Identification of probable inhibitors for the DNA polymerase of the Monkeypox virus through the virtual screening approach

Prediction of potential public health risk of the recent multicountry monkeypox outbreak: An update after the end declaration of global public health emergency

Background and Aims

A double-stranded DNA virus called monkeypox virus (MPV) belonging to the Poxviridae family and Orthopoxvirus genus causes monkeypox (mpox) infection. This virus used to infect only Central, East, and West Africa. However, it has spread to an extent outside Africa recently. The range of MPV outbreaks was so high that on July 23, 2022, the World Health Organization (WHO) declared it a Public Health Emergency of International Concern (PHEIC). About a year later, the WHO notified the end of a global public health emergency for mpox on May 11, 2023. Here, we aimed to assess the current pathogenicity and potential risk of MPV causing public health emergencies.

Methods

We searched information from published articles available in PubMed, Scopus, and ScienceDirect. We used monkeypox, mpox, monkeypox outbreak, and monkeypox virus as keywords during the literature search.

Results

Many new variants of MPV have emerged throughout the world that created PHEIC for mpox. Considering the low lethality and transmission rate, mpox is no longer a global public health threat. In addition, the availability of therapeutic and preventive measures helped the healthcare authorities fight the mpox infection in an efficient manner. In this review, we have portrayed the history and evolution of mpox from past to present and an idea of its future outcomes. Also, we have discussed the symptoms related to mpox and approved antiviral treatment strategies to fight off the infection in this piece. This review also emphasized the preventive guidelines set by the WHO for patients, caregivers, and healthcare providers to control the outbreak of mpox infection.

Conclusion

We believe this article would give an idea about the potential public health threats of the recent multi-country monkeypox outbreak to the healthcare authorities for taking measures accordingly.

Potential Inhibitors of Lumpy Skin Disease's Viral Protein (DNA Polymerase): A Combination of Bioinformatics Approaches

Lumpy skin disease (LSD), caused by a virus within the Poxviridae family and Capripoxvirus genus, induces nodular skin lesions in cattle. This spreads through direct contact and insect vectors, significantly affecting global cattle farming. Despite the availability of vaccines, their efficacy is limited by poor prophylaxis and adverse effects. Our study aimed to identify the potential inhibitors targeting the LSDV-encoded DNA polymerase protein (gene LSDV039) for further investigation through comprehensive analysis and computational methods. Virtual screening revealed rhein and taxifolin as being potent binders among 380 phytocompounds, with respective affinities of -8.97 and -7.20 kcal/mol. Canagliflozin and tepotinib exhibited strong affinities (-9.86 and -8.86 kcal/mol) among 718 FDA-approved antiviral drugs. Simulating the molecular dynamics of canagliflozin, tepotinib, rhein, and taxifolin highlighted taxifolin's superior stability and binding energy. Rhein displayed compactness in RMSD and RMSF, but fluctuated in Rg and SASA, while canagliflozin demonstrated stability compared to tepotinib. This study highlights the promising potential of using repurposed drugs and phytocompounds as potential LSD therapeutics. However, extensive validation through in vitro and in vivo testing and clinical trials is crucial for their practical application.

Computer-assisted discovery and evaluation of potential ribosomal protein S6 kinase beta 2 inhibitors

S6K2 is an important protein in mTOR signaling pathway and cancer. To identify potential S6K2 inhibitors for mTOR pathway treatment, a virtual screening of 1,575,957 active molecules was performed using PLANET, AutoDock GPU, and AutoDock Vina, with their classification abilities compared. The MM/PB(GB)SA method was used to identify four compounds with the strongest binding energies. These compounds were further investigated using molecular dynamics (MD) simulations to understand the properties of the S6K2/ligand complex. Due to a lack of available 3D structures of S6K2, OmegaFold served as a reliable 3D predictive model with higher evaluation scores in SAVES v6.0 than AlphaFold, AlphaFold2, and RoseTTAFold2. The 150 ns MD simulation revealed that the S6K2 structure in aqueous solvation experienced compression during conformational relaxation and encountered potential energy traps of about 19.6 kJ mol-1. The virtual screening results indicated that Lys75 and Lys99 in S6K2 are key binding sites in the binding cavity. Additionally, MD simulations revealed that the ligands remained attached to the activation cavity of S6K2. Among the compounds, compound 1 induced restrictive dissociation of S6K2 in the presence of a flexible region, compound 8 achieved strong stability through hydrogen bonding with Lys99, compound 9 caused S6K2 tightening, and the binding of compound 16 was heavily influenced by hydrophobic interactions. This study suggests that these four potential inhibitors with different mechanisms of action could provide potential therapeutic options.

