Comparative binding analysis of WGX50 and Alpha-M with APP family proteins APLP1 and APLP2 using structural-dynamics and free energy calculation approaches.

A.D. is a common disease among other neurodegenerative disorders primarily developing due to amyloid-ß (Aß) neurotoxicity derived from the amyloid-ß protein precursor (AßPP). The amyloid precursor-like proteins 1 and 2 (APP1 and APLP2) biochemically behave similarly in many aspects to AßPP. We, therefore, proposed to test WGX-50 and Alpha-M for their interaction mechanism with APLP1 and APLP2 because both these drug candidate compounds previously showed inhibition of Aß aggregation. We employed a comparative atomic investigation on Alpha-M and WGX-50 in complex with novel targets, i.e., APLP1 and APLP2, using biophysical and molecular simulation methods. The docking score was -6.83 kcal mol-1 for Alpha-M-APLP1, -8.41 kcal mol-1 for WGX-50-APLP1, -7.02 kcal mol-1 for Alpha-M-APLP2 and -8.25 kcal mol-1 for the WGX-50-APLP2 complex. Our results also elaborate that in the case of their interaction with both APLP1 and APLP2, the WGX-50 complex exhibits better stability than the APLP1/2-Alpha-M complexes during simulation. Furthermore, WGX50 in both APLP1 and APLP2 stabilized the internal flexibility upon binding in contrast to the Alpha-M complexes. The data showed that the BFE for Alpha-M-APLP1 was calculated to be -27.38 ± 0.93 kcal mol-1, for WGX-50-APLP1 -39.65 ± 0.95 kcal mol-1, for Alpha-M-APLP2 -24.80 ± 0.63 kcal mol-1 while for WGX-50-APLP2 the BFE was -57.16 ± 1.03 kcal mol-1 respectively. These results highlight that APLP2-WGX50 has greater binding energies in all four systems. PCA and FEL analysis further revealed variations in the dynamic behavior of these complexes. Overall, our findings demonstrate that WGX50 potentially acts as a more potent inhibitor for APLP1 and APLP2 than Alpha-M and thus shows the diverse pharmacological potential of WGX50. Due to its stable binding interaction, WGX50 might be a suitable candidate drug compound for targeting these precursors under pathological conditions.

16S rRNA gene sequencing and machine learning reveal correlation between drug abuse and human host gut microbiota.

Over the past few years, there has been increasing evidence highlighting the strong connection between gut microbiota and overall well-being of the host. This has led to a renewed emphasis on studying and addressing substance use disorder from the perspective of brain-gut axis. Previous studies have suggested that alcohol, food, and cigarette addictions are strongly linked to gut microbiota and faecal microbiota transplantation or the use of probiotics achieved significant efficacy. Unfortunately, little is known about the relationship between drug abuse and gut microbiota. This paper aims to reveal the potential correlation between gut microbiota and drug abuse and to develop an accurate identification model for drug-related faeces samples by machine learning. Faecal samples were collected from 476 participants from three regions in China (Shanghai, Yunnan, and Shandong). Their gut microbiota information was obtained using 16S rRNA gene sequencing, and a substance use disorder identification model was developed by machine learning. Analysis revealed a lower diversity and a more homogeneous gut microbiota community structure among participants with substance use disorder. Bacteroides, Prevotella_9, Faecalibacterium, and Blautia were identified as important biomarkers associated with substance use disorder. The function prediction analysis revealed that the citrate and reductive citrate cycles were significantly upregulated in the substance use disorder group, while the shikimate pathway was downregulated. In addition, the machine learning model could distinguish faecal samples between substance users and nonsubstance users with an AUC = 0.9, indicating its potential use in predicting and screening individuals with substance use disorder within the community in the future.

MiR-210-3p enhances intermittent hypoxia-induced tumor progression via inhibition of E2F3.

