, we identified that ADAMTS9, SYAP1, and HIGD1A as intrinsic regulators of CD59 on ECs, which were inhibited by the SARS-CoV-2 M, NSP16, and ORF9b proteins. IFN-γ, GM-CSF, and IFN-α upregulated CD55 and CD59, while IFN-γ antagonized the inhibition of CD59 by the three SARS-CoV-2 proteins. So, the deficiency of IFN-γ weakened the protection of ECs by CRPs against complement-mediated injury which may be enhanced during infection. Our findings illustrated the regulation of protection against complement-mediated attack on self-cells by SARS-CoV-2 infection and immune responses, providing insights into endothelial injury, thrombotic microangiopathy, and potential targets for treating severe COVID-19.

COVID-19 is a human respiratory syndrome caused by the infection of the SARS-CoV-2 virus that has a high rate of infection and mortality. Viruses modulate the host machinery by altering cellular mechanisms that favor their replication. One of the mechanisms that viruses exploit is the protein folding and processing of post-translational modifications that occur in the endoplasmic reticulum (ER). When ER function is impaired, there is an accumulation of misfolded proteins leading to endoplasmic reticulum stress (ER stress). To maintain homeostasis, cells trigger an adaptive signaling mechanism called the Unfolded Protein Response (UPR) which helps cells deal with stress, but under severe conditions, can activate the apoptotic cell death mechanism. This study elucidated an activation of a diversity of molecular mechanisms by Brazilian variants of SARS-CoV-2 by a time-resolved and large-scale characterization of SARS-CoV-2-infected cells proteomics and immunoblotting. Furthermore, it was shown that pharmacological UPR modulation could reduce viral release by counteracting the different viral activations of its cellular response. Analysis of human clinical specimens and disease outcomes focusing on ER stress reinforces the importance of UPR modulation as a host regulatory mechanism during viral infection and could point to novel therapeutic targets. SIGNIFICANCE: Since the emergence of SARS-CoV-2 and the consequent COVID-19 pandemic, the rapid emergence of variants of this new coronavirus has been a cause for concern since many of them have significantly higher rates of transmissibility and virulence, being called Variants of Concern (VOC). In this work, we studied the VOCs Gamma (P.1) and Zeta (P.2), also known as Brazilian variants. Constant evidence has reported that there are particularities related to each variant of SARS-CoV-2, with different rates of transmissibility, replication and modulation of host biological processes being observed, in addition to the mutations present in the variants. For this reason, this work focused on infections caused by the Brazilian variants of SARS-CoV-2 in different cell lines, in which we were able to observe that the infections caused by the variants induced endoplasmic reticulum stress in the infected cells and activated the UPR pathways, presenting specific modulations of each variant in this pathway. Furthermore, transcriptome analysis of patients revealed a correlation between ER-related genes and COVID-19 progression. Finally, we observed that the use of UPR modulators in host cells decreased viral release of all variants without affecting cell viability. The data presented in this work complement the observations of other studies that aim to understand the pathogenicity of SARS-CoV-2 VOCs and possible new therapeutic strategies, mainly targeting biological processes related to the endoplasmic reticulum.

Since 2020, numerous compounds have been investigated for their potential use in treating SARS-CoV-2 infections. By identifying the molecular targets during the virus replication process, rationally designed anti-SARS-CoV-2 agents are developed. Among these targets, the main protease (Mpro) is a crucial enzyme required for virus replication, and its highly conserved characteristic make it an important drug target for the development of anti-SARS-CoV-2 drugs. Herein, we utilized warhead-based design strategy to conduct the structural optimization of M-1 developed through virtual screening, leading to a series of novel Mpro inhibitors with 4-(quinolin-2-yl)aniline scaffold. Among them, M-32 exhibited good SARS-CoV-2 Mpro inhibitory activity (IC50 = 5.2 μM) with a nearly 25-fold increase. Isothermal titration calorimetry (ITC) directly proved that M-32 binds directly to SARS-CoV-2 Mpro in an entropy-driven manner. Mass spectrometry (MS) further confirmed the covalent binding ability of M-32 to Mpro. Meanwhile, M-32 effectively inhibited the replication of SARS-CoV-2 in Vero E6 cells (EC50 = 5.29 μM).

Protein-protein interactions (PPIs) regulate essential physiological and pathological processes. Due to their large and shallow binding surfaces, PPIs are often considered challenging drug targets for small molecules. Peptides offer a viable alternative, as they can bind these targets, acting as regulators or mimicking interaction partners. This review focuses on competitive peptides, a class of orthosteric modulators that disrupt PPI formation. We provide a concise yet comprehensive overview of recent advancements in in-silico peptide design, highlighting computational strategies that have improved the efficiency and accuracy of PPI-targeting peptides. Additionally, we examine cutting-edge experimental methods for evaluating PPI-based peptides. By exploring the interplay between computational design and experimental validation, this review presents a structured framework for developing effective peptide therapeutics targeting PPIs in various diseases.

