Prediction of antiviral drugs against African swine fever viruses based on protein-protein interaction analysis

Discovery of a potent inhibitor, D-132, targeting AsfvPolX, via protein-DNA complex-guided pharmacophore screening and in vitro molecular characterizations

The heightened transmissibility and capacity of African swine fever virus (ASFV) induce fatal diseases in domestic pigs and wild boars, posing significant economic repercussions and global threats. Despite extensive research efforts, the development of potent vaccines or treatments for ASFV remains a persistent challenge. Recently, inhibiting the AsfvPolX, a key DNA repair enzyme, emerges as a feasible strategy to disrupt viral replication and control ASFV infections. In this study, a comprehensive approach involving pharmacophore-based inhibitor screening, coupled with biochemical and biophysical analyses, were implemented to identify, characterize, and validate potential inhibitors targeting AsfvPolX. The constructed pharmacophore model, Phar-PolX-S, demonstrated efficacy in identifying a potent inhibitor, D-132 (IC50 = 2.8 ± 0.2 µM), disrupting the formation of the AsfvPolX-DNA complex. Notably, D-132 exhibited strong binding to AsfvPolX (KD = 6.9 ± 2.2 µM) through a slow-on-fast-off binding mechanism. Employing molecular modeling, it was elucidated that D-132 predominantly binds in-between the palm and finger domains of AsfvPolX, with crucial residues (R42, N48, Q98, E100, F102, and F116) identified as hotspots for structure-based inhibitor optimization. Distinctively characterized by a 1,2,5,6-tetrathiocane with modifications at the 3 and 8 positions involving ethanesulfonates, D-132 holds considerable promise as a lead compound for the development of innovative agents to combat ASFV infections.

In silico simulation of hyperoside, isoquercetin, quercetin, and quercitrin as potential antivirals against the pNP868R protein of African swine fever virus

Background and Aim

African swine fever (ASF) causes disease in pigs with up to 100% mortality rates. There is no effective vaccine to protect against it. This study aimed to perform in silico docking of ASF virus (ASFV) pNP868R protein with potential flavonoid ligands to identify ligands that interfere with mRNA cap formation.

Materials and Methods

The ASFV pNP868R protein was tested with hyperoside, isoquercetin, quercetin, and quercitrin in this in silico simulation. ASFV pNP868R protein was extracted from the Research Collaboration for Structural Bioinformatics Protein Data Bank (RCSB PDB) database with PDB ID 7D8U (https://www.rcsb.org/structure/7D8U). Standard ligands were separated from proteins using UCSF Chimera 1.13. The standard ligand was redocked to protein using AutoDockTools 1.5.6 with the AutoDock4 method for validation. In the docking process, the grid box size was 40 × 40 × 40 Å3 with x, y, and z coordinates of 16.433, -43.826, and -9.496, respectively. The molecular docking process of the proposed ligand-protein complex can proceed if the standard ligand position is not significantly different from its original position in the viral protein's pocket. The root mean square deviation (RMSD), root mean square fluctuation (RMSF), and radius of gyration (RoG) of the hyperoside with the lowest energy binding need to be analyzed with molecular dynamics using Groningen machine for chemical simulation 5.1.1.

Results

Molecular docking and dynamic simulation revealed that hyperoside had the most stable and compact binding to the pNP868R protein. Hyperoside binds to the protein at the minimum energy of -9.07 KJ/mol. The RMSD, RMSF, and RoG values of 0.281 nm, 0.2 nm, and 2.175 nm, respectively, indicate the stability and compactness of this binding.

Conclusion

Hyperoside is the most likely antiviral candidate to bind to the pNP868R protein in silico. Therefore, it is necessary to test whether this flavonoid can inhibit mRNA capping in vitro and elicit the host immune response against uncapped viral mRNA.

Bridging the Gap: Can COVID-19 Research Help Combat African Swine Fever?

African swine fever (ASF) is a highly contagious and economically devastating disease affecting domestic pigs and wild boar, caused by African swine fever virus (ASFV). Despite being harmless to humans, ASF poses significant challenges to the swine industry, due to sudden losses and trade restrictions. The ongoing COVID-19 pandemic has spurred an unparalleled global research effort, yielding remarkable advancements across scientific disciplines. In this review, we explore the potential technological spillover from COVID-19 research into ASF. Specifically, we assess the applicability of the diagnostic tools, vaccine development strategies, and biosecurity measures developed for COVID-19 for combating ASF. Additionally, we discuss the lessons learned from the pandemic in terms of surveillance systems and their implications for managing ASF. By bridging the gap between COVID-19 and ASF research, we highlight the potential for interdisciplinary collaboration and technological spillovers in the battle against ASF.

