Characterization and functional evidence for Orf2 of Streptomyces sp. 139 as a novel dipeptidase E.

Aspartyl dipeptidase (dipeptidase E) can hydrolyze Asp-X dipeptides (where X is any amino acid), and the enzyme plays a key role in the degradation of peptides as nutrient sources. Dipeptidase E remains uncharacterized in Streptomyces. Orf2 from Streptomyces sp. 139 is located in the exopolysaccharide biosynthesis gene cluster, which may be a novel dipeptidase E with "S134-H170-D198" catalytic triad by sequence and structure comparison. Herein, recombinant Orf2 was expressed in E. coli and characterized dipeptidase E activity using the Asp-ρNA substrate. The optimal pH and temperature for Orf2 are 7.5 and 40 ℃; Vmax and Km of Orf2 are 0.0787 mM·min-1 and 1.709 mM, respectively. Orf2 exhibits significant degradation activities to Asp-Gly-Gly, Asp-Leu, Asp-His, and isoAsp-Leu and minimal activities to Asp-Pro and Asp-Ala. Orf2 contains a Ser-His-Asp catalytic triad characterized by point mutation. In addition, the Asp147 residue of Orf2 is also proven to be critical for the enzyme's activity through molecular docking and point mutation. Transcriptome analysis reveals the upregulation of genes associated with ribosomes, amino acid biosynthesis, and aminoacyl-tRNA biosynthesis in the orf2 mutant strain. Compared with the orf2 mutant strain and WT, the yield of crude polysaccharide does not change significantly. However, crude polysaccharides from the orf2 mutant strain exhibit a wider range of molecular weight distribution. The results indicate that the Orf2 links nutrient stress to secondary metabolism as a novel dipeptidase E. KEY POINTS: • A novel dipeptidase E with a Ser-His-Asp catalytic triad was characterized from Streptomyces sp. 139. • Orf2 was involved in peptide metabolism both in vitro and in vivo. • Orf2 linked nutrient stress to mycelia formation and secondary metabolism in Streptomyces.

Modulatory effects of rutin and vitamin A on hyperglycemia induced glycation, oxidative stress and inflammation in high-fat-fructose diet animal model.

In the current study we investigated the impact of combination of rutin and vitamin A on glycated products, the glyoxalase system, oxidative markers, and inflammation in animals fed a high-fat high-fructose (HFFD) diet. Thirty rats were randomly divided into six groups (n = 5). The treatments, metformin (120 mg/kg), rutin (100 mg/kg), vitamin A (43 IU/kg), and a combination of rutin (100 mg/kg) and vitamin A (43 IU/kg) were given to relevant groups of rats along with high-fructose high-fat diet for 42 days. HbA1c, D-lactate, Glyoxylase-1, Hexokinase 2, malondialdehyde (MDA), glutathione peroxidase (GPx), catalase (CAT), nuclear transcription factor-B (NF-κB), interleukin-6 (IL-6), interleukin-8 (IL-8) and histological examinations were performed after 42 days. The docking simulations were conducted using Auto Dock package. The combined effects of rutin and vitamin A in treated rats significantly (p < 0.001) reduced HbA1c, hexokinase 2, and D-lactate levels while preventing cellular damage. The combination dramatically (p < 0.001) decreased MDA, CAT, and GPx in treated rats and decreased the expression of inflammatory cytokines such as IL-6 andIL-8, as well as the transcription factor NF-κB. The molecular docking investigations revealed that rutin had a strong affinity for several important biomolecules, including as NF-κB, Catalase, MDA, IL-6, hexokinase 2, and GPx. The results propose beneficial impact of rutin and vitamin A as a convincing treatment strategy to treat AGE-related disorders, such as diabetes, autism, alzheimer's, atherosclerosis.

In silico identification of a novel Cdc2-like kinase 2 (CLK2) inhibitor in triple negative breast cancer.

