UNASSIGNED: To explore the mechanism of PG against acute lymphoblastic leukaemia (ALL) by network pharmacology and experimental verification in vitro.
UNASSIGNED: First, the biological activity of PG against B-ALL was determined by CCK-8 and flow cytometry. Then, the potential targets of PG were obtained from the PharmMapper database. ALL-related genes were collected from the GeneCards, OMIM and PharmGkb databases. The two datasets were intersected to obtain the target genes of PG in ALL. Then, protein interaction networks were constructed using the STRING database. The key targets were obtained by topological analysis of the network with Cytoscape 3.8.0 software. In addition, the mechanism of PG in ALL was confirmed by protein‒protein interaction, gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Furthermore, molecular docking was carried out by AutoDock Vina. Finally, Western blotting was performed to confirm the effect of PG on NALM6 cells.
UNASSIGNED: PG inhibited the proliferation of NALM6 cells. A total of 174 antileukaemic targets of PG were obtained by network pharmacology. The key targets included AKT1, MAPK14, EGFR, ESR1, LCK, PTPN11, RHOA, IGF1, MDM2, HSP90AA1, HRAS, SRC and JAK2. Enrichment analysis found that PG had antileukaemic effects by regulating key targets such as MAPK signalling, and PG had good binding activity with MAPK14 protein (-8.9 kcal/mol). PG could upregulate the expression of the target protein p-P38, induce cell cycle arrest, and promote the apoptosis of leukaemia cells.
UNASSIGNED: MAPK14 was confirmed to be one of the key targets and pathways of PG by network pharmacology and molecular experiments.

UNASSIGNED: Oxidative stress is recognized as a major driver of non-alcoholic steatohepatitis (NASH) progression. The transcription factor NRF2 and its negative regulator KEAP1 are master regulators of redox, metabolic and protein homeostasis, as well as detoxification, and thus appear to be attractive targets for the treatment of NASH.
UNASSIGNED: Molecular modeling and X-ray crystallography were used to design S217879 - a small molecule that could disrupt the KEAP1-NRF2 interaction. S217879 was highly characterized using various molecular and cellular assays. It was then evaluated in two different NASH-relevant preclinical models, namely the methionine and choline-deficient diet (MCDD) and diet-induced obesity NASH (DIO NASH) models.
UNASSIGNED: Molecular and cell-based assays confirmed that S217879 is a highly potent and selective NRF2 activator with marked anti-inflammatory properties, as shown in primary human peripheral blood mononuclear cells. In MCDD mice, S217879 treatment for 2 weeks led to a dose-dependent reduction in NAFLD activity score while significantly increasing liver Nqo1 mRNA levels, a specific NRF2 target engagement biomarker. In DIO NASH mice, S217879 treatment resulted in a significant improvement of established liver injury, with a clear reduction in both NAS and liver fibrosis. αSMA and Col1A1 staining, as well as quantification of liver hydroxyproline levels, confirmed the reduction in liver fibrosis in response to S217879. RNA-sequencing analyses revealed major alterations in the liver transcriptome in response to S217879, with activation of NRF2-dependent gene transcription and marked inhibition of key signaling pathways that drive disease progression.
UNASSIGNED: These results highlight the potential of selective disruption of the NRF2-KEAP1 interaction for the treatment of NASH and liver fibrosis.
UNASSIGNED: We report the discovery of S217879 - a potent and selective NRF2 activator with good pharmacokinetic properties. By disrupting the KEAP1-NRF2 interaction, S217879 triggers the upregulation of the antioxidant response and the coordinated regulation of a wide spectrum of genes involved in NASH disease progression, leading ultimately to the reduction of both NASH and liver fibrosis progression in mice.