The dual-cleavable nature of the cross-linking technology (DUCCT) enhances the reliable identification of cross-linked peptides via mass spectrometry. The DUCCT approach uses a cross-linking agent that can be selectively cleaved by two different tandem mass spectrometry techniques: collision-induced dissociation (CID) and electron transfer dissociation (ETD). This results in distinct signatures in two independent mass spectra for the same cross-linked precursor, leading to unambiguous identification and the validation of the spectra. In this study, we expanded the application of the DUCCT cross-linker to evaluate the binding domains of a specific cat dander allergen, Fel d 1, which exists as the Fel d 1 A and B protein complex, and a viral spike protein from SARS-CoV-2, which invades host cells. To assess the cross-linked products obtained by DUCCT, we utilized a software tool called Cleave-XL, which effectively identified cross-linked sites using data from CID and ETD. Dual cleavable cross-linking studies identified cross-linked peptides in these complexes, which have been reported in bioinformatics analysis and proposed for immunotherapy using synthetic peptides. A benchmark study was also conducted using a commercial cross-linker disuccinimidyl suberate (DSS). Overall, we expect that DUCCT cross-linking technology will greatly facilitate the rapid screening of binding interfaces, thereby advancing structural biology and cell signaling investigations.

Alzheimer's disease (AD), the most prevalent form of dementia, remains enigmatic in its origins despite the widely accepted "amyloid hypothesis," which implicates amyloid-beta peptide aggregates in its pathogenesis and progression. Despite advancements in technology and healthcare, the incidence of AD continues to rise. The traditional drug development process remains time-consuming, often taking years to bring an AD treatment to market. Drug repurposing has emerged as a promising strategy for developing cost-effective and efficient therapeutic options by identifying new uses for existing approved drugs, thus accelerating drug development.

This study aimed to examine two key drug repurposing methodologies in general diseases and specifically in AD, which are artificial intelligent (AI) approach and molecular docking approach. In addition, the hybrid approach that integrates AI with molecular docking techniques will be explored too.

This study systematically compiled a comprehensive collection of relevant academic articles, scientific papers, and research studies which were published up until November 2024 (as of the writing of this review paper). The final selection of papers was filtered to include studies related to Alzheimer's disease and general diseases, and then categorized into three groups: AI articles, molecular docking articles, and hybrid articles.

As a result, 331 papers were identified that employed AI for drug repurposing in general diseases, and 58 papers focused specifically in AD. For molecular docking in drug repurposing, 588 papers addressed general diseases, while 46 papers were dedicated to AD. The hybrid approach combining AI and molecular docking in drug repurposing has 52 papers for general diseases and 9 for AD. A comparative review was done across the methods, results, strengths, and limitations in those studies. Challenges of drug repurposing in AD are explored and future prospects are proposed.

Drug repurposing emerges as a compelling and effective strategy within AD research. Both AI and molecular docking methods exhibit significant potential in this domain. AI algorithms yield more precise predictions, thus facilitating the exploration of new therapeutic avenues for existing drugs. Similarly, molecular docking techniques revolutionize drug-target interaction modelling, employing refined algorithms to screen extensive drug databases against specific target proteins. This review offers valuable insights for guiding the utilization of AI, molecular docking, or their hybrid in AD drug repurposing endeavors. The hope is to speed up the timeline of drug discovery which could improve the therapeutic approach to AD.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains a threat due to the emergence of variants with increased transmissibility and enhanced escape from immune responses. Like other coronaviruses before, SARS-CoV-2 likely emerged after its transmission from bats. The successful propagation of SARS-CoV-2 in humans might have been facilitated by usurping evolutionarily conserved cellular factors to execute crucial steps in its life cycle, such as the generation of replication organelles-membrane structures where coronaviruses assemble their replication-transcription complex. In this study, we found that RAB5, which is highly conserved across mammals, is a critical host dependency factor for the replication of the SARS-CoV-2 genome. Our results also suggest that SARS-CoV-2 uses RAB5+ membranes to build replication organelles with the aid of COPB1, a component of the COP-I complex, and that the virus protein NSP6 participates in this process. Hence, targeting NSP6 represents a promising approach to interfere with SARS-CoV-2 RNA synthesis and halt its propagation.IMPORTANCEIn this study, we sought to identify the host dependency factors that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uses for the generation of replication organelles: cellular membranous structures that SARS-CoV-2 builds in order to support the replication and transcription of its genome. We uncovered that RAB5 is an important dependency factor for SARS-CoV-2 replication and the generation of replication organelles, and that the viral protein NSP6 participates in this process. Hence, NSP6 represents a promising target to halt SARS-CoV-2 replication.