Dysregulation of RNA splicing processes is intricately linked to tumorigenesis in various cancers, especially breast cancer. Cdc2-like kinase 2 (CLK2), an oncogenic RNA-splicing kinase pivotal in breast cancer, plays a significant role, particularly in the context of triple-negative breast cancer (TNBC), a subtype marked by substantial medical challenges due to its low survival rates. In this study, we employed a structure-based virtual screening (SBVS) method to identify potential CLK2 inhibitors with novel chemical structures for treating TNBC. Compound 670551 emerged as a novel CLK2 inhibitor with a 50% inhibitory concentration (IC50) value of 619.7 nM. Importantly, Compound 670551 exhibited high selectivity for CLK2 over other protein kinases. Functionally, this compound significantly reduced the survival and proliferation of TNBC cells. Results from a cell-based assay demonstrated that this inhibitor led to a decrease in RNA splicing proteins, such as SRSF4 and SRSF6, resulting in cell apoptosis. In summary, we identified a novel CLK2 inhibitor as a promising potential treatment for TNBC therapy.

Structural and functional insights into transcription activation of the essential LysR-type transcriptional regulators.

The enormous LysR-type transcriptional regulators (LTTRs), which are diversely distributed amongst prokaryotes, play crucial roles in transcription regulation of genes involved in basic metabolic pathways, virulence and stress resistance. However, the precise transcription activation mechanism of these genes by LTTRs remains to be explored. Here, we determine the cryo-EM structure of a LTTR-dependent transcription activation complex comprising of Escherichia coli RNA polymerase (RNAP), an essential LTTR protein GcvA and its cognate promoter DNA. Structural analysis shows two N-terminal DNA binding domains of GcvA (GcvA_DBD) dimerize and engage the GcvA activation binding sites, presenting the -35 element for specific recognition with the conserved σ70R4. In particular, the versatile C-terminal domain of α subunit of RNAP directly interconnects with GcvA_DBD, σ70R4 and promoter DNA, providing more interfaces for stabilizing the complex. Moreover, molecular docking supports glycine as one potential inducer of GcvA, and single molecule photobleaching experiments kinetically visualize the occurrence of tetrameric GcvA-engaged transcription activation complex as suggested for the other LTTR homologs. Thus, a general model for tetrameric LTTR-dependent transcription activation is proposed. These findings will provide new structural and functional insights into transcription activation of the essential LTTRs.

An ensemble machine learning model generates a focused screening library for the identification of CDK8 inhibitors.

The identification of an effective inhibitor is an important starting step in drug development. Unfortunately, many issues such as the characterization of protein binding sites, the screening library, materials for assays, etc., make drug screening a difficult proposition. As the size of screening libraries increases, more resources will be inefficiently consumed. Thus, new strategies are needed to preprocess and focus a screening library towards a targeted protein. Herein, we report an ensemble machine learning (ML) model to generate a CDK8-focused screening library. The ensemble model consists of six different algorithms optimized for CDK8 inhibitor classification. The models were trained using a CDK8-specific fragment library along with molecules containing CDK8 activity. The optimized ensemble model processed a commercial library containing 1.6 million molecules. This resulted in a CDK8-focused screening library containing 1,672 molecules, a reduction of more than 99.90%. The CDK8-focused library was then subjected to molecular docking, and 25 candidate compounds were selected. Enzymatic assays confirmed six CDK8 inhibitors, with one compound producing an IC50 value of ≤100 nM. Analysis of the ensemble ML model reveals the role of the CDK8 fragment library during training. Structural analysis of molecules reveals the hit compounds to be structurally novel CDK8 inhibitors. Together, the results highlight a pipeline for curating a focused library for a specific protein target, such as CDK8.

Globospiramine from Voacanga globosa Exerts Robust Cytotoxic and Antiproliferative Activities on Cancer Cells by Inducing Caspase-Dependent Apoptosis in A549 Cells and Inhibiting MAPK14 (p38α): In Vitro and Computational Investigations.