PURPOSE: Intermittent hypoxia (IH) is a hallmark of obstructive sleep apnea (OSA), which is related to tumorigenesis and progression. Although micro-ribonucleic acid-210-3p (miR-210-3p) is correlated with hypoxia-induced tumor development, its role in the relationship between IH and tumor function remains poorly understood. The present work focused on elucidating the molecular mechanism through which miR-210-3p drives tumor progression under IH. METHODS: MiR-210-3p levels were quantified within tumor samples from patients with lung adenocarcinoma who had or did not have OSA. Correlations between miR-210-3p and polysomnographic variables were analyzed. For in vitro experiments, miR-210-3p was inhibited or overexpressed via transfection under IH conditions. Cell viability, growth, invasion and migration assays were carried out. For in vivo modeling of IH using mouse xenografts, a miR-210-3p antagomir was intratumorally injected, tumor biological behaviors were evaluated, and reverse transcription-quantitative polymerase chain reaction (RT-qPCR), immunohistochemistry and western blot were carried out for detecting miR-210-3p and E2F transcription factor 3 (E2F3) expression. RESULTS: For patients with lung adenocarcinoma and OSA, high miR-210-3p levels showed positive relation to polysomnographic variables, such as oxygen desaturation index, apnea-hypopnea index, and proportion of total sleep time with oxygen saturation in arterial blood < 90%. IH enhanced tumor viability, proliferation, migration, and invasion, downregulated E2F3 expression, and increased miR-210-3-p levels. miR-210-3p overexpression induced similar changes. These changes were reversed by miR-210-3p inhibition in vitro or miR-210-3p antagomir through intratumoral injection in vivo. CONCLUSIONS: IH-induced tumor development is driven through miR-210-3p by E2F3 suppression. MiR-210-3p represents a potential therapeutic target among patients with concomitant cancer and OSA.

Insight into substrate-assisted catalytic mechanism and stereoselectivity of bifunctional nocardicin thioesterase.

The inversion from L- to D-stereochemistry endows peptides improved bioactivity and enhanced resistance to many proteases and peptidases. To strengthen the biostability and bioavailability of peptide drugs, enzymatic epimerization becomes an important way to incorporate D-amino acid into peptide backbones. Recently, a bifunctional thioesterase NocTE, which is responsible for the epimerization and hydrolysis of the C-terminal (p-hydroxyphenyl)glycine residue of ß-lactam antibiotic nocardicin A, exclusively directs to the generation of D-diastereomers. Different from other epimerases, NocTE exhibits unique stereochemical selectivity. Herein, we investigated the catalytic mechanism of NocTE via molecular dynamic (MD) simulations and quantum mechanical/molecular mechanics (QM/MM) calculations. Through structural analyses, two key water molecules around the reaction site were found to serve as proton mediators in epimerization. The structural characteristics inspired us to propose a substrate-assisted mechanism for the epimerization, where multi-step proton transfers were mediated by water molecules and ß-lactam ring, and the free energy barrier was calculated to be 20.3 kcal/mol. After that, the hydrolysis of D-configured substrate was energetically feasible with the energy barrier of 14.3 kcal/mol. As a comparison, the energy barrier for the direct hydrolysis of L-configured substrate was obtained to be 24.0 kcal/mol. Our study provides mechanistic insights into catalytic activities of bifunctional thioesterase NocTE, uncovers more clues to the molecular basis for stereochemical selectivity and paves the way for the directed biosynthesis of novel peptide drugs with various stereostructural characteristics by enzyme rational design.

An ultrahigh-throughput screening platform based on flow cytometric droplet sorting for mining novel enzymes from metagenomic libraries.