Identification of natural xanthine oxidase inhibitors: Virtual screening, anti-xanthine oxidase activity, and interaction mechanism

Xanthine oxidase (XO) is a crucial target for hyperuricemia treatment(s). Naturally occurred XO inhibitors with minimal toxicity and high efficacy have attracted researchers' attention. With the goal of quickly identifying natural XO inhibitors, an integrated computational screening strategy was constructed by molecular docking and calculating the free energy of binding. Twenty-seven hits were achieved from a database containing 19,377 natural molecules. This includes fourteen known XO inhibitors and four firstly-reported inhibitors (isolicoflavonol, 5,7-dihydroxycoumarin, parvifolol D and clauszoline M, IC50 < 40 μM). Iolicoflavonol (hit 8, IC50 = 8.45 ± 0.68 μM) and 5,7-dihydroxycoumarin (hit 25, IC50 = 10.91 ± 0.71 μM) displayed the great potency as mixed-type inhibitors. Docking study and molecular dynamics simulation revealed that both hits could interact with XO's primarily active site residues ARG880, MOS1328, and ASN768 of XO. Fluorescence spectroscopy studies showed that hit 8 bound to the active cavity region of XO, causing changes in XO's conformation and hydrophobicity. Hits 8 and 25 exhibit favorable Absorption, Distribution, Metabolism, and Excretion (ADME) properties. Additionally, no cytotoxicity against human liver cells was observed at their median inhibition concentrations against XO. Therefore, the present study offers isolicoflavonol and 5,7-dihydroxycoumarin with the potential to be disease-modifying agents for hyperuricemia.

Comparative Structure-Based Virtual Screening Utilizing Optimized AlphaFold Model Identifies Selective HDAC11 Inhibitor

HDAC11 is a class IV histone deacylase with no crystal structure reported so far. The catalytic domain of HDAC11 shares low sequence identity with other HDAC isoforms, which makes conventional homology modeling less reliable. AlphaFold is a machine learning approach that can predict the 3D structure of proteins with high accuracy even in absence of similar structures. However, the fact that AlphaFold models are predicted in the absence of small molecules and ions/cofactors complicates their utilization for drug design. Previously, we optimized an HDAC11 AlphaFold model by adding the catalytic zinc ion and minimization in the presence of reported HDAC11 inhibitors. In the current study, we implement a comparative structure-based virtual screening approach utilizing the previously optimized HDAC11 AlphaFold model to identify novel and selective HDAC11 inhibitors. The stepwise virtual screening approach was successful in identifying a hit that was subsequently tested using an in vitro enzymatic assay. The hit compound showed an IC50 value of 3.5 µM for HDAC11 and could selectively inhibit HDAC11 over other HDAC subtypes at 10 µM concentration. In addition, we carried out molecular dynamics simulations to further confirm the binding hypothesis obtained by the docking study. These results reinforce the previously presented AlphaFold optimization approach and confirm the applicability of AlphaFold models in the search for novel inhibitors for drug discovery.

Breaking Barriers: Current Advances and Future Directions in Mpox Therapy

BACKGROUND

Mpox, a newly discovered zoonotic infection, can be transmitted from animal to human and between humans. Serological and genomic studies are used to identify the virus.