Bisindole alkaloids are a source of inspiration for the design and discovery of new-generation anticancer agents. In this study, we investigated the cytotoxic and antiproliferative activities of three spirobisindole alkaloids from the traditional anticancer Philippine medicinal plant Voacanga globosa, along with their mechanisms of action. Thus, the alkaloids globospiramine (1), deoxyvobtusine (2), and vobtusine lactone (3) showed in vitro cytotoxicity and antiproliferative activities against the tested cell lines (L929, KB3.1, A431, MCF-7, A549, PC-3, and SKOV-3) using MTT and CellTiter-Blue assays. Globospiramine (1) was also screened against a panel of breast cancer cell lines using the sulforhodamine B (SRB) assay and showed moderate cytotoxicity. It also promoted the activation of apoptotic effector caspases 3 and 7 using Caspase-Glo 3/7 and CellEvent-3/7 apoptosis assays. Increased expressions of cleaved caspase 3 and PARP in A549 cells treated with 1 were also observed. Apoptotic activity was also confirmed when globospiramine (1) failed to promote the rapid loss of membrane integrity according to the HeLa cell membrane permeability assay. Network pharmacology analysis, molecular docking, and molecular dynamics simulations identified MAPK14 (p38α), a pharmacological target leading to cancer cell apoptosis, as a putative target. Low toxicity risks and favorable drug-likeness were also predicted for 1. Overall, our study demonstrated the anticancer potentials and apoptotic mechanisms of globospiramine (1), validating the traditional medicinal use of Voacanga globosa.

Small-Molecule Inhibitors of TIPE3 Protein Identified through Deep Learning Suppress Cancer Cell Growth In Vitro.

Tumor necrosis factor-α-induced protein 8-like 3 (TNFAIP8L3 or TIPE3) functions as a transfer protein for lipid second messengers. TIPE3 is highly upregulated in several human cancers and has been established to significantly promote tumor cell proliferation, migration, and invasion and inhibit the apoptosis of cancer cells. Thus, inhibiting the function of TIPE3 is expected to be an effective strategy against cancer. The advancement of artificial intelligence (AI)-driven drug development has recently invigorated research in anti-cancer drug development. In this work, we incorporated DFCNN, Autodock Vina docking, DeepBindBC, MD, and metadynamics to efficiently identify inhibitors of TIPE3 from a ZINC compound dataset. Six potential candidates were selected for further experimental study to validate their anti-tumor activity. Among these, three small-molecule compounds (K784-8160, E745-0011, and 7238-1516) showed significant anti-tumor activity in vitro, leading to reduced tumor cell viability, proliferation, and migration and enhanced apoptotic tumor cell death. Notably, E745-0011 and 7238-1516 exhibited selective cytotoxicity toward tumor cells with high TIPE3 expression while having little or no effect on normal human cells or tumor cells with low TIPE3 expression. A molecular docking analysis further supported their interactions with TIPE3, highlighting hydrophobic interactions and their shared interaction residues and offering insights for designing more effective inhibitors. Taken together, this work demonstrates the feasibility of incorporating deep learning and MD simulations in virtual drug screening and provides inhibitors with significant potential for anti-cancer drug development against TIPE3-.

Multi-epitope vaccine design using in silico analysis of glycoprotein and nucleocapsid of NIPAH virus.

According to the 2018 WHO R&D Blueprint, Nipah virus (NiV) is a priority disease, and the development of a vaccine against NiV is strongly encouraged. According to criteria used to categorize zoonotic diseases, NiV is a stage III disease that can spread to people and cause unpredictable outbreaks. Since 2001, the NiV virus has caused annual outbreaks in Bangladesh, while in India it has caused occasional outbreaks. According to estimates, the mortality rate for infected individuals ranges from 70 to 91%. Using immunoinformatic approaches to anticipate the epitopes of the MHC-I, MHC-II, and B-cells, they were predicted using the NiV glycoprotein and nucleocapsid protein. The selected epitopes were used to develop a multi-epitope vaccine construct connected with linkers and adjuvants in order to improve immune responses to the vaccine construct. The 3D structure of the engineered vaccine was anticipated, optimized, and confirmed using a variety of computer simulation techniques so that its stability could be assessed. According to the immunological simulation tests, it was found that the vaccination elicits a targeted immune response against the NiV. Docking with TLR-3, 7, and 8 revealed that vaccine candidates had high binding affinities and low binding energies. Finally, molecular dynamic analysis confirms the stability of the new vaccine. Codon optimization and in silico cloning showed that the proposed vaccine was expressed to a high degree in Escherichia coli. The study will help in identifying a potential epitope for a vaccine candidate against NiV. The developed multi-epitope vaccine construct has a lot of potential, but they still need to be verified by in vitro & in vivo studies.

