Drug discovery against H1N1 virus (influenza A virus) via computational virtual screening approach

Research progress on antiviral constituents in traditional Chinese medicines and their mechanisms of action

CONTEXT

Viruses have the characteristics of rapid transmission and high mortality. At present, western medicines still lack an ideal antiviral. As natural products, many traditional Chinese medicines (TCM) have certain inhibitory effects on viruses, which has become the hotspot of medical research in recent years.

OBJECTIVE

The antiviral active ingredients and mechanisms of TCM against viral diseases was studied in combination with the pathogenesis of viral diseases and antiviral effects.

MATERIALS AND METHODS

English and Chinese literature from 1999 to 2021 was collected from databases including Web of Science, PubMed, Elsevier, Chinese Pharmacopoeia 2020 (CP), and CNKI (Chinese). Traditional Chinese medicines (TCM), active ingredients, antiviral, mechanism of action, and anti-inflammatory effect were used as the key words.

RESULTS

The antiviral activity of TCM is clarified to put forward a strategy for discovering active compounds against viruses, and provide reference for screening antivirus drugs from TCM. TCM can not only directly kill viruses and inhibit the proliferation of viruses in cells, but also prevent viruses from infecting cells and causing cytophilia. It can also regulate the human immune system, enhance human immunity, and play an indirect antiviral role.

DISCUSSION AND CONCLUSION

Based on the experimental study and antiviral mechanism of TCM, this paper can provide analytical evidence that supports the effectiveness of TCM in treating virus infections, as well as their mechanisms against viruses. It could be helpful to provide reference for the research and development of innovative TCMs with multiple components, multiple targets and low toxicity.

Screening and identification of bioactive compounds from citrus against non-structural protein 3 protease of hepatitis C virus genotype 3a by fluorescence resonance energy transfer assay and mass spectrometry

BACKGROUND

Hepatitis C virus genotype 3a (HCV G3a) is highly prevalent in Pakistan. Due to the elevated cost of available Food and Drug Administration-approved drugs against HCV, medicinal natural products of potent antiviral activity should be screened for the cost-effective treatment of the disease. Furthermore, from natural products, active compounds against vital HCV proteins like non-structural protein 3 (NS3) protease could be identified to prevent viral proliferation in the host.

AIM

To develop cost-effective HCV genotype 3a NS3 protease inhibitors from citrus fruit extracts.

METHODS

Full-length NS3 without co-factor non-structural protein 4A (NS4A) and codon optimized NS3 protease in fusion with NS4A were expressed in Escherichia coli. The expressed protein was purified by metal ion affinity chromatography and gel filtration. Citrus fruit extracts were screened using fluorescence resonance energy transfer (FRET) assay against the protease and polyphenols were identified as potential inhibitors using electrospray ionization-mass spectrometry (MS)/MS technique. Among different polyphenols, highly potent compounds were screened using molecular modeling approaches and consequently the most active compound was further evaluated against HCV NS4A-NS3 protease domain using FRET assay.

RESULTS

NS4A fused with NS3 protease domain gene was overexpressed and the purified protein yield was high in comparison to the lower yield of the full-length NS3 protein. Furthermore, in enzyme kinetic studies, NS4A fused with NS3 protease proved to be functionally active compared to full-length NS3. So it was concluded that co-factor NS4A fusion is essential for the purification of functionally active protease. FRET assay was developed and validated by the half maximal inhibitory concentration (IC₅₀) values of commercially available inhibitors. Screening of citrus fruit extracts against the native purified fused NS4A-NS3 protease domain showed that the grapefruit mesocarp extract exhibits the highest percentage inhibition 91% of protease activity. Among the compounds identified by LCMS analysis, hesperidin showed strong binding affinity with the protease catalytic triad having S-score value of -10.98.

CONCLUSION

Fused NS4A-NS3 protease is functionally more active, which is effectively inhibited by hesperidin from the grapefruit mesocarp extract with an IC₅₀ value of 23.32 µmol/L.

Different Inhibitory Potencies of Oseltamivir Carboxylate, Zanamivir, and Several Tannins on Bacterial and Viral Neuraminidases as Assessed in a Cell-Free Fluorescence-Based Enzyme Inhibition Assay

Neuraminidase is a key enzyme in the life cycle of influenza viruses and is present in some bacterial pathogens. We here assess the inhibitory potency of plant tannins versus clinically used inhibitors on both a viral and a bacterial model neuraminidase by applying the 2′-(4-methylumbelliferyl)-α-d-N-acetylneuraminic acid (MUNANA)-based activity assay. A range of flavan-3-ols, ellagitannins and chemically defined proanthocyanidin fractions was evaluated in comparison to oseltamivir carboxylate and zanamivir for their inhibitory activities against viral influenza A (H1N1) and bacterial Vibrio cholerae neuraminidase (VCNA). Compared to the positive controls, all tested polyphenols displayed a weak inhibition of the viral enzyme but similar or even higher potency on the bacterial neuraminidase. Structure–activity relationship analyses revealed the presence of galloyl groups and the hydroxylation pattern of the flavan skeleton to be crucial for inhibitory activity. The combination of zanamivir and EPs^® 7630 (root extract of Pelargonium sidoides) showed synergistic inhibitory effects on the bacterial neuraminidase. Co-crystal structures of VCNA with oseltamivir carboxylate and zanamivir provided insight into bacterial versus viral enzyme-inhibitor interactions. The current data clearly indicate that inhibitor potency strongly depends on the biological origin of the enzyme and that results are not readily transferable. The therapeutic relevance of our findings is briefly discussed.