Uncultivable microbial communities provide enormous reservoirs of enzymes, but their experimental identification by functional metagenomics is challenging, mainly due to the difficulty of screening enormous metagenomic libraries. Here, we propose a reliable and convenient ultrahigh-throughput screening platform based on flow cytometric droplet sorting (FCDS). The FCDS platform employs water-in-oil-in-water double emulsion droplets serving as single-cell enzymatic micro-reactors and a commercially available flow cytometer, and it can efficiently isolate novel biocatalysts from metagenomic libraries by processing single cells as many as 108 per day. We demonstrated the power of this platform by screening a metagenomic library constructed from domestic running water samples. The FCDS assay screened 30 million micro-reactors in only 1 h, yielding a collection of esterase genes. Among these positive hits, Est WY was identified as a novel esterase with high catalytic efficiency and distinct evolutionary origin from other lipolytic enzymes. Our study manifests that the FCDS platform is a robust tool for functional metagenomics, with the potential to significantly improve the efficiency of exploring novel enzymes from nature.

Genomic characterization of an emerging Enterobacteriaceae species: the first case of co-infection with a typical pathogen in a human patient.

BACKGROUND: Opportunistic pathogens are important for clinical practice as they often cause antibiotic-resistant infections. However, little is documented for many emerging opportunistic pathogens and their biological characteristics. Here, we isolated a strain of extended-spectrum ß-lactamase-producing Enterobacteriaceae from a patient with a biliary tract infection. We explored the biological and genomic characteristics of this strain to provide new evidence and detailed information for opportunistic pathogens about the co-infection they may cause. RESULTS: The isolate grew very slowly but conferred strong protection for the co-infected cephalosporin-sensitive Klebsiella pneumoniae. As the initial laboratory testing failed to identify the taxonomy of the strain, great perplexity was caused in the etiological diagnosis and anti-infection treatment for the patient. Rigorous sequencing efforts achieved the complete genome sequence of the isolate which we designated as AF18. AF18 is phylogenetically close to a few strains isolated from soil, clinical sewage, and patients, forming a novel species together, while the taxonomic nomenclature of which is still under discussion. And this is the first report of human infection of this novel species. Like its relatives, AF18 harbors many genes related to cell mobility, various genes adaptive to both the natural environment and animal host, over 30 mobile genetic elements, and a plasmid bearing blaCTX-M-3 gene, indicating its ability to disseminate antimicrobial-resistant genes from the natural environment to patients. Transcriptome sequencing identified two sRNAs that critically regulate the growth rate of AF18, which could serve as targets for novel antimicrobial strategies. CONCLUSIONS: Our findings imply that AF18 and its species are not only infection-relevant but also potential disseminators of antibiotic resistance genes, which highlights the need for continuous monitoring for this novel species and efforts to develop treatment strategies.

Improved thermostability of creatinase from Alcaligenes Faecalis through non-biased phylogenetic consensus-guided mutagenesis.

BACKGROUND: Enzymatic quantification of creatinine has become an essential method for clinical evaluation of renal function. Although creatinase (CR) is frequently used for this purpose, its poor thermostability severely limits industrial applications. Herein, we report a novel creatinase from Alcaligenes faecalis (afCR) with higher catalytic activity and lower KM value, than currently used creatinases. Furthermore, we developed a non-biased phylogenetic consensus method to improve the thermostability of afCR. RESULTS: We applied a non-biased phylogenetic consensus method to identify 59 candidate consensus residues from 24 creatinase family homologs for screening afCR mutants with improved thermostability. Twenty-one amino acids of afCR were selected to mutagenesis and 11 of them exhibited improved thermostability compared to the parent enzyme (afCR-M0). Combination of single-site mutations in sequential screens resulted in a quadruple mutant D17V/T199S/L6P/T251C (M4-2) which showed ~ 1700-fold enhanced half-life at 57 °C and a 4.2 °C higher T5015 than that of afCR-M0. The mutant retained catalytic activity equivalent to afCR-M0, and thus showed strong promise for application in creatinine detection. Structural homology modeling revealed a wide range of potential molecular interactions associated with individual mutations that contributed to improving afCR thermostability. CONCLUSIONS: Results of this study clearly demonstrated that the non-biased-phylogenetic consensus design for improvement of thermostability in afCR is effective and promising in improving the thermostability of more enzymes.