Coronavirus disease (COVID-19) is still a severe concern, especially in Africa with suboptimal intention rates of vaccination. This flagged the requirement of plant-based remedies as an alternative treatment. In this study we integrated metabolomics and chemometrics approaches with In silico and In vitro approaches to accelerate and unravel compounds from commonly used South African plants that may inhibit SARS-CoV-2 main protease. The selected commonly used plants, Artemisia afra and Artemisia annua, were found to be non-toxic against Vero cells, as determined by the resazurin cell viability assay. Metabolites profiling revealed eighty-one compounds and the top three hit compounds, quercetin 3-O-(6"-acetyl-glucoside), 2"-O-acetylrutin, and quercetin 3-(6"-malonyl-glucoside), had binding affinities of -9.3 kcal/mol, -9.5 kcal/mol, and -9.3 kcal/mol, respectively. The 2"-O-acetyl group of the rutin moiety and quercetin moiety produces a hydrogen bond with the amide nitrogen of His41 and with the side chain carboxylate of Cys145, respectively. Molecular dynamics simulations revealed a stable binding of the docked complexes. In silico observations were validated by In vitro bioassay, which flagged the ability of these compounds to inhibit SARS-CoV-2 3CLpro. The collected analysed data of this study does not only draw special attention to the surfaced 2"-O-acetylrutin as the best suitable inhibitor of SARS-CoV-2 3CLpro, but also indirectly reveals the importance of integrating metabolomics and chemometrics approaches with In silico and In vitro approaches to accelerate and unravel compounds from South African commonly used plants.

The membrane (M) protein of betacoronaviruses is well conserved and has a key role in viral assembly1,2. Here we describe the identification of JNJ-9676, a small-molecule inhibitor targeting the coronavirus M protein. JNJ-9676 demonstrates in vitro nanomolar antiviral activity against SARS-CoV-2, SARS-CoV and sarbecovirus strains from bat and pangolin zoonotic origin. Using cryogenic electron microscopy (cryo-EM), we determined a binding pocket of JNJ-9676 formed by the transmembrane domains of the M protein dimer. Compound binding stabilized the M protein dimer in an altered conformational state between its long and short forms, preventing the release of infectious virus. In a pre-exposure Syrian golden hamster model, JNJ-9676 (25 mg per kg twice per day) showed excellent efficacy, illustrated by a significant reduction in viral load and infectious virus in the lung by 3.5 and 4 log10-transformed RNA copies and 50% tissue culture infective dose (TCID50) per mg lung, respectively. Histopathology scores at this dose were reduced to the baseline. In a post-exposure hamster model, JNJ-9676 was efficacious at 75 mg per kg twice per day even when added at 48 h after infection, when peak viral loads were observed. The M protein is an attractive antiviral target to block coronavirus replication, and JNJ-9676 represents an interesting chemical series towards identifying clinical candidates addressing the current and future coronavirus pandemics.

An accurate spatial representation of protein-protein interaction networks is needed to achieve a realistic and biologically relevant representation of interactomes. Here, we leveraged the spatial information included in Proximity-Dependent Biotin Identification (BioID) interactomes of SARS-CoV-2 proteins to calculate weighted distances and model the organization of the SARS-CoV-2-human interactome in three dimensions (3D) within a cell-like volume. Cell regions with viral occupancy were highlighted, along with the coordination of viral proteins exploiting the cellular machinery. Profiling physical intra-virus and virus-host contacts enabled us to demonstrate both the accuracy and the predictive value of our 3D map for direct interactions, meaning that proteins in closer proximity tend to interact physically. Several functionally important virus-host complexes were detected, and robust structural models were obtained, opening the way to structure-directed drug discovery screens. This PPI discovery pipeline approach brings us closer to a realistic spatial representation of interactomes, which, when applied to viruses or other pathogens, can provide significant information for infection. Thus, it represents a promising tool for coping with emerging infectious diseases.

Bats are reservoirs for numerous viruses that cause serious diseases in other animals and humans. Several mechanisms are proposed to contribute to the tolerance of bats to these pathogens. This study investigates the response of bat cells to double-stranded RNA generated by SARS-CoV-2 replication. Here, we found the involvement of Dicer in the processing of viral genomic RNAs during SARS-CoV-2 infection. Examining RNA sequencing of infected cells, small-interfering RNA (siRNA)-like fragments were found derived from viral RNAs. Depletion of Dicer showed a reduction in these RNAs and an increase in viral loads suggesting unlike other mammals, bats may use Dicer to limit viral replication. This prompted the exploration of key dsRNA sensors in bat cells. Our analysis showed significant upregulation of OAS1 and MX1 in response to dsRNA, while PKR levels remained low, suggesting alternative dsRNA-response mechanisms are present that eschew the common PKR-based system. These results further show how bats employ distinct strategies for antiviral defense that may contribute to tolerating viral infections. They suggest the involvement of Dicer in antiviral mechanisms in bats, a function not observed in other mammals. This highlights a mechanism for bat originating viruses to evolve features that in other animals could cause extreme antiviral responses such as is seen with SARS-CoV-2.

The Syrian hamster (Mesocricetus auratus) has shown promise as a human diseases model, recapitulating features of different human diseases including COVID-19. However, the landscape of its genome and transcriptome has not been systematically dissected, restricting its potential applications.