Target Discovery of Matrine against PRRSV in Marc-145 Cells via Activity-Based Protein Profiling

Porcine reproductive and respiratory syndrome (PRRS) seriously endangers the sustainable development of the pig industry. Our previous studies have shown that matrine can resist porcine reproductive and respiratory syndrome virus (PRRSV) infection. This study aimed to explore the anti-PRRSV targets of matrine in Marc-145 cells. Biotin-labeled matrine 1 and 2 were used as probes. MTT assay was used to determine the maximum non-cytotoxic concentration (MNTC) of each probe in Marc-145 cells. The anti-PRRSV activity of each probe was evaluated via MTT, qPCR and Western blot, and its anti-inflammatory activity was evaluated via qPCR and Western blot. The targets of matrine in Marc-145 cells were searched using activity-based protein profiling (ABPP), and compared with the targets predicted via network pharmacology for screening the potential targets of matrine against PRRSV. The protein-protein interaction networks (PPI) of potential targets were constructed using a network database and GO/KEGG enrichment analysis was performed. ACAT1, ALB, HMOX1, HSPA8, HSP90AB1, PARP1 and STAT1 were identified as potential targets of matrine, and their functions were related to antiviral capacity and immunity. Matrine may play an anti-PRRSV role by directly acting on ACAT1, ALB, HMOX1, HSPA8, HSP90AB1, PARP1 and STAT1.

Polygalic acid inhibits african swine fever virus polymerase activity: findings from machine learning and in vitro testing

African swine fever virus (ASFV), an extremely contagious virus with high mortality rates, causes severe hemorrhagic viral disease in both domestic and wild pigs. Fortunately, ASFV cannot be transmitted from pigs to humans. However, ongoing ASFV outbreaks could have severe economic consequences for global food security. Although ASFV was discovered several years ago, no vaccines or treatments are commercially available yet; therefore, the identification of new anti-ASFV drugs is urgently warranted. Using molecular docking and machine learning, we have previously identified pentagastrin, cangrelor, and fostamatinib as potential antiviral drugs against ASFV. Here, using machine learning combined with docking simulations, we identified natural products with a high affinity for AsfvPolX proteins. We selected five natural products (NPs) that are located close in chemical space to the six known natural flavonoids that possess anti-ASFV activity. Polygalic acid markedly reduced AsfvPolX polymerase activity in a dose-dependent manner. We propose an efficient protocol for identifying NPs as potential antiviral drugs by identifying chemical spaces containing high-affinity binders against ASFV in NP databases.

New perspective on African swine fever: a bibliometrics study and visualization analysis

Introduction

African swine fever (ASF) is a contagious viral disease that can have devastating effects on domestic pigs and wild boars. Over the past decade, there has been a new wave of this ancient disease spreading around the world, prompting many scholars to dedicate themselves to researching this disease. This research aims to use bibliometric methods to organize, analyze and summarize the scientific publications on ASF that have been amassed in the past two decades.

Methods

This paper used VOSviewer, CiteSpace, and a bibliometric online analysis platform to conduct performance analysis and visualization studies on 1,885 academic papers about ASF in the Web of Science from January 2003 to December 2022.

Results

The amount of literature published on ASF has increased exponentially in recent years, and the development trend of related research is good. A group of representative scholars have appeared in this research field, and some cooperative networks have been formed. Transboundary and Emerging Diseases is the journal with the most publications in this field, while Virus Research is the journal with the most citation per article. High-productivity countries are led by China in terms of the number of articles published followed by the United States and Spain. In regard to the average number of citations, the scholars in the UK are in the lead. The institution with the most articles was the Chinese Academy of Agricultural Sciences. The analysis of high-frequency keywords showed that the pathogens and epidemiology of ASF were the research hotspots in this field, and the research content was closely related to molecular biology and immunology. The burst keywords "transmission", "identification", "virulence", "replication", and "gene" reflects the research frontier. In addition, by collating and analyzing highly cited journals and highly co-cited references, we explored the knowledge structure and theoretical basis of this field.

Discussion

This is the first bibliometric analysis report on ASF research, which highlights the key characteristics of ASF research and presents the research status and evolution trend in this field from a new perspective. It provides a valuable reference for further research.