SERS-based lateral flow assay combined with machine learning for highly sensitive quantitative analysis of Escherichia coli O157:H7.

In the present study, surface-enhanced Raman scattering-based lateral flow assay (SERS-LFA) strips were applied to promptly and sensitively detect Escherichia coli O157:H7 (E. coli O157:H7) to ensure food safety. The SERS nanotags were prepared by connecting peculiar monoclonal antibody (McAb) against E. coli O157:H7 directly onto the surfaces of gold-silver core-shell nanostructures loaded with two-layer Raman reporter molecules of 5,5'-dithiobis-(2-nitrobenzoic acid) (DTNB). The Raman signal intensity at 1335 cm-1 on the test line (T line) of SERS-LFA strips was detected in the wide range of 101-109 colony-forming units/mL (CFU/mL), and regression models based on machine learning were combined to accurately and quantitatively analyze E. coli O157:H7. The limit of detection (LOD) of the extreme gradient boosting regression (XGBR) based on the Raman signal intensity of DTNB was 6.94 × 101 CFU/mL for E. coli O157:H7, which was approximately four orders of magnitude lower than that of visual limits. In addition, although E. coli O157:H7 was spiked into the food matrices including milk and beef at an ultra-low dose of 10 CFU/mL, the SERS-LFA combined with XGBR was able to successfully explore E. coli O157:H7 from the mixture that was incubated for only 2 h, in which the recoveries were mainly distributed between 86.41 and 128.25%. In summary, these results demonstrated that the SERS-LFA had a significant potential as a powerful tool for the point-of-care testing (POCT) of E. coli O157:H7 in the early food contamination stage.

Investigation of lipid metabolism dysregulation and the effects on immune microenvironments in pan-cancer using multiple omics data.

BACKGROUND: Lipid metabolism reprogramming is a hallmark for tumor which contributes to tumorigenesis and progression, but the commonality and difference of lipid metabolism among pan-cancer is not fully investigated. Increasing evidences suggest that the alterations in tumor metabolism, including metabolite abundance and accumulation of metabolic products, lead to local immunosuppression in the tumor microenvironment. An integrated analysis of lipid metabolism in cancers from different tissues using multiple omics data may provide novel insight into the understanding of tumorigenesis and progression. RESULTS: Through systematic analysis of the multiple omics data from TCGA, we found that the most-widely altered lipid metabolism pathways in pan-cancer are fatty acid metabolism, arachidonic acid metabolism, cholesterol metabolism and PPAR signaling. Gene expression profiles of fatty acid metabolism show commonalities across pan-cancer, while the alteration in cholesterol metabolism and arachidonic acid metabolism differ with tissue origin, suggesting tissue specific lipid metabolism features in different tumor types. An integrated analysis of gene expression, DNA methylation and mutations revealed factors that regulate gene expression, including the differentially methylated sites and mutations of the lipid genes, as well as mutation and differential expression of the up-stream transcription factors for the lipid metabolism pathways. Correlation analysis of the proportion of immune cells in the tumor microenvironment and the expression of lipid metabolism genes revealed immune-related differentially expressed lipid metabolic genes, indicating the potential crosstalk between lipid metabolism and immune response. Genes related to lipid metabolism and immune response that are associated with poor prognosis were discovered including HMGCS2, GPX2 and CD36, which may provide clues for tumor biomarkers or therapeutic targets. CONCLUSIONS: Our study provides an integrated analysis of lipid metabolism in pan-cancer, highlights the perturbation of key metabolism processes in tumorigenesis and clarificates the regulation mechanism of abnormal lipid metabolism and effects of lipid metabolism on tumor immune microenvironment. This study also provides new clues for biomarkers or therapeutic targets of lipid metabolism in tumors.

Blood circRNAs as biomarkers for the diagnosis of community-acquired pneumonia.