Here we provide a complete analysis of the genome and transcriptome of the Syrian hamster and found that its lineage diverged from that of the Chinese hamster (Cricetulus griseus) around 29.4 million years ago. 21,387 protein-coding genes were identified, with 90.03% of the 2.56G base pair sequence being anchored to 22 chromosomes. Further comparison of the transcriptomes from 15 tissues of the Syrian hamster revealed that the Syrian hamster shares a pattern of alternative splicing modes more similar to humans, compared to rats and mice. An integrated genomic-transcriptomic analysis revealed that the Syrian hamster also has genetic and biological advantages as a superior animal model for cardiovascular diseases. Strikingly, several genes involved in SARS-COV-2 infection, including ACE2, present a higher homology with humans compared to other rodents and show the same function as their human counterparts.

The detailed molecular characterisation of the Syrian hamster in the present study opens a wealth of fundamental resources from this small rodent for future research into human disease pathology and treatment.

Viral genomes encode viral transcriptional regulators (vTRs) that manipulate host gene expression to facilitate replication and evade immune detection. Nevertheless, their role in non-cancerous diseases remains largely underexplored. Here, we unveiled 268 new candidate vTRs from 14 of the 20 viral families we investigated. We mapped vTRs' genome-wide binding profiles and identified their potential human targets, which were enriched in immune-mediated pathways, neurodegenerative disorders, and cancers. Through vTR DNA-binding preference analysis, 283 virus-specific and human-like motifs were identified. Prioritized Epstein-Barr virus (EBV) vTR target genes were associated with multiple sclerosis (MS), rheumatoid arthritis, and systemic lupus erythematosus. The partitioned heritability study among 19 diseases indicated significant enrichment of these diseases in EBV vTR-binding sites, implicating EBV vTRs' roles in immune-mediated disorders. Finally, drug repurposing analysis pinpointed candidate drugs for MS, asthma, and Alzheimer disease. This study enhances our understanding of vTRs in diverse human diseases and identifies potential therapeutic targets for future investigation.

SARS-CoV-2 virus and its variants remain a global health threat, due to their capacity for rapid evolution. Variants throughout the COVID-19 pandemic exhibited variations in virulence, impacting vaccine protection and disease severity. Investigating nonstructural protein variants is critical to understanding viral evolution and manipulation of host protein interactions. We focus on nonstructural protein 3 (nsp3), with multiple domains with different activities, including viral polyprotein cleavage, host deubiquitylation, de-ISGylation, and double-membrane vesicle formation. Using affinity purification-mass spectrometry (AP-MS), we identify differential protein interactions in nsp3 caused by mutations found in variants identified between 2019 and 2024: Alpha 20I, Beta 20H, Delta 21I, Delta 21J, Gamma 20J, Kappa 21B, Lambda 21G, Omicron 21K, and Omicron 21L. A small set of amino acid substitutions in the N-terminal region of nsp3 (nsp3.1) could be traced to increased interactions with RNA-binding proteins, which are vital in viral replication. Meanwhile, variants of the central region of nsp3 (nsp3.2) were found to share interactions with protein quality control machinery, including ER-associated degradation. In this construct, shared trends in interactor enrichment are observed between Omicron 21K and Delta 21I. These results underscore how minor mutations reshape host interactions, emphasizing the evolutionary arms race between the host and virus. We provide a roadmap to track the interaction changes driven by SARS-CoV-2 variant evolution.

The goal of this research work is to predict protein-protein interactions (PPIs) between the Ebola virus and the host who is at risk of infection. Since there are very limited databases available on the Ebola virus; we have prepared a comprehensive database of all the PPIs between the Ebola virus and human proteins (EbolaInt). Our work focuses on the finding of some new protein-protein interactions between humans and the Ebola virus using some state- of-the-arts machine learning techniques. However, it is basically a two-class problem with a positive interacting dataset and a negative non-interacting dataset. These datasets contain various sequence-based human protein features such as structure of amino acid and conjoint triad and domain-related features. In this research, we have briefly discussed and used some well-known supervised learning approaches to predict PPIs between human proteins and Ebola virus proteins, including K-nearest neighbours (KNN), random forest (RF), support vector machine (SVM), and deep feed-forward multi-layer perceptron (DMLP) etc. We have validated our prediction results using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Our goal with this prediction is to compare all other models' accuracy, precision, recall, and f1-score for predicting these PPIs. In the result section, DMLP is giving the highest accuracy along with the prediction of 2655 potential human target proteins.

Regions on a host protein that interact with virus proteins (exogenous interfaces) frequently overlap with those that interact with other host proteins (endogenous interfaces), resulting in competition between hosts and viruses for these shared interfaces (mimic-targeted interfaces). Yet, the evolutionary consequences of this competitive relationship on the host are not well understood. Here, we integrate experimentally determined structures and homology-based templates of protein complexes with protein-protein interaction networks to construct a high-resolution human-virus structural interaction network. We perform site-specific evolutionary rate analyses on this structural interaction network and find that exogenous-specific interfaces evolve faster than endogenous-specific interfaces. Mimic-targeted interfaces evolve as fast as exogenous-specific interfaces, despite being targeted by both human and virus proteins. Our findings suggest that virus targeting plays a dominant role in host interfacial evolution within the context of domain-domain interactions and that mimic-targeted interfaces on human proteins are the key battleground for a mammalian-specific host-virus evolutionary arms race.

The SARS-CoV-2 nucleocapsid (N) protein is an essential structural element of the virion, playing a crucial role in enclosing the viral genome into a ribonucleoprotein (RNP) assembly, as well as viral replication and transmission. The C-terminal domain of the N-protein (N-CTD) is essential for encapsidation, contributing to the stabilization of the RNP complex. In a previous study, three inhibitors (ceftriaxone, cefuroxime, and ampicillin) were screened for their potential to disrupt the RNA packaging process by targeting the N-protein. However, the binding efficacy, mechanism of RNA binding inhibition, and molecular insights of binding with N-CTD remain unclear. In this study, we evaluated the binding efficacy of these inhibitors using isothermal titration calorimetry (ITC), revealing the affinity of ceftriaxone (18 ± 1.3 μM), cefuroxime (55 ± 4.2 μM), and ampicillin (28 ± 1.2 μM) with the N-CTD. Further inhibition assay and fluorescence polarisation assay demonstrated RNA binding inhibition, with IC50 ranging from ∼ 12 to 18 μM and KD values between 24 μM to 32 μM for the inhibitors, respectively. Additionally, we also determined the inhibitor-bound complex crystal structures of N-CTD-Ceftriaxone (2.0 Å) and N-CTD-Ampicillin (2.2 Å), along with the structure of apo N-CTD (1.4 Å). These crystal structures revealed previously unobserved interaction sites involving residues K261, K266, R293, Q294, and W301 at the oligomerization interface and the predicted RNA-binding region of N-CTD. These findings provide valuable molecular insights into the inhibition of N-CTD, highlighting its potential as an underexplored but promising target for the development of novel antiviral agents against coronaviruses.

The SARS-CoV-2 nucleocapsid (N) protein is crucial for viral replication and modulation of host cell responses. Here, we identify and characterize a novel N-fusion protein, designated NFP. NFP is derived from an alternative open reading frame spanning the N gene and the non-structural protein 1 (NSP1) sequence. While NFP shares some functional domains with the canonical N protein, it exhibits distinct structural features and protein interactions. NFP retains the ability to dimerize and bind RNA but lacks the formation of biomolecular condensates associated with N. Notably, NFP can dominantly interfere with N's condensate formation capacity when co-expressed. Functionally, NFP partially suppresses stress granule (SG) formation through a G3BP1-independent mechanism but gains the ability to interact with G3BP1 in the presence of N, potentially through N-NFP heterodimer formation. Post-translational modifications, particularly ubiquitination of specific lysine residues (K374 in N and K502 in NFP), differentially regulate the subcellular localization, SG inhibition, and cell cycle regulation activities of N and NFP. Our findings establish NFP as a distinct viral effector protein that modulates host cellular environments through both conserved and unique mechanisms compared to the canonical N protein, providing insights into SARS-CoV-2 pathogenesis and potential therapeutic targets.

The coronavirus disease 2019 (COVID-19) pandemic has devastated global health and the economy, underscoring the urgent need for extensive research into the mechanisms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral entry and the development of effective therapeutic interventions.

We established a cell line expressing human angiotensin-converting enzyme 2 (ACE2). We used it as a model of pseudotyped viral entry using murine leukemia virus (MLV) expressing SARS-CoV-2 spike (S) protein on its surface and firefly luciferase as a reporter. We screened an U.S. Food and Drug Administration (FDA)-approved compound library for inhibiting ACE2-dependent SARS-CoV-2 pseudotyped viral entry and identified several drug-repurposing candidates.

We identified 18 drugs and drug candidates, including 14 previously reported inhibitors of viral entry and four novel candidates. Pyridoxal 5'-phosphate, Dovitinib, Adefovir dipivoxil, and Biapenem potently inhibit ACE2-dependent viral entry with inhibitory concentration 50% (IC50) values of 57nM, 74 nM, 130 nM, and 183 nM, respectively.

We identified four novel FDA-approved candidate drugs for anti-SARS-CoV-2 combination therapy. Our findings contribute to the growing body of evidence supporting drug repurposing as a viable strategy for rapidly developing COVID-19 treatments.

In structural bioinformatics, the efficiency of predicting protein similarity, function, and evolutionary relationships is crucial. Our approach proposed herein leverages protein energy profiles derived from a knowledge-based potential, deviating from traditional methods relying on structural alignment or atomic distances. This method assigns unique energy profiles to individual proteins, facilitating rapid comparative analysis for both structural similarities and evolutionary relationships across various hierarchical levels. Our study demonstrates that energy profiles contain substantial information about protein structure at class, fold, superfamily, and family levels. Notably, these profiles accurately distinguish proteins across species, illustrated by the classification of coronavirus spike glycoproteins and bacteriocin proteins. Introducing a separation measure based on energy profile similarity, our method shows significant correlation with a network-based approach, emphasizing the potential of energy profiles as efficient predictors for drug combinations with faster computational requirements. Our key insight is that the sequence-based energy profile strongly correlates with structure-derived energy, enabling rapid and efficient protein comparisons based solely on sequences.