A virtual screening approach for identifying plants with anti H5N1 neuraminidase activity

Recent outbreaks of highly pathogenic and occasional drug-resistant influenza strains have highlighted the need to develop novel anti-influenza therapeutics. Here, we report computational and experimental efforts to identify influenza neuraminidase inhibitors from among the 3000 natural compounds in the Malaysian-Plants Natural-Product (NADI) database. These 3000 compounds were first docked into the neuraminidase active site. The five plants with the largest number of top predicted ligands were selected for experimental evaluation. Twelve specific compounds isolated from these five plants were shown to inhibit neuraminidase, including two compounds with IC50 values less than 92 μM. Furthermore, four of the 12 isolated compounds had also been identified in the top 100 compounds from the virtual screen. Together, these results suggest an effective new approach for identifying bioactive plant species that will further the identification of new pharmacologically active compounds from diverse natural-product resources.

Molecular basis of R294K mutation effects of H7N9 neuraminidases with drugs and cyclic peptides: an in silico and experimental study

An overview of Shanghai N9/cyclic peptide I complex structure.

Other Related Techniques

With the advances in computational resources, there is an increasing urge among the computational researchers to make the in silico approaches fast, convenient, reproducible, acceptable, and sensible ones. Along with the typical two-dimensional (2D) and three-dimensional (3D) quantitative structure–activity relationship (QSAR) methods, approaches like pharmacophore, structure-based docking studies, and combinations of ligand- and structure-based approaches like comparative residue interaction analysis (CoRIA) and comparative binding energy analysis (COMBINE) have gained a significant popularity in the computational drug design process. A pharmacophore can be developed either in a ligand-based method, by superposing a set of active molecules and extracting common chemical features which are vital for their bioactivity; or in a structure-based manner, by probing probable interaction points between the macromolecular target and ligands. The interaction of protein and ligand molecules with each other is one of the interesting studies in modern molecular biology and molecular recognition. This interaction can well be explained with the conceptof a docking study to show how a molecule can bind to another molecule to exert the bioactivity. Docking and pharmacophore are non-QSAR approaches in in silico drug design that can support the QSAR findings. Approaches like CoRIA and COMBINE can use information generated from the ligand–receptor complexes to extract the critical clue concerning the types of significant interaction at the level of both the receptor and the ligand. Employing the abovementioned ligand- and structure-based methodologies and chemical libraries, virtual screening (VS) emerged as an important tool in the quest to develop novel drug compounds. VS serves as an efficient computational tool that integrates structural data with lead optimization as a cost-effective approach to drug discovery.

Improving the effectiveness of (-)-epigallocatechin gallate (EGCG) against rabbit atherosclerosis by EGCG-loaded nanoparticles prepared from chitosan and polyaspartic acid

(-)-Epigallocatechin gallate (EGCG) is the major bioactive compound in green tea. Its effect is limited by the harsh environment of the gastrointestinal tract. The present study investigates how the effectiveness of EGCG is influenced by its encapsulation into self-assembled nanoparticles of chitosan (CS) and aspartic acid (PAA). Blank nanoparticles with a mean diameter of ca. 93 nm were prepared from 30-50 kDa PAA and 3-5 kDa CS with a mass rate of 1:1. EGCG was loaded in the nanoparticles to yield EGCG-CS-PAA nanoparticles with an average diameter of 102 nm, which were pH-responsive and demonstrated different EGCG release profiles in simulated gastrointestinal tract media. The average ratio (%) of lipid deposition for EGCG-CS-PAA nanoparticles administered orally to rabbits was 16.9 ± 5.8%, which was close to that of oral simvastatin (15.6 ± 4.1%). Orally administered EGCG alone yielded an average ratio of lipid deposit area of 42.1 ± 4.0%, whereas this value was 65.3 ± 10.8% for the blank nanoparticles. The effectiveness of EGCG against rabbit atherosclerosis was significantly improved by incorporating EGCG into the nanoformulation.

Insights from QM/MM Modeling the 3D Structure of the 2009 H1N1 Influenza A Virus Neuraminidase and Its Binding Interactions with Antiviral Drugs

Control of drug release through the inhibition of neuraminidase-1 has been identified as a potential target for the treatment of H1N1 influenza; however, the drug binding mode of neuraminidase is not yet completely understood. In this work, we propose a model for a neuraminidase-1 complex based on four known X-ray structures of drug/neuraminidase-1 complexes. Specifically, H1N1 neuraminidase-1 complexed with 4 drugs (zanamivir, laninamivir, laninamivir octanoate and oseltamivir) was first investigated using a combined quantum mechanical and molecular mechanical (QM/MM) approach. Based on these structures, a model for the H1N1 neuraminidase-1 complex was proposed and simulated using the same computational protocol. Implications to drug/H1N1 neuraminidase-1 binding modes are discussed. From our simulations, the predicted binding free energies of the four drugs are in good agreement with the experimental results, with the correlation coefficient being 0.84.