Circular RNAs (circRNAs) have been reported as effective diagnostic and therapeutic biomarkers in many diseases, but the potential of using this easy-to-monitor and highly stable materials for diagnosing Community-acquired pneumonia (CAP) remains unexplored. Here, aiming to identify potential CAP-related circRNAs in peripheral blood and seeking to deepen the understanding of how circRNA-miRNA-mRNA regulatory networks may contribute to CAP, we applied microarrays profiling analysis and identified 8296 differentially expressed (DE) circRNAs between patients with CAP (n = 6) and healthy controls (n = 6). Subsequently, we validated the accumulation trends for the top 100 DE circRNAs based on qPCR in an independent validation cohort (30 patients vs 30 controls), and ultimately identified a panel of four circRNAs that perform extremely well as sensitive and specific biomarkers for diagnosing CAP: hsa_circ_0018429 (area under the curve [AUC] = 0.8216), hsa_circ_0026579 (AUC = 0.7733), hsa_circ_0125357 (AUC = 0.7730), and hsa_circ_0099188 (AUC = 0.6978); combined as a panel (AUC = 0.8776). In addition, hsa_circ_0026579 exhibited good performance in differentiating viral from bacterial or mixed infection, with an AUC of 0.863. We also identified 10 miRNAs that most likely to interact with these four circRNAs, and then predicted 205 mRNA target genes. The KEGG pathway enrichment analysis suggested highly plausible functional implications related to inflammation and to virus-infection-related signaling pathways (such as HTLV-1 infection and hepatitis B infection). Thus, we generated a genetic network of potential CAP-related regulatory interactions that should inform future hypothesis-driven research into the causes and potential treatment of this widespread and frequently fatal disease.

Investigating the Mechanism of L-Valine in Improving the Stability of Gabapentin Combining Chemical Analysis Experiments with Computational Pharmacy.

The mechanism of L-Val on how to improve the stability of gabapentin (GBP) was described by the combination of chemical analysis experiments and computer simulations. Scanning electron microscope (SEM), powder X-ray diffraction (PXRD), and differential scanning calorimeter (DSC), coupled with attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), were used to identify ß-GBP prepared by rapid solvent removal method. The reaction barriers on crystal planes, ß-GBP (100) and ß-GBP (10-1), are smaller than α-GBP and γ-GBP, reaching 276.65 kJ/mol and 299.57 kJ/mol, respectively. Thus, it was easier for ß-GBP to form lactam, and the occurrence of ß-GBP would lead the worse stability of α-GBP. The addition of neutral amino acids such as L-Val could improve the stability of α-GBP effectively. The adsorption energy of α-GBP (002) crystal plane with L-Val is larger than that of other crystal planes, reaching 42.17 kJ/mol. Hydrogen bond was the combination of L-Val and GBP main crystal planes, which could inhibit the crystal transformation of α-GBP. These results suggest that neutral amino acid protectants, such as L-Val, could improve the stability of α-GBP effectively, and inhibition of crystal transformation is one of the effective methods to improve the stability of polymorphic drugs.

Integration of mass spectrometry and RNA-Seq data to confirm human ab initio predicted genes and lncRNAs.

MS/MS has been used to improve genome annotation in various organisms. The classical approach is to construct comprehensive theoretical peptide database with six frame translation model from the whole ORF of a genome and search against this database with real MS/MS spectra. In this work we took a more focused approach, we constructed a database containing only peptides from the ab initio predicted genes from current human genome annotation, and all theoretical peptides from currently annotated lncRNAs, and searched such a database with MS/MS data from human Hela cell line. The purpose of this design is to find translation evidence for ab initio predicted genes and to rule out possible wrongly defined lncRNAs in a systematic proteogenomics effort. To validate proteogenomics results, we integrated RNA-Seq data analysis for the same Hela cell line which generated MS/MS data, and performed MRM experiment on self-cultured Hela cell line samples. Six peptides were found to support ab initio predicted genes with both RNA-Seq and MRM validations, while none was found to support a translated lncRNA. This workflow could be flexibly applied to other human samples and datasets to help further improve human gene annotation.

[Investigation on bioactive protective function of amino acids to insulin by molecular simulation].

Heat sensitive protein medicines are increasingly exhibiting their critical importance on treatment of various diseases at present. But their popularization and application meet a great challenge because of their heat instability. In the present study, insulin was taken as a heat sensitive protein medicine and amino acid as bio-protective agent in order to investigate if these amino acids can protect the insulin from losing its bioactivity due to desiccation. The experiment was performed by using replica exchange molecular simulation (REMD) method and Gromacs software with Gromos96 (53a6) force field. The REMD results indicated that these amino acids could protect the bioactive structure of insulin during desiccation. The configurations of the protected insulin were preserved very well. Those results proved that amino acid is a kind of good bioactive protective agent for the heat sensitive protein medicines.

[Investigation on bioactive protection of LEA protein for insulin by molecular simulation in the low-temperature drying process].

Nowadays various protein medicines are increasingly playing significant roles in the treatment of many diseases, but the bioactive structures of such kinds of protein medicines are unstable because they are heat sensitive. Therefore, it is very important to explore a protective method and to explain the protective mechanism of protein medicines. In the present research, insulin was chosen as a heat-sensitive protein medicine, and a Group 3 late embryogenesis abundant (LEA) protein was chosen as its bioactive protectant during desiccation. The results of replica exchange molecular dynamics simulation suggest that comparing with insulin without any protection, the bioactive 3D structure and secondary structure of the insulin protected by LEA protein were preserved very well. All analyzing results proved that the LEA protein was a good bioactive protectant for heat sensitive protein medicines.

[Molecular simulation research on aggregation of insulin].

In the present research, molecular simulation and quantum chemistry calculations were combined to investigate the thermal stability of three kinds of insulin aggregations and the effect of Zn (II) ion coordination on these aggregations. The results of molecular simulation indicated that the three insulin dimers in the same sphere closed hexamer had synergistic stability. It is the synergistic stability that enhances the structural and thermal stability of insulin, preserves its bioactivity during production, storage, and delivery of insulin formulations, and prolongs its halflife in human bodies. According to the results of quantum chemistry calculations, each Zn (II)-N (Im-insulin) bond energy can reach 73.610 kJ/mol for insulin hexamer and 79.907 kJ/mol for insulin tetramer. However, the results of Gibbs free energy changes still indicats that the coordination of zinc (II) ions is unfavorable for the formation of insulin hexamer, because the standard Gibbs free energy change of the coordinate reaction of zinc (II) ions associated with the formatting insulin hexamer is positive and increased.

Molecular dynamic simulation reveals spider antimicrobial peptide Latarcin-1 and human eosinophil cationic protein as peptide inhibitors of SARS-CoV-2 variants.

COVID-19 has rapidly proliferated around 180 countries, and new cases are reported frequently. No peptide medication has been developed that can reliably block SARS-CoV-2 infection. The investigation focuses on the crucial host receptors angiotensin-converting enzyme 2 (ACE2) , which can bind receptor-binding domain (RBD) on the SARS-CoV-2 spike protein (S). To investigate the inhibitory effects of human Eosinophil Cationic Protein (hECP) and Latarcin-1 (L1)on SARS-CoV-2 infection, we have selected them as research subjects. Further, we ran extensive molecular dynamics simulations to bring the docked peptide-ACE2 complex into its equilibrium state. The outcomes were then evaluated with g_MMPBSA and interaction analysis. We have also considered the Delta and Omicron variants to examine these peptides' inhibitory effects. The experimental findings revealed an enhanced capability of L1 and hECP as SARS-CoV-2 inhibitors, occupying hot spots and numerous key residues in ACE2. These include ASP30, ASP38, GLU35 and GLU75, which significantly inhibit the binding of RBD and ACE2 and are effective against two common variants in a similar manner. In addition, this study can serve as a springboard for future research on SARS-CoV-2 inhibitors.Communicated by Ramaswamy H. Sarma.

Investigating the stabilisation of IFN-α2a by replica exchange molecular dynamics simulation.

Current biopharmaceutical drugs are mainly a class of peptides or proteins that play an essential role in the treatment of many diseases. Such peptides/proteins are usually thermally unstable and may lose their bioactivity when exposed to ambient conditions. Therefore, they are not suitable for long-term storage. Lyophilisation is the most common method to prolong shelf life of solid peptide/protein drugs; however, the freeze-drying process can lead to irreversible damage. In the present study, human interferon-alpha 2a (IFN-α2a) was selected as a model protein drug; four disaccharides (ß-lactose, ß-maltose, sucrose, and trehalose) were selected as bioactive protectants. We investigated the effects of different protectants on IFN-α2a under various ambient conditions (vacuum, dry state, and aqueous solution) using replica exchange molecular dynamics simulation. The protective effect of ß-maltose on IFN-α2a was the highest in aqueous solution and dry state, ß-lactose showed a poor protective effect in all three conditions, the performance of sucrose was good in all conditions, and trehalose showed a better protective effect under vacuum conditions and in aqueous solution. Disaccharides form H-bonds with water, thereby preventing water from the tertiary structure of proteins. Trehalose forms strong H-bonds with water which explains its extraordinary stability.

[Preparation of luciferase-expressing mRNA and expression characteristics of mRNA delivered by electroporation in vivo].

In this study, we aimed to construct a non-replication mRNA platform and explore the side effects of electroporation-mediated delivery of mRNA on the mice as well as the expression features of the mRNA. With luciferase gene as a marker, in vitro transcription with T7 RNA polymerase was carried out for the synthesis of luciferase-expressed mRNA, followed by enzymatic capping and tailing. The mRNA was delivered in vivo by electroporation via an in vivo gene delivery system, and the expression intensity and duration of luciferase in mice were observed via an in vivo imaging system. The results demonstrated that the mRNA transcripts were successfully expressed both in vitro and in vivo. The electroporation-mediated delivery of mRNA had no obvious side effects on the mice. Luciferase was expressed successfully in all the mRNA-transduced mice, while the expression intensity and duration varied among individuals. Overall, the expression level peaked on the first day after electroporation and rapidly declined on the fourth day. This study is of great importance for the construction of non-replication mRNAs and their application in vaccine or antitumor drug development.

Discovery of a Natural Product with Potent Efficacy Against SARS-CoV-2 by Drug Screening.

The novel coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread worldwide for almost 2 years. It starts from viral adherence to host cells through an interaction between spike glycoprotein 1 (S1) containing a receptor-binding domain (RBD) and human angiotensin-converting enzyme-2 (ACE2). One of the useful strategies to prevent SARS-CoV-2 infection is to inhibit the attachment of RBD to ACE2. Therefore, the current work proposed potent peptides against SARS-CoV-2 infection by carrying out MM-PBSA calculation based on the binding of 52 antiviral peptides (AVPs) to RBD. Considering the binding free energies of AVPs to RBD, cyanovirin-N (CV-N) showed the strongest RBD binding affinity among 52 AVPs. Upon structural analysis of RBD complex with CV-N, it was observed that 12 of the 13 key residues of RBD binding to ACE2 were hijacked by CV-N. CV-N bound to RBD at a smaller affinity of 14.9 nM than that of ACE2 and inhibited the recruitment of S1 to human alveolar epithelial cells. Further analysis revealed that CV-N suppressed SARS-CoV-2 S pseudovirion infection with a half-maximal inhibitory concentration (IC50) of 18.52 µg/mL. This study demonstrated a drug screening for AVPs against SARS-CoV-2 and discovered a peptide with inspiring antiviral properties, which provided a promising strategy for the COVID-19 therapeutic approach.