The kinase-like NiRAN domain of nsp12 in SARS-CoV-2 catalyzes the formation of the 5' RNA cap structure. This activity is required for viral replication, offering a new target for the development of antivirals. Here, we develop a high-throughput assay to screen for small molecule inhibitors targeting the SARS-CoV-2 NiRAN domain. We identified NCI-2, a compound with a reactive chloromethyl group that covalently binds to an active site cysteine (Cys53) in the NiRAN domain, inhibiting its activity. NCI-2 can enter cells, bind to, and inactivate ectopically expressed nsp12. A cryo-EM reconstruction of the SARS-CoV-2 replication-transcription complex (RTC) bound to NCI-2 offers a detailed structural blueprint for rational drug design. Although NCI-2 showed limited potency against SARS-CoV-2 replication in cells, our work lays the groundwork for developing more potent and selective inhibitors targeting the NiRAN domain. This approach presents a promising therapeutic strategy for effectively combating COVID-19 and potentially mitigating future coronavirus outbreaks.

Metformin, an oral hypoglycemic agent, is commonly used in patients with type II diabetes mellitus. Studies have shown its use is associated with a reduction in major cardiovascular events (MACE) in patients with type 2 diabetes such as hospitalization for acute myocardial infarction, stroke, transient ischemic attack, or cardiovascular death. There is also a suggestion that metformin may have effects beyond those relating to lowering of blood sugar. The goal of this review is to assess the effects of metformin in coronary artery disease (CAD), but more importantly, its effects on disease states other than CAD.

Classical proteomics experiments offer high-throughput protein quantification but lack direct evidence of the spatial organization of the proteome, including protein-protein interaction (PPIs) networks. While affinity purification mass spectrometry (AP-MS) is the method of choice for generating these networks, technological impediments have stymied the throughput of AP-MS sample collection and therefore constrained the rate and scale of experiments that can be performed. Here, we build on advances in mass spectrometry hardware that have rendered high-flow liquid chromatography separations a viable solution for faster throughput quantitative proteomics. We describe our methodology using the Orbitrap-Astral mass spectrometer with 7 min, high-flow separations to analyze 216 AP-MS samples in ∼29 h. We show that the ion-focusing advancements, rapid mass analysis, and sensitive ion detection facilitate narrow-bin data-independent acquisition on a chromatographically practical timescale. Further, we highlight several aspects of state-of-the-art confidence-scoring software that warrant reinvestigation given the analytical characteristics of the Orbitrap-Astral mass spectrometer through comparisons with an enrichment-based thresholding technique. With our data, we generated an interaction map between 998 human proteins and 59 viral proteins. These results hold promise in expediting the throughput of AP-MS experiments, enabling more high-powered PPI studies.

Neuroimaging studies have indicated that altered cerebral blood flow (CBF) was associated with the long-term symptoms of postacute sequelae of SARS-CoV-2 infection (PASC), also known as "long COVID". COVID-19 and long COVID were found to be strongly associated with host gene expression. Nevertheless, the relationships between altered CBF, clinical symptoms, and gene expression in the central nervous system (CNS) remain unclear in individuals with long COVID. This study aimed to explore the genetic mechanisms of CBF abnormalities in individuals with long COVID by transcriptomic-neuroimaging spatial association. Lower CBF in the left frontal-temporal gyrus was associated with higher fatigue and worse cognition in individuals with long COVID. This CBF pattern was spatially associated with the expression of 2,178 genes, which were enriched in the molecular functions and biological pathways of COVID-19. Our study suggested that lower CBF is associated with persistent clinical symptoms in long COVID individuals, possibly as a consequence of the complex interactions among multiple COVID-19-related genes, which contributes to our understanding of the impact of adverse CNS outcomes and the trajectory of development to long COVID.

COVID-19 continues to show long-term impacts on our health. Limited effective immune-mediated antiviral drugs have been launched.

We conducted a Mendelian randomization (MR) and colocalization analysis using 26,597 single-cell expression quantitative trait loci (sc-eQTL) to proxy effects of expressions of 16,597 genes in 14 peripheral blood immune cells and tested them against four COVID-19 outcomes from COVID-19 Genetic Housing Initiative GWAS meta-analysis Round 7. We also carried out additional validations including colocalization, linkage disequilibrium check and host-pathogen interactome predictions. We integrated MR findings with clinical trial evidence from several drug gene related databases to identify drugs with repurposing potential. Finally, we developed a tier system and identified immune-cell-based prioritized drug targets for COVID-19.

We identified 132 putative causal genes in 14 immune cells (343 MR associations) for COVID-19, with 58 genes that were not reported previously. 145 (73%) gene-COVID-19 pairs showed effects on COVID-19 in only one immune cell type, which implied widespread immune-cell specific effects. For pathway analyses, we found the putative causal genes were enriched in natural killer (NK) recruiting cells but de-enriched in NK cells. Using a deep learning model, we found 107 (81%) of the putative causal genes (41 novel genes) were predicted to interact with SARS-COV-2 proteins. Integrating the above evidence with drug trial information, we developed a tier system and prioritized 37 drug targets for COVID-19.

Our study showcased the central role of immune-mediated regulatory mechanisms for COVID-19 and prioritized drug targets that might inform interventions for viral infectious diseases.