Identification of African Swine Fever Virus Inhibitors through High Performance Virtual Screening Using Machine Learning

African swine fever virus (ASFV) is a highly contagious virus that causes severe hemorrhagic viral disease resulting in high mortality in domestic and wild pigs, until few antiviral agents can inhibit ASFV infections. Thus, new anti-ASFV drugs need to be urgently identified. Recently, we identified pentagastrin as a potential antiviral drug against ASFVs using molecular docking and machine learning models. However, the scoring functions are easily influenced by properties of protein pockets, resulting in a scoring bias. Here, we employed the 5′-P binding pocket of AsfvPolX as a potential binding site to identify antiviral drugs and classified 13 AsfvPolX structures into three classes based on pocket parameters calculated by the SiteMap module. We then applied principal component analysis to eliminate this scoring bias, which was effective in making the SP Glide score more balanced between 13 AsfvPolX structures in the dataset. As a result, we identified cangrelor and fostamatinib as potential antiviral drugs against ASFVs. Furthermore, the classification of the pocket properties of AsfvPolX protein can provide an alternative approach to identify novel antiviral drugs by optimizing the scoring function of the docking programs. Here, we report a machine learning-based novel approach to generate high binding affinity compounds that are individually matched to the available classification of the pocket properties of AsfvPolX protein.

Prediction of African Swine Fever Virus Inhibitors by Molecular Docking-Driven Machine Learning Models

African swine fever virus (ASFV) causes a highly contagious and severe hemorrhagic viral disease with high mortality in domestic pigs of all ages. Although the virus is harmless to humans, the ongoing ASFV epidemic could have severe economic consequences for global food security. Recent studies have found a few antiviral agents that can inhibit ASFV infections. However, currently, there are no vaccines or antiviral drugs. Hence, there is an urgent need to identify new drugs to treat ASFV. Based on the structural information data on the targets of ASFV, we used molecular docking and machine learning models to identify novel antiviral agents. We confirmed that compounds with high affinity present in the region of interest belonged to subsets in the chemical space using principal component analysis and k-means clustering in molecular docking studies of FDA-approved drugs. These methods predicted pentagastrin as a potential antiviral drug against ASFVs. Finally, it was also observed that the compound had an inhibitory effect on AsfvPolX activity. Results from the present study suggest that molecular docking and machine learning models can play an important role in identifying potential antiviral drugs against ASFVs.

Advance of African swine fever virus in recent years

African swine fever (ASF) is one of the most devastating hemorrhagic infectious diseases that affect pigs and wild suids due to the lack of a vaccine or an effective treatment. The large dsDNA genome of African swine fever virus (ASFV) contains up to 167 ORFs that are predicted to encode proteins. Since its introduction to China in 2018, this genome has aroused the enthusiasm of researchers throughout the world. Here, we review the research progress on ASFV in recent years. Given the importance of this disease, this review will highlight recent discoveries in basic virology, focusing mainly on epidemiology, virulence, pathogenic mechanisms, diagnosis, vaccine development, and treatment; this will help in understanding virus-host interactions and disease prevention regarding ASFV.

A New Method for Detection African Swine Fever Virus: Time-resolved Fluorescence Immunoassay

African swine fever (ASF) has severely influenced the swine industry of the whole world. Fast and accurate African swine fever virus (ASFV) antigen detection is very important for ASF prevention. This study aims to establish a new detection method for detection ASFV antigen using time-resolved fluorescence immunoassay (TRFIA) in the nose and mouth discharge. A double antibody sandwich TRFIA method was optimized and established. Recombinant P30 recombinant antigen was captured by its antibodies immobilized on 96-well plate, and then banded together with another detection antibodies labeled with Europium(III) (Eu³⁺) chelates, finally time-resolved analyzer measured the fluorescence intensity. The performance of this TRFIA (sensitivity, specificity and accuracy) was evaluated using the clinical samples and compared with the nucleic acid testing method. The sensitivity of this TRFIA was 0.015 ng/mL (dynamic range 0.24-500 ng/mL) with high specificity. The recovery ranged from 92.00 to 103.62 %, the inter-assay CVs ranged from 5.50 to 11.96 %, and the intra-assay CVs was between 5.20 and 10.53 %. Additionally, the cutoff value was 0.016. TRFIA took only 45 min to generate results, and its detection capability comparable to the nucleic acid detection. This study developed a TRFIA method that could be used for qualitative/quantitative detection of ASFV antigen in pigs nasal discharge, which has high sensitivity, specificity and accuracy. This TRFIA provides a new method for rapidly screening ASFV infection in pigs industry.