OBJECTIVE

Currently, there are no proven effective treatments for Mpox. Also, the safety and efficacy of intravenous vaccinia immune globulin, oral Tecovirimat (an inhibitor of intracellular viral release), and oral Brincidofovir (a DNA polymerase inhibitor) against the Mpox virus are uncertain, highlighting the need for more effective and safe treatments. As a result, drug repurposing has emerged as a promising strategy to identify previously licensed drugs that can be repurposed to treat Mpox.

RESULTS

Various approaches have been employed to identify previously approved drugs that can target specific Mpox virus proteins, including thymidylate kinase, D9 decapping enzyme, E8 protein, Topoisomerase1, p37, envelope proteins (D13, A26, and H3), F13 protein, virus's main cysteine proteases, and DNA polymerase.

CONCLUSION

In this summary, we provide an overview of potential drugs that could be used to treat Mpox and discuss the underlying biological processes of their actions.

AI-assisted structural consensus-proteome prediction of human monkeypox viruses isolated within a year after the 2022 multi-country outbreak

IMPORTANCE

The 2022 outbreak of the monkeypox virus already involves, by April 2023, 110 countries with 86,956 confirmed cases and 119 deaths. Understanding an emerging disease on a molecular level is essential to study infection processes and eventually guide drug discovery at an early stage. To support this, we provide the so far most comprehensive structural proteome of the monkeypox virus, which includes 210 structural models, each computed with three state-of-the-art structure prediction methods. Instead of building on a single-genome sequence, we generated our models from a consensus of 3,713 high-quality genome sequences sampled from patients within 1 year of the outbreak. Therefore, we present an average structural proteome of the currently isolated viruses, including mutational analyses with a special focus on drug-binding sites. Continuing dynamic mutation monitoring within the structural proteome presented here is essential to timely predict possible physiological changes in the evolving virus.

Insights into a class of natural eugenol and its optimized derivatives as potential tobacco mosaic virus helicase inhibitors by structure-based virtual screening

Plant diseases caused by malignant and refractory phytopathogenic viruses have considerably restricted crop yields and quality. To date, drug design targeting functional proteins or enzymes of viruses is an efficient and viable strategy to guide the development of new pesticides. Herein, a series of novel eugenol derivatives targeting the tobacco mosaic virus (TMV) helicase have been designed using structure-based virtual screening (SBVS). Structure-activity relationship indicated that 2 t displayed the most powerful bonding capability (Kd = 0.2 μM) along with brilliant TMV helicase ATPase inhibitory potency (IC50 = 141.9 μM) and applausive anti-TMV capability (EC50 = 315.7 μg/mL), ostentatiously outperforming that of commercial Acyclovir (Kd = 23.0 μM, IC50 = 183.7 μM) and Ribavirin (EC50 = 624.3 μg/mL). Molecular dynamics simulations and docking suggested ligand 2 t was stable and bound in the active pocket of the TMV helicase by multiple interactions. Given these superior properties, eugenol-based derivatives could be considered as the novel potential plant viral helicase inhibitors. Furthermore, this effective and feasible SBVS strategy established a valuable screening platform for helicase-targeted drug development.

Using AlphaFold Predictions in Viral Research

Elucidation of the tertiary structure of proteins is an important task for biological and medical studies. AlphaFold, a modern deep-learning algorithm, enables the prediction of protein structure to a high level of accuracy. It has been applied in numerous studies in various areas of biology and medicine. Viruses are biological entities infecting eukaryotic and procaryotic organisms. They can pose a danger for humans and economically significant animals and plants, but they can also be useful for biological control, suppressing populations of pests and pathogens. AlphaFold can be used for studies of molecular mechanisms of viral infection to facilitate several activities, including drug design. Computational prediction and analysis of the structure of bacteriophage receptor-binding proteins can contribute to more efficient phage therapy. In addition, AlphaFold predictions can be used for the discovery of enzymes of bacteriophage origin that are able to degrade the cell wall of bacterial pathogens. The use of AlphaFold can assist fundamental viral research, including evolutionary studies. The ongoing development and improvement of AlphaFold can ensure that its contribution to the study of viral proteins will be significant in the future.