This work was supported by grants from the National Key Research and Development Program of China (2022YFC2505203).

Hydroxychloroquine and Chloroquine (CQ) and Hydroxychloroquine (HCQ) are antimalarial drugs with well-known anti-inflammatory and antiviral effects used to treat various diseases, with few side effects. After COVID-19 emergence, numerous researches from around the world have examined the potential of using CQ or HCQ as potential treatment of COVID-19. However, conflicting outcomes have been found in COVID-19 clinical trials after treatment with CQ or HCQ. This study aims to evaluate research on CQ and HCQ for COVID-19 treatment and prophylaxis control using bibliometric methods.

We analyzed bibliometric data on HCQ and COVID-19 (HCQ-C19) quantitatively and semantically (2020-2023) using the Scopus database VOSviewer, Bibliometrix, and MS Excel.

Analyses of 7471 original and conference articles revealed that the total number of publications has continually increased. The country producing the most articles in this field was the United States, followed by Italy, India, and Spain. The top-productive authors on HCQ-C19 are Mussini, C., and Raoult, D. (Italy) with 23 and 21 articles, respectively. The top-impactful organization is IHU Méditerranée Infection, France. A Bibliometrix's network analysis based on the co-occurrence of keywords revealed the following themes HCQ-C19, including "clinical research/practice," "COVID-19," "thrombosis," "HCQ," "epidemiology," and "infectious disease."

In conclusion, the analysis reveals a growing interest in HCQ-C19 research. Prominent contributions come from the United States, Italy, India, and Spain. Key themes include clinical research/practice, COVID-19, thrombosis, HCQ, epidemiology, and infectious disease. Future recommendations include conducting well-designed clinical trials and fostering collaborative interdisciplinary efforts.

Classical swine fever (CSF) is a highly contagious disease caused by classical swine fever virus (CSFV). NS5A, a non-structural protein of CSFV, plays an important role in regulating viral replication and protein translation. The purpose of this study was to investigate the effects of the CSFV NS5A protein on key proteins in the mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase (PI3K)-mechanistic target of rapamycin (mTOR) pathways in porcine macrophages. In this study, an NS5A lentivirus was constructed, and 3D4/21 cells were infected. The cells infected for 48 h were collected for proteomic analysis to screen the differential proteins in the two signaling pathways in the NS5A/control group, and the expression levels of key proteins were verified by Western blotting (Wb). CSFV NS5A lentivirus was successfully constructed and used to infect porcine macrophages, and 23 upregulated proteins and 16 downregulated proteins were found in the MAPK signaling pathway, whereas 5 upregulated and 15 downregulated proteins were found in the PI3K-mTOR signaling pathway. The results revealed that with increasing infection time, the expression of IKBKG, AKT1, CDC37, MAP3K2, and PKN2 decreased, whereas the expression of MAP3K7 and KRAS2 increased. The 3D4/21 cells infected with NS5A lentivirus and classical swine fever virus were inoculated, and the differential protein expression was verified via Wb. With increasing time, the protein expression levels of IKBKG and KRAS2 increased, whereas the protein expression levels of MAP3K7, MAP3K2, AKT1, CDC37, and PKN2 decreased. This study provides data for revealing the mechanism by which CSFV evades host antiviral immune clearance and has important scientific significance and potential application value.

Betacoronaviruses express a small internal (I) protein that is encoded by the same subgenomic RNA (sgRNA) as the nucleocapsid (N) protein. Translation of the +1 reading frame of the N sgRNA through leaky ribosomal scanning leads to expression of the I protein. The I protein is an accessory protein reported to evade host innate immune responses during coronavirus infection. Previous studies have shown that the I proteins of severe acute respiratory syndrome coronavirus (SARS-CoV), SARS-CoV-2, and Middle East respiratory syndrome coronavirus suppress type I interferon production by distinct mechanisms. In this review, we summarize the current knowledge on the I proteins of betacoronaviruses from different subgenera, with emphasis on its function and role in pathogenesis.

The COVID-19 pandemic highlights the need for novel antiviral drug discovery approaches that could dramatically shorten timelines from compound discovery to clinical development. At the beginning of the pandemic, repurposing approaches were at the forefront of early research efforts to screen for antiviral activity against SARS-CoV-2 in over 2,500 compounds. Here, we report cellular screening results of 100 FDA-approved and experimental compounds against SARS-CoV-2 in the human Calu-3 cell line. We observed 13 compounds showing antiviral activity against SARS-CoV-2, including seven FDA-approved compounds (remdesivir, boceprevir, amiloride, nafamostat, cisplatin, silmitasertib, and miglustat), and six compounds in pre-clinical and clinical development (tarloxotinib, lucerastat (NB-DGJ), MON-DNJ, NAP-DNJ, NN-DGJ and NN-DNJ). Further, we observed that our screening hits include several host-targeting antivirals, namely iminosugars, that are largely non-toxic and offer a large therapeutic window. The most-developed iminosugar MON-DNJ (UV-4B), which has been evaluated in a Phase 1 clinical trial, showed antiviral activity against SARS-CoV-2 wild type as well as alpha, beta, gamma, delta, and omicron variants. Its activity also extended to another betacoronavirus HCoV OC43, but not alphacoronavirus HCoV 229E. Our cellular screening results add to the body of knowledge on antivirals against coronaviruses and confirm the antiviral efficacy of iminosugars in cellular assays using the human lung-cell line Calu-3.

Defining the subcellular distribution of all human proteins and their remodeling across cellular states remains a central goal in cell biology. Here, we present a high-resolution strategy to map subcellular organization using organelle immunocapture coupled to mass spectrometry. We apply this workflow to a cell-wide collection of membranous and membraneless compartments. A graph-based analysis assigns the subcellular localization of over 7,600 proteins, defines spatial networks, and uncovers interconnections between cellular compartments. Our approach can be deployed to comprehensively profile proteome remodeling during cellular perturbation. By characterizing the cellular landscape following HCoV-OC43 viral infection, we discover that many proteins are regulated by changes in their spatial distribution rather than by changes in abundance. Our results establish that proteome-wide analysis of subcellular remodeling provides key insights for elucidating cellular responses, uncovering an essential role for ferroptosis in OC43 infection. Our dataset can be explored at organelles.czbiohub.org.

Developing sigma-1 receptor (S1R) modulators is considered a valuable therapeutic strategy to counteract neurodegeneration, cancer progression, and viral infections, including COVID-19. In this context, in silico tools capable of accurately predicting S1R affinity are highly desirable. Herein, we present a panel of 25 classifiers trained on a curated dataset of high-quality bioactivity data of small molecules, experimentally tested as potential S1R modulators. All data were extracted from ChEMBL v33, and the models were built using five different fingerprints and machine-learning algorithms. Remarkably, most of the developed classifiers demonstrated good predictive performance. The best-performing model, which achieved an AUC of 0.90, was developed using the support vector machine algorithm with Morgan fingerprints. To provide additional, user-friendly information for medicinal chemists in the rational design of S1R modulators, two independent explainable artificial intelligence (XAI) approaches were employed, namely Shapley Additive exPlanations (SHAP) and Contrastive Explanation. The top-performing model is accessible through a user-friendly web platform, SIGMAP (https://www.ba.ic.cnr.it/softwareic/sigmap/), specifically developed for this purpose. With its intuitive interface, robust predictive power, and implemented XAI approaches, SIGMAP serves as a valuable tool for the rational design of new and more effective S1R modulators.

The inhibition of twenty-five 1,2-fused/disubstituted benzimidazoles on the SARS-CoV-2 Mpro were investigated in this work. It was found that four compounds (1i, 1k, 1l, and 1m) showed obvious inhibitory effect on Mpro. The inhibitory effect of 1k (IC50 46.86 μM) was the best. UV-vis, fluorescence, CD and molecular docking methods were used to reveal the mechanisms of interaction between these compounds and Mpro. Results indicated that static quenching was the main type of quenching. 1i, 1k, 1l, and 1m may alter the conformation and microenvironment of Mpro. The dominant forces between 1i (or 1l) and Mpro were hydrogen bonds or van der Waals forces. The dominant forces between 1k (or 1m) and Mpro were electrostatic or hydrophobic forces, which was consistent with the results of molecular docking. The influence of molecular structure on the binding was investigated. Chlorine atom groups were favorable for the 1,2-fused/disubstituted benzimidazoles derivative inhibitors of Mpro. This work confirmed the changes in the micro-environment of Mpro by 1k, and provided clues for the design of potential Mpro inhibitors.

The Ras GTPase-activating protein SH3-domain-binding protein 1 (G3BP1) serves as a formidable barrier to viral replication by generating stress granules (SGs) in response to viral infections. Interestingly, viruses, including SARS-CoV-2, have evolved defensive mechanisms to hijack SG proteins like G3BP1 for the dissipation of SGs that lead to the evasion of the host's immune responses. Previous research has demonstrated that the interaction between the NTF2-like domain of G3BP1 (G3BP1NTF-2) and the intrinsically disordered N-terminal domain (NTD-N1-25) of the N-protein plays a crucial role in regulating viral replication and pathogenicity. Interestingly, the current study identified an additional upstream stretch of residues (128KDGIIWVATEG138) (N128-138) within the N-terminal domain of the N-protein (NTD-N41-174) that also forms molecular contacts with the G3BP1 protein, as revealed through in silico analysis, site-directed mutagenesis, and biochemical analysis. Remarkably, WIN-62577, and fluspirilene, the small molecules targeting the conserved peptide-binding pocket in G3BP1NTF-2, not only disrupted the protein-protein interactions (PPIs) between NTD-N41-174 and G3BP1NTF-2 but also exhibited significant antiviral efficacy against SARS-CoV-2 replication with EC50 values of ∼1.8 and ∼1.3 μM, respectively. The findings of this study, validated by biophysical thermodynamics and biochemical investigations, advance the potential of developing therapeutics targeting the SG host protein against SARS-CoV-2, which may also serve as a broad-spectrum antiviral target.