Meniscus, the cushion in knee joint, is a load-bearing tissue that transfers mechanical forces to extracellular matrix (ECM) and tissue resident cells. The mechanoresponse of human tissue resident stem/progenitor cells in meniscus (hMeSPCs) is significant to tissue homeostasis and regeneration but is not well understood. This study reports that a mild cyclic tensile loading regimen of ∼1800 loads/day on hMeSPCs seeded in 3-dimensional (3D) photocrosslinked gelatin methacryloyl (GelMA) hydrogel is critical in maintaining cellular homeostasis. Experimentally, a \"slow walk\" biomimetic cyclic loading regimen (10% tensile strain, 0.5 Hz, 1 h/day, up to 15 days) is applied to hMeSPCs encapsulated in GelMA hydrogel with a magnetic force-controlled loading actuator. The loading significantly increases cell differentiation and fibrocartilage-like ECM deposition without affecting cell viability. Transcriptomic analysis reveals 332 mechanoresponsive genes, clustered into cell senescence, mechanical sensitivity, and ECM dynamics, associated with interleukins, integrins, and collagens/matrix metalloproteinase pathways. The cell-GelMA constructs show active ECM remodeling, traced using a green fluorescence tagged (GFT)-GelMA hydrogel. Loading enhances nascent pericellular matrix production by the encapsulated hMeSPCs, which gradually compensates for the hydrogel loss in the cultures. These findings demonstrate the strong tissue-forming ability of hMeSPCs, and the importance of mechanical factors in maintaining meniscus homeostasis.

Cardiovascular disease is the most common disease in the world and the first among the causes of human death. Its morbidity and mortality increase annually, but no effective treatment is available. Therefore, new drugs should be developed to treat cardiovascular disease. Gentianella acuta (Michx.) Hulten (G. acuta) is an important Mongolian medicine in China and elicits protective effects on cardiovascular health. In this study, liquid chromatography-mass spectrometry (LC-MS) combined with network pharmacology was used to screen the main active ingredients and confirm that bellidifolin was one of the main components for the treatment of ischemic heart disease. Then, rat myocardial (H9c2) cells injury model induced by hydrogen peroxide (H2O2) in vitro was established to verify the effect of bellidifolin on oxidative stress stimulation, including determination of antioxidant enzyme activity and apoptosis. Transcriptome sequencing, qRT-PCR, and western blot were performed to further verify the antioxidant stress mechanism of bellidifolin. Results showed that bellidifolin pretreatment decreased the rate of apoptosis and the levels of lactate dehydrogenase (LDH), creatine kinase (CK), and alanine aminotransferase (ALT). Conversely, it increased the contents of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) in a dose-dependent manner, indicating that bellidifolin caused a protective effect on cardiomyocyte injury. Bellidifolin minimized the H2O2-induced cell injury by activating the PI3K-Akt signal pathway and downregulating glycogen synthase kinase-3β (GSK-3β) and p-Akt1/Akt1. Therefore, this work revealed that G. acuta has a good development prospect as an edible medicinal plant in cardiovascular disease. Its bellidifolin component is a potential therapeutic agent for cardiovascular disease induced by oxidative stress damage.

Protein-protein interactions (PPIs) are involved in most cellular processes. Unfortunately, current knowledge of host-pathogen interactomes is still very limited. Experimental methods used to detect PPIs have several limitations, including increasing complexity and economic cost in large-scale screenings. Hence, computational methods are commonly used to support experimental data, although they generally suffer from high false-positive rates. To address this issue, we have created HPIPred, a host-pathogen PPI prediction tool based on numerical encoding of physicochemical properties. Unlike other available methods, HPIPred integrates phenotypic data to prioritize biologically meaningful results. We used HPIPred to screen the entire Homo sapiens and Pseudomonas aeruginosa PAO1 proteomes to generate a host-pathogen interactome with 763 interactions displaying a highly connected network topology. Our predictive model can be used to prioritize protein-protein interactions as potential targets for antibacterial drug development. Available at: https://github.com/SysBioUAB/hpi_predictor.

Protein-protein interactions (PPI) play an essential role in the biological processes that occur in the cell. Therefore, the dissection of PPI networks becomes decisive to model functional coordination and predict pathological de-regulation. Cellular networks are dynamic and proteins display varying roles depending on the tissue-interactomic context. Thus, the use of centrality measures in individual proteins fall short to dissect the functional properties of the cell. For this reason, there is a need for more comprehensive, relational, and context-specific ways to analyze the multiple actions of proteins in different cells and identify specific functional assemblies within global biomolