Search Results (430)

The recent discovery of Orthonairovirus songlingense (SGLV) and Norwavirus beijiense (BJNV) in China has raised significant concern due to their potential to cause severe human disease. However, little is known about the structural features and function of their nucleoproteins, which play a key role in the viral life cycle. By combining small-angle X-ray scattering (SAXS) data and AlphaFold 3 simulations, we reconstructed the BJNV and SGLV nucleoprotein structures for the first time. The SGLV and BJNV nucleoproteins have structures that are broadly similar to those of Orthonairovirus haemorrhagiae (CCHFV) nucleoproteins despite low sequence similarity. Based on structural analysis, several residues located in the positively charged region of BJNV and SGLV nucleoproteins have been indicated to be important for viral RNA binding. A positively charged RNA-binding crevice runs along the interior of the SGLV and BJNV ribonucleoprotein complex (RNP), shielding the viral RNA. Despite the high structural similarity between SGLV and BJNV nucleoprotein monomers, their RNPs adopt distinct conformations. These findings provide important insights into the molecular mechanisms of viral genome packaging and replication in these emerging pathogens. Also, our work demonstrates that experimental SAXS data can validate and improve predicted AlphaFold 3 structures to reflect their solution structure and also provides the first low-resolution structures of the BJNV and SGLV nucleoproteins for the future development of POC tests, vaccines, and antiviral drugs. Full article

Since the onset of the COVID-19 pandemic, remarkable progress has been made in the development of antiviral therapies for SARS-CoV-2. Several direct-acting antivirals, such as remdesivir, molnupiravir, and nirmatrelvir/ritonavir, offer clinical benefits. These agents have significantly contributed to reducing the viral loads and duration of the illness, as well as the disease’s severity and mortality. However, despite these advances, important limitations remain. The continued emergence of resistant SARS-CoV-2 variants highlights the urgent need for adaptable and durable therapeutic strategies. Therefore, this review aims to provide an updated overview of the main antiviral strategies that are used and the discovery of new drugs against SARS-CoV-2, as well as the therapeutic limitations that have shaped clinical management in recent years. The major challenges include resistance associated with viral mutations, limited treatment windows, and unequal access to treatment. Moreover, there is an ongoing need to identify novel compounds with broad-spectrum activity, improved pharmacokinetics, and suitable safety profiles. Combination treatment regimens represent a promising strategy to increase the efficacy of treating COVID-19 while minimizing the potential for resistance. Ideally, these interventions should be safe, affordable, and easy to administer, which would ensure broad global access and equitable treatment and enable control of COVID-19 cases and preparedness for future threats. Full article

Herpes simplex virus type 1 (HSV-1) has a global prevalence of 64%. Established antiviral drugs, such as acyclovir (ACV), have been successfully used over the past decades. However, due to growing viral resistance against approved antivirals and the lack of effective vaccines, new concepts are essential to target HSV-1 infections. Here, we present data on the inhibitory effect of the procaine-based substance ProcCluster^® (PC) in reducing HSV-1 replication in vitro. Non-toxic PC concentrations significantly decreased HSV-1 replication in infected cells. Immunofluorescence microscopy revealed an accumulation of viral proteins in early and recycling endosomes, resulting in reduced viral release. The combination of PC with ACV resulted in an enhanced antiviral effect. Based on these results, PC alone, as well as in combination with ACV, appears to be a promising substance with antiviral potential against HSV-1 infections. Full article

Background/Objectives: Combination therapies using traditional Chinese medicine and Western drugs have gained attention for their enhanced therapeutic effects and reduced side effects. Toujie Quwen Granules (TQG), known for its antiviral properties, particularly against respiratory viruses, could offer new treatment strategies when combined with antiviral drugs like arbidol, especially for diseases such as Coronavirus disease. This study investigates the synergistic mechanisms between arbidol and components from TQG against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (M^pro). Methods: We identified compounds from TQG via existing data. Multi-ligand molecular docking, pharmacokinetic/toxicity screening, and preliminary simulations were performed to assess potential synergistic compounds with arbidol. UPLC-Q-Exactive Orbitrap-MS verified the presence of these compounds. Extended simulations and in vitro assays, including Luciferase and surface plasmon resonance, validated the findings. Results: Five compounds interacted with arbidol in synergy based on docking and preliminary dynamics simulation results. Only Baicalein (HQA004) could be identified in the herbal remedy by untargeted metabolomics, with ideal pharmacokinetic properties, and as a non-toxic compound. Extended simulations revealed that HQA004 enhanced arbidol’s antiviral activity via a “Far” Addition Mechanism #2, with an optimal 2:1 arbidol:HQA004 ratio. The movements of arbidol (diffusion and intramolecular conformational shifts) in the system were significantly reduced by HQA004, which may be the main reason for the synergism that occurred. In vitro experiments confirmed an increased inhibition of M^pro by the combination. Conclusions: HQA004 demonstrated synergistic potential with arbidol in inhibiting M^pro. The development of combination therapies integrating Western and herbal medicine is supported by these findings for effective antiviral treatments. Full article

Coronavirus disease 2019 (COVID-19) produced devastating health and economic impacts worldwide. While progress has been made in vaccine development, effective antiviral treatments remain limited, particularly those targeting the papain-like protease (PLpro) of SARS-CoV-2. PLpro plays a key role in viral replication and immune evasion, making it an attractive yet underexplored target for drug repurposing. In this study, we combined machine learning, molecular dynamics, and molecular docking to identify potential PLpro inhibitors in existing drugs. We performed long-timescale molecular dynamics simulations on PLpro–ligand complexes at two known binding sites, followed by structural clustering to capture representative structures. These were used for molecular docking, including a training set of 127 compounds and a library of 1107 FDA-approved drugs. A random forest model, trained on the docking scores of the representative conformations, yielded 76.4% accuracy via leave-one-out cross-validation. Applying the model to the drug library and filtering results based on prediction confidence and the applicability domain, we identified five drugs as promising candidates for repurposing for COVID-19 treatment. Our findings demonstrate the power of integrating computational modeling with machine learning to accelerate drug repurposing against emerging viral targets. Full article

Marine peptides, derived from a great number of aquatic organisms, exhibit a broad spectrum of biological activities that hold a significant therapeutic potential. This article reviews the multifaceted roles of marine peptides, focusing on their antibacterial, antibiofilm, antifungal, antiviral, antiparasitic, cytotoxic, anticancer, immunomodulatory, chemotactic, opsonizing, anti-inflammatory, antiaging, skin-protective, and wound-healing properties. By elucidating mechanisms of their action and highlighting key research findings, this review aims to provide a comprehensive understanding of possible therapeutic applications of marine peptides, underscoring their importance in developing novel drugs as well as in cosmetology, food industry, aquatic and agriculture biotechnology. Further investigations are essential to harness their therapeutic potential and should focus on detailed mechanism studies, large-scale production, and clinical evaluations with a view to confirm their efficacy and safety and translate these findings into practical applications. It is also important to investigate the potential synergistic effects of marine peptide combinations with existing medicines to enhance their efficacy. Challenges include the sustainable sourcing of marine peptides, and therefore an environmental impact of harvesting marine organisms must be considered as well. Full article

This study focuses on exploring potential inhibitors of the Marburg virus interferon inhibitory domain protein (MARV-VP35), which is responsible for immune evasion and immunosuppression during viral manifestation. A combination of in silico techniques was applied, including structure-based pharmacophore virtual screening, molecular docking, absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis, molecular dynamics (MD), and molecular stability assessment of the identified hits. The docking scores of the 14 selected ligands ranged between −6.88 kcal/mol and −5.28 kcal/mol, the latter being comparable to the control ligand. ADMET and drug likeness evaluation identified Mol_01 and Mol_09 as the most promising candidates, both demonstrating good predicted antiviral activity against viral targets. Density functional theory (DFT) calculations, along with relevant quantum chemical descriptors, correlated well with the docking score hierarchy, and molecular electrostatic potential (MEP) mapping confirmed favorable electronic distributions supporting the docking orientation. Molecular dynamics simulations further validated complex stability, with consistent root mean square deviation (RMSD), root mean square fluctuation (RMSF), and secondary structure element (SSE) profiles. These findings support Mol_01 and Mol_09 as viable candidates for experimental validation. Full article

Influenza is still a chronic global health threat, inducing a sustained search for effective antiviral therapeutics. Computational methods have played a pivotal role in developing small molecule therapeutics. In this study, we applied a combined in silico and in vitro approach to explore the potential anti-influenza activity of cyproheptadine, a clinically used histamine H1 receptor antagonist. Virtual screening based on the average quasivalence number (AQVN) and electron–ion interaction potential (EIIP) descriptors suggests similarities between cyproheptadine and several established anti-influenza agents. The subsequent ligand-based pharmacophore screening of a focused H1 antagonist library was aligned with the bioinformatics prediction, and further experimental in vitro evaluation of cyproheptadine demonstrated its anti-influenza activity. These findings provide proof of concept for cyproheptadine’s in silico-predicted antiviral potential and underscore the value of integrating computational predictions with experimental validation. The results of the current study provide a preliminary proof of concept for the predicted anti-influenza potential based on computational analysis and emphasize the utility of integrating in silico screening with experimental validation in the early stages of drug repurposing efforts. Full article

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of COVID-19. The development of antiviral drugs for COVID-19 has been hampered by the requirement of a biosafety level 3 (BSL3) laboratory for experiments related to SARS-CoV-2, and by the lack of easy and precise methods for quantification of infection. Here, we developed a SARS-CoV-2 viral vector composed of all four SARS-CoV-2 structural proteins constitutively expressed in lentivirally transduced cells, combined with an RNA replicon deleted for SARS-CoV-2 structural protein genes S, M, and E, and expressing a luciferase–GFP fusion protein. We show that, after concentrating viral stocks by ultracentrifugation, the SARS-CoV-2 viral vector is able to infect two human cell lines expressing receptors ACE2 and TMPRSS2. Both luciferase activity and GFP fluorescence were detected, and transduction was remdesivir-sensitive. We also show that this vector is inhibited by three type I interferon (IFN-I) subtypes. Although improvements are needed to increase infectious titers, this vector system may prove useful for antiviral drug screening and SARS-CoV-2-related investigations. Full article

Norovirus, a major cause of acute gastroenteritis, possesses a single-stranded positive-sense RNA genome. The viral 3C-like cysteine protease (3CL^pro) plays a critical role in processing the viral polyprotein into mature non-structural proteins, a step essential for viral replication. Targeting 3CL^pro has emerged as a promising strategy for developing small-molecule inhibitors against Norovirus. In this study, we employed a combination of virtual screening and the FlipGFP assay to identify potential inhibitors targeting the 3CL^pro of Norovirus genotype GII.4. A library of approximately 58,800 compounds was screened using AutoDock Vina tool, yielding 20 candidate compounds based on their Max Affinity scores. These compounds were subsequently evaluated using a cell-based FlipGFP assay. Among them, eight compounds demonstrated significant inhibitory activity against 3CL^pro, with Gedatolisib showing the most potent effect (IC₅₀ = 0.06 ± 0.01 μM). Molecular docking and molecular dynamics simulations were conducted to explore the binding mechanisms and structural stability of the inhibitor–3CL^pro complexes. Our findings provide valuable insights into the development of antiviral drugs targeting Norovirus 3CL^pro, offering potential therapeutic strategies to combat Norovirus infections. Full article

Background/Objectives: While various nucleoside and nucleotide analogs have been approved as anticancer and antiviral drugs, their limitations, including low bioavailability and chemotherapeutic resistance, encourage the development of novel structures. In this context, and motivated by our previous findings on bioactive 3′-O-substituted xylofuranosyl nucleosides and 5-guanidine xylofuranose derivatives, we present herein the synthesis and biological evaluation of 5′-guanidino furanosyl nucleosides comprising 6-chloropurine and uracil moieties and a 3-O-benzyl xylofuranosyl unit. Methods: The synthetic methodology was based on the N-glycosylation of a 5-azido 3-O-benzyl xylofuranosyl acetate donor with the silylated nucleobase and a subsequent one-pot sequential two-step protocol involving Staudinger reduction of the thus-obtained 5-azido uracil and N⁷/N⁹-linked purine nucleosides followed by guanidinylation with N,N′-bis(tert-butoxycarbonyl)-N′′-triflylguanidine. The molecules were evaluated for their anticancer and anti-neurodegenerative diseases potential. Results: 5′-Guanidino 6-chloropurine nucleosides revealed dual anticancer and butyrylcholinesterase (BChE)-inhibitory effects. Both N⁹/N⁷-linked nucleosides exhibited mixed-type and selective submicromolar/micromolar BChE inhibiton. The N⁹ regioisomer was the best inhibitor (K_i/K_i′ = 0.89 μM/2.96 μM), while showing low cytotoxicity to FL83B hepatocytes and no cytotoxicity to human neuroblastoma cells (SH-SY5Y). Moreover, the N⁹-linked nucleoside exhibited selective cytotoxicity to prostate cancer cells (DU-145; IC₅₀ = 27.63 μM), while its N⁷ regioisomer was active against all cancer cells tested [DU-145, IC₅₀ = 24.48 μM; colorectal adenocarcinoma (HCT-15, IC₅₀ = 64.07 μM); and breast adenocarcinoma (MCF-7, IC₅₀ = 43.67 μM)]. In turn, the 5′-guanidino uracil nucleoside displayed selective cytotoxicity to HCT-15 cells (IC₅₀ = 76.02 μM) and also showed neuroprotective potential in a Parkinson’s disease SH-SY5Y cells’ damage model. The active molecules exhibited IC₅₀ values close to or lower than those of standard drugs, and comparable, or not significant, neuro- and hepatotoxicity. Conclusions: These findings demonstrate the interest of combining guanidine moieties with nucleoside frameworks towards the search for new therapeutic agents. Full article

The SARS-CoV-2 main protease (Mpro), essential for viral replication, remains a prime target for antiviral drug design against COVID-19 and related coronaviruses. In this study, we present a systematic investigation into the molecular determinants of Mpro inhibition using an integrated approach combining large-scale data mining, cheminformatics, and quantum chemical calculations. A curated dataset comprising 963 high-resolution structures of Mpro–ligand complexes—348 covalent and 615 non-covalent inhibitors—was mined from the Protein Data Bank. Cheminformatics analysis revealed distinct physicochemical profiles for each inhibitor class: covalent inhibitors tend to exhibit higher hydrogen bonding capacity and sp³ character, while non-covalent inhibitors are enriched in aromatic rings and exhibit greater aromaticity and lipophilicity. A novel descriptor, Weighted Hydrogen Bond Count (WHBC), normalized for molecular size, revealed a notable inverse correlation with aromatic ring count, suggesting a compensatory relationship between hydrogen bonding and π-mediated interactions. To elucidate the energetic underpinnings of molecular recognition, 40 representative inhibitors (20 covalent, 20 non-covalent) were selected based on principal component analysis and aromatic ring content. Quantum mechanical calculations at the double-hybrid B2PLYP/def2-QZVP level quantified non-bonded interaction energies, revealing that covalent inhibitors derive binding strength primarily through hydrogen bonding (~63.8%), whereas non-covalent inhibitors depend predominantly on π–π stacking and CH–π interactions (~62.8%). Representative binding pocket analyses further substantiate these findings: the covalent inhibitor F2F-2020198-00X exhibited strong hydrogen bonds with residues such as Glu166 and His163, while the non-covalent inhibitor EDG-MED-10fcb19e-1 engaged in extensive π-mediated interactions with residues like His41, Met49, and Met165. The distinct interaction patterns led to the establishment of pharmacophore models, highlighting key recognition motifs for both covalent and non-covalent inhibitors. Our findings underscore the critical role of aromaticity and non-bonded π interactions in driving binding affinity, complementing or, in some cases, substituting for hydrogen bonding, and offer a robust framework for the rational design of next-generation Mpro inhibitors with improved selectivity and resistance profiles. Full article