Predicting drug-Protein interaction with deep learning framework for molecular graphs and sequences: Potential candidates against SAR-CoV-2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COVID-19 disease, which represents a new life-threatening disaster. Regarding viral infection, many therapeutics have been investigated to alleviate the epidemiology such as vaccines and receptor decoys. However, the continuous mutating coronavirus, especially the variants of Delta and Omicron, are tended to invalidate the therapeutic biological product. Thus, it is necessary to develop molecular entities as broad-spectrum antiviral drugs. Coronavirus replication is controlled by the viral 3-chymotrypsin-like cysteine protease (3CLpro) enzyme, which is required for the virus's life cycle. In the cases of severe acute respiratory syndrome coronavirus (SARS-CoV) and middle east respiratory syndrome coronavirus (MERS-CoV), 3CLpro has been shown to be a promising therapeutic development target. Here we proposed an attention-based deep learning framework for molecular graphs and sequences, training from the BindingDB 3CLpro dataset (114,555 compounds). After construction of such model, we conducted large-scale screening the in vivo/vitro dataset (276,003 compounds) from Zinc Database and visualize the candidate compounds with attention score. geometric-based affinity prediction was employed for validation. Finally, we established a 3CLpro-specific deep learning framework, namely GraphDPI-3CL (AUROC: 0.958) achieved superior performance beyond the existing state of the art model and discovered 10 molecules with a high binding affinity of 3CLpro and superior binding mode.

Research in revealing the effects on Cuscuta chinensis to diarrhea type irritable bowel syndrome based on network pharmacology and molecular docking potential mechanism.

To explore the potential mechanism in Cuscuta sinensis on diarrhea-type irritable bowel syndrome using network pharmacology and molecular docking techniques. First, the active components and related targets of Cuscuta were found setting oral utilization >30% and drug-like properties greater than or equal to 0.18 as filter information from TCMSP database. The targets of diarrheal irritable bowel syndrome were compiled by searching DrugBank, GeneCards, OMIM, PharmGkb, and TTD databases. The intersections of drugs and targets related to the disease were taken for gene ontology enrichment and Kyoto encyclopedia of genes and genomes enrichment analyses, to elucidate the potential molecular mechanisms and pathway information of Cuscuta sinensis for the treatment of diarrheal irritable bowel syndrome. The protein-protein interaction network was constructed by using the STRING database and visualized with Cytoscape_v3.10.0 software to find the protein-protein interaction network core At last, molecular docking was performed to validate the combination of active compounds with the core target. The target information of Cuscuta and diarrhea-type irritable bowel syndrome was compiled, which can be resulted in 11 active compounds such as quercetin, kaempferol, isorhamnetin, ß-sitosterol, and another 17 core targets such as TP53, IL6, AKT1, IL1B, TNF, EGFR, etc, whose Kyoto encyclopedia of genes and genomes was enriched in the pathways of lipids and atherosclerosis, chemical carcinogenesis-receptor activation, PI3K-Akt signaling pathway, and fluid shear stress and atherosclerosis, etc. Docking demonstrated that the core targets and the active compounds were able to be better combined. Cuscuta chinensis may exert preventive effects on diarrhea-type irritable bowel syndrome by reducing intestinal inflammation, protecting intestinal mucosa, and playing an important role in antioxidant response through multi-targets and multi-pathways.

THOC6 is a novel biomarker of glioma and a target of anti-glioma drugs: An analysis based on bioinformatics and molecular docking.

Glioma is a typical malignant tumor of the nervous system. It is of great significance to identify new biomarkers for accurate diagnosis of glioma. In this context, THOC6 has been studied as a highly diagnostic prognostic biomarker, which contributes to improve the dilemma in diagnosing gliomas. We used online databases and a variety of statistical methods, such as Wilcoxon rank sum test, Dunn test and t test. We analyzed the mutation, location and expression profile of THOC6, revealing the network of THOC6 interaction with disease. Wilcoxon rank sum test showed that THOC6 is highly expressed in gliomas (P < 0.001). Dunn test, Wilcoxon rank sum test and t test showed that THOC6 expression was correlated with multiple clinical features. Logistic regression analysis further confirmed that THOC6 gene expression was a categorical dependent variable related to clinical features of poor prognosis. Kaplan-Meier survival analysis showed that the overall survival (OS) of glioma patients with high expression of THOC6 was poor (P < 0.001). Both univariate (P < 0.001) and multivariate (P = 0.04) Cox analysis confirmed that THOC6 gene expression was an independent risk factor for OS in patients with glioma. ROC curve analysis showed that THOC6 had a high diagnostic value in glioma (AUC = 0.915). Based on this, we constructed a nomogram to predict patient survival. Enrichment analysis showed that THOC6 expression was associated with multiple signal pathways. Immuno-infiltration analysis showed that the expression of THOC6 in glioma was closely related to the infiltration level of multiple immune cells. Molecular docking results showed that THOC6 might be the target of anti-glioma drugs. THOC6 is a novel diagnostic factor and prognostic biomarker of glioma.

Uncovering the molecular mechanism of Mume Fructus in treatment of Sjögren's syndrome.

BACKGROUND: Modern medicine has no cure for the xerostomia caused by the early onset of Sjögren's syndrome. Mume Fructus is a common Chinese herbal medicine used to relieve xerostomia. However, the molecular mechanisms of the effects of Mume Fructus are unknown. In this study, network pharmacology and molecular docking were used to investigate the mechanisms of action of Mume Fructus on Sjögren's syndrome. MATERIALS AND METHOD: The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database was used to identify the active components and targets of Mume Fructus, and the UniProt database was used to identify the genes encoding these targets. SS-related targets were also identified from the GeneCards and OMIM databases. By finding the intersection of the targets of the compounds and the targets of Sjögren's syndrome, the predicted targets of Mume Fructus in the treatment of Sjögren's syndrome were obtained. Further investigation of the active compounds and their targets was carried out by constructing a network of "medicine-candidate compound-target-disease" using Cytoscape 3.7.2, the Protein-Protein Interaction network using the STRING database and Cytoscape 3.7.2, and key targets were identified by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis on R software. Finally, molecular docking was used to verify the affinity of the candidate compounds to the key targets. RESULTS: Quercetin, beta-sitosterol, and kaempferol in Mume Fructus interact with AKT1, IL-6, IL-1B, JUN, CASP3, and MAPK8. These results suggest that Mume Fructus exerts its therapeutic effects on the peripheral gland injury of Sjögren's syndrome and its secondary cardiovascular disease and tumorigenesis through anti-inflammatory, anti-oxidant, and anti-tumor pathways. CONCLUSION: With network pharmacology, this study systematically identified the main active components, targets, and specific mechanisms of the therapeutic effects of Mume Fructus on Sjögren's syndrome, providing both a theoretical basis and research direction for further investigations on Mume Fructus.

Exploring the efficacy and molecular mechanism of Danhong injection comprehensively in the treatment of idiopathic pulmonary fibrosis by combining meta-analysis, network pharmacology, and molecular docking methods.

BACKGROUND: Danhong injection, a compound injection of Chinese herbal medicine, has been widely used in idiopathic pulmonary fibrosis (IPF) at present as an adjuvant treatment. However, the clinical efficacy and molecular mechanism of IPF are still unclear. This study will evaluate and explore the clinical efficacy and molecular mechanism of Danhong injection in the treatment of IPF. METHODS: In meta-analysis, the computer was used to search 8 databases (PubMed, EMbase, CENTRAL, MEDLINE, CBM, CNKI, WanFang, and VIP) to collect the RCTs, and RevMan 5.3 and Stata 14.0 were used for statistical analysis. It has been registered on PROSPERO: CRD42020221096. In network pharmacology, the main chemical components and targets of the chemical components of Danhong injection were obtained in TCMSP and Swiss Target Prediction databases. The main targets of IPF were obtained through Gencards, Disgenet, OMIM, TTD, and DRUGBANK databases. The String platform was used to construct PPI networks. Cytoscape 3.8.2 was used to construct the "Danhong components - IPF targets-pathways" network. The molecular docking verification was conducted by Auto Dock. RESULTS: Twelve RCTs were finally included with a total of 896 patients. The meta-analysis showed that Danhong injection could improve the clinical efficiency ([OR] = 0.25, 95% CI [0.15, 0.41]), lung function, arterial blood gas analysis, inflammatory cytokines, and serum cytokines associated with pulmonary fibrosis of IPF patients, respectively (P < .05). The core active components of Danhong injection on IPF were Luteolin, Quercetin, and Kaempferol, and the core targets were PTGS2, AR, ESR1, PPARG, and RELA. Danhong injection mainly improved IPF through PD-L1 expression and PD-1 checkpoint path in cancer, pathways in cancer, PI3K-Akt signaling pathway, etc. CONCLUSION: These results provided scientific basis for the clinical use of Danhong injection for the treatment of IPF, and provided a new direction to explore the potential mechanism of action of Danhong injection.

The synchronized feature of Saururus chinensis and gut microbiota against T2DM, NAFLD, obesity and hypertension via integrated pharmacology.

Type 2 diabetes mellitus (T2DM), nonalcoholic fatty liver disease (NAFLD), obesity (OB) and hypertension (HT) are categorized as metabolic disorders (MDs), which develop independently without distinct borders. Herein, we examined the gut microbiota (GM) and Saururus chinensis (SC) to confirm their therapeutic effects via integrated pharmacology. The overlapping targets from the four diseases were determined to be key protein coding genes. The protein-protein interaction (PPI) networks, and the SC, GM, signalling pathway, target and metabolite (SGSTM) networks were analysed via RPackage. Additionally, molecular docking tests (MDTs) and density functional theory (DFT) analysis were conducted to determine the affinity and stability of the conformer(s). TNF was the main target in the PPI analysis, and equol derived from Lactobacillus paracasei JS1 was the most effective agent for the formation of the TNF complex. The SC agonism (PPAR signalling pathway), and antagonism (neurotrophin signalling pathway) by SC were identified as agonistic bioactives (aromadendrane, stigmasta-5,22-dien-3-ol, 3,6,6-trimethyl-3,4,5,7,8,9-hexahydro-1H-2-benzoxepine, 4α-5α-epoxycholestane and kinic acid), and antagonistic bioactives (STK734327 and piclamilast), respectively, via MDT. Finally, STK734327-MAPK1 was the most favourable conformer according to DFT. Overall, the seven bioactives from SC and equol that can be produced by Lactobacillus paracasei JS1 can exert synergistic effects on these four diseases.

An Overview of SARS-CoV-2 Potential Targets, Inhibitors, and Computational Insights to Enrich the Promising Treatment Strategies.

The rapid spread of the SARS-CoV-2 virus has emphasized the urgent need for effective therapies to combat COVID-19. Investigating the potential targets, inhibitors, and in silico approaches pertinent to COVID-19 are of utmost need to develop novel therapeutic agents and reprofiling of existing FDA-approved drugs. This article reviews the viral enzymes and their counter receptors involved in the entry of SARS-CoV-2 into host cells, replication of genomic RNA, and controlling the host cell physiology. In addition, the study provides an overview of the computational techniques such as docking simulations, molecular dynamics, QSAR modeling, and homology modeling that have been used to find the FDA-approved drugs and other inhibitors against SARS-CoV-2. Furthermore, a comprehensive overview of virus-based and host-based druggable targets from a structural point of view, together with the reported therapeutic compounds against SARS-CoV-2 have also been presented. The current study offers future perspectives for research in the field of network pharmacology investigating the large unexplored molecular libraries. Overall, the present in-depth review aims to expedite the process of identifying and repurposing drugs for researchers involved in the field of COVID-19 drug discovery.

Heterologous expression and structure prediction of a xylanase identified from a compost metagenomic library.

Xylanases are key biocatalysts in the degradation of the ß-1,4-glycosidic linkages in the xylan backbone of hemicellulose. These enzymes are potentially applied in a wide range of bioprocessing industries under harsh conditions. Metagenomics has emerged as powerful tools for the bioprospection and discovery of interesting bioactive molecules from extreme ecosystems with unique features, such as high temperatures. In this study, an innovative combination of function-driven screening of a compost metagenomic library and automatic extraction of halo areas with in-house MATLAB functions resulted in the identification of a promising clone with xylanase activity (LP4). The LP4 clone proved to be an effective xylanase producer under submerged fermentation conditions. Sequence and phylogenetic analyses revealed that the xylanase, Xyl4, corresponded to an endo-1,4-ß-xylanase belonging to glycosyl hydrolase family 10 (GH10). When xyl4 was expressed in Escherichia coli BL21(DE3), the enzyme activity increased about 2-fold compared to the LP4 clone. To get insight on the interaction of the enzyme with the substrate and establish possible strategies to improve its activity, the structure of Xyl4 was predicted, refined, and docked with xylohexaose. Our data unveiled, for the first time, the relevance of the amino acids Glu133 and Glu238 for catalysis, and a close inspection of the catalytic site suggested that the replacement of Phe316 by a bulkier Trp may improve Xyl4 activity. Our current findings contribute to enhancing the catalytic performance of Xyl4 towards industrial applications. KEY POINTS: • A GH10 endo-1,4-ß-xylanase (Xyl4) was isolated from a compost metagenomic library • MATLAB's in-house functions were developed to identify the xylanase-producing clones • Computational analysis showed that Glu133 and Glu238 are crucial residues for catalysis.

Expression analysis and mapping of Viral-Host Protein interactions of Poxviridae suggests a lead candidate molecule targeting Mpox.

BACKGROUND: Monkeypox (Mpox) is an important human pathogen without etiological treatment. A viral-host interactome study may advance our understanding of molecular pathogenesis and lead to the discovery of suitable therapeutic targets. METHODS: GEO Expression datasets characterizing mRNA profile changes in different host responses to poxviruses were analyzed for shared pathway identification, and then, the Protein-protein interaction (PPI) maps were built. The viral gene expression datasets of Monkeypox virus (MPXV) and Vaccinia virus (VACV) were used to identify the significant viral genes and further investigated for their binding to the library of targeting molecules. RESULTS: Infection with MPXV interferes with various cellular pathways, including interleukin and MAPK signaling. While most host differentially expressed genes (DEGs) are predominantly downregulated upon infection, marked enrichments in histone modifiers and immune-related genes were observed. PPI analysis revealed a set of novel virus-specific protein interactions for the genes in the above functional clusters. The viral DEGs exhibited variable expression patterns in three studied cell types: primary human monocytes, primary human fibroblast, and HeLa, resulting in 118 commonly deregulated proteins. Poxvirus proteins C6R derived protein K7 and K7R of MPXV and VACV were prioritized as targets for potential therapeutic interventions based on their histone-regulating and immunosuppressive properties. In the computational docking and Molecular Dynamics (MD) experiments, these proteins were shown to bind the candidate small molecule S3I-201, which was further prioritized for lead development. RESULTS: MPXV circumvents cellular antiviral defenses by engaging histone modification and immune evasion strategies. C6R-derived protein K7 binding candidate molecule S3I-201 is a priority promising candidate for treating Mpox.

Synthesis, In Silico and Kinetics Evaluation of N-(ß-d-glucopyranosyl)-2-arylimidazole-4(5)-carboxamides and N-(ß-d-glucopyranosyl)-4(5)-arylimidazole-2-carboxamides as Glycogen Phosphorylase Inhibitors.

Recently studied N-(ß-d-glucopyranosyl)-3-aryl-1,2,4-triazole-5-carboxamides have proven to be low micromolar inhibitors of glycogen phosphorylase (GP), a validated target for the treatment of type 2 diabetes mellitus. Since in other settings, the bioisosteric replacement of the 1,2,4-triazole moiety with imidazole resulted in significantly more efficient GP inhibitors, in silico calculations using Glide molecular docking along with unbound state DFT calculations were performed on N-(ß-d-glucopyranosyl)-arylimidazole-carboxamides, revealing their potential for strong GP inhibition. The syntheses of the target compounds involved the formation of an amide bond between per-O-acetylated ß-d-glucopyranosylamine and the corresponding arylimidazole-carboxylic acids. Kinetics experiments on rabbit muscle GPb revealed low micromolar inhibitors, with the best inhibition constants (Kis) of ~3-4 µM obtained for 1- and 2-naphthyl-substituted N-(ß-d-glucopyranosyl)-imidazolecarboxamides, 2b-c. The predicted protein-ligand interactions responsible for the observed potencies are discussed and will facilitate the structure-based design of other inhibitors targeting this important therapeutic target. Meanwhile, the importance of the careful consideration of ligand tautomeric states in binding calculations is highlighted, with the usefulness of DFT calculations in this regard proposed.

Isolation, Characterization, Genome Annotation, and Evaluation of Hyaluronidase Inhibitory Activity in Secondary Metabolites of Brevibacillus sp. JNUCC 41: A Comprehensive Analysis through Molecular Docking and Molecular Dynamics Simulation.

Brevibacillus sp. JNUCC 41, characterized as a plant-growth-promoting rhizobacterium (PGPR), actively participates in lipid metabolism and biocontrol based on gene analysis. This study aimed to investigate the crucial secondary metabolites in biological metabolism; fermentation, extraction, and isolation were performed, revealing that methyl indole-3-acetate showed the best hyaluronidase (HAase) inhibitory activity (IC50: 343.9 µM). Molecular docking results further revealed that the compound forms hydrogen bonds with the residues Tyr-75 and Tyr-247 of HAase (binding energy: -6.4 kcal/mol). Molecular dynamics (MD) simulations demonstrated that the compound predominantly binds to HAase via hydrogen bonding (MM-PBSA binding energy: -24.9 kcal/mol) and exhibits good stability. The residues Tyr-247 and Tyr-202, pivotal for binding in docking, were also confirmed via MD simulations. This study suggests that methyl indole-3-acetate holds potential applications in anti-inflammatory and anti-aging treatments.

Computational Design of Novel Cyclic Peptides Endowed with Autophagy-Inhibiting Activity on Cancer Cell Lines.

(1) Autophagy plays a significant role in development and cell proliferation. This process is mainly accomplished by the LC3 protein, which, after maturation, builds the nascent autophagosomes. The inhibition of LC3 maturation results in the interference of autophagy activation. (2) In this study, starting from the structure of a known LC3B binder (LIR2-RavZ peptide), we identified new LC3B ligands by applying an in silico drug design strategy. The most promising peptides were synthesized, biophysically assayed, and biologically evaluated to ascertain their potential antiproliferative activity on five humans cell lines. (3) A cyclic peptide (named Pep6), endowed with high conformational stability (due to the presence of a disulfide bridge), displayed a Kd value on LC3B in the nanomolar range. Assays accomplished on PC3, MCF-7, and A549 cancer cell lines proved that Pep6 exhibited cytotoxic effects comparable to those of the peptide LIR2-RavZ, a reference LC3B ligand. Furthermore, it was ineffective on both normal prostatic epithelium PNT2 and autophagy-defective prostate cancer DU145 cells. (4) Pep6 can be considered a new autophagy inhibitor that can be employed as a pharmacological tool or even as a template for the rational design of new small molecules endowed with autophagy inhibitory activity.