Proventricular dilatation disease (PDD) is a neurologic syndrome of birds caused by the infectious agent Psittacine Bornavirus (PaBV). Clinical disease may be based on the T-cell-mediated immune response to PaBV within the central and peripheral nervous system, similar to Borna disease virus, a closely related mammalian virus. Lymphoplasmacytic infiltrations may occur in ganglia, nerve plexuses, peripheral nerves and the central nervous system of the infected bird. Clinical disease may result in multiple neurologic disorders and life-threatening morbidity. Treatment of PDD with antivirals and non-steroidal anti-inflammatories has thus far been non-curative and unsuccessful long-term. Cyclosporine is an immunosuppressant drug that decreases cell-mediated immune responses by inhibiting T-cell proliferation and decreasing cytokine production. In avian species, cyclosporine is a potent immunosuppressant with T-cell-specific action. A pilot study performed in PaBV-infected cockatiels showed increased weight gain and a lack of morbidity or mortality following experimental PaBV infection and cyclosporine treatment at 10 mg/kg orally every 12 h. In this case series of six psittacine birds affected by PDD, cyclosporine at this dose alleviated or reduced clinical signs in multiple birds without severe sequelae. Itraconazole was used concurrently in these cases to prevent secondary fungal infections during immunosuppression but may have had a synergetic effect when used in combination with cyclosporine. Further prospective research is indicated to better evaluate cyclosporine use in birds with PDD. However, these preliminary clinical findings suggest that cyclosporine and itraconazole administration is a treatment option for palliation of PDD in psittacine patients, especially those refractory to other treatments. Full article

Neurodegenerative disorders, such as Alzheimer’s, Parkinson’s, and Huntington’s disease, due to their multifaced and complicated nature, remain uncurable and impose substantial financial and human burdens on society. Therefore, developing new innovative therapeutic strategies is vital. In this context, drug repurposing has emerged as a promising avenue to expedite the development of treatments for these challenging conditions. One particularly compelling target in this regard is the chaperone protein sigma-1 receptor (S1R), which has garnered significant attention for its neuroprotective properties. Interestingly, several medications, including fluvoxamine (an antidepressant), dextromethorphan (a cough suppressant), and amantadine (an antiviral), which were initially developed for unrelated indications, have shown encouraging results in neurodegenerative therapy through S1R activation. These findings suggest that existing drugs in pharmacopeias can play an essential role in alleviating neurodegenerative symptoms by modulating S1R, thereby offering a faster route and cost-effective path to clinical applications compared to the de novo development of entirely new compounds. Furthermore, as a synergistic benefit, combining S1R-targeting drugs with other therapeutic agents may also improve treatment efficacy. In this review, we highlight key repurposed drugs targeting S1R and explore their mechanisms of action, shedding light on their emerging therapeutic potential in the fight against neurodegeneration. Full article

RNA-dependent RNA polymerase (RdRP) represents a critical target for antiviral drug development. We developed a multi-model machine learning framework combining five traditional algorithms (ExtraTreesClassifier, RandomForestClassifier, LGBMClassifier, BernoulliNB, and BaggingClassifier) with a CNN deep learning model to identify potential RdRP inhibitors among FDA-approved drugs. Using the PubChem dataset AID 588519, our ensemble models achieved the highest performance with accuracy, ROC-AUC, and F1 scores higher than 0.70, while the CNN model demonstrated complementary predictive value with a specificity of 0.77 on external validation. Molecular docking studies with the norovirus RdRP (PDB: 4NRT) identified raloxifene as a promising candidate, with a binding affinity (−8.8 kcal/mol) comparable to the positive control (−9.2 kcal/mol). The molecular dynamics simulation confirmed stable binding with RMSD values of 0.12–0.15 nm for the protein–ligand complex and consistent hydrogen bonding patterns. Our findings suggest that raloxifene may possess RdRP inhibitory activity, providing a foundation for its experimental validation as a potential broad-spectrum antiviral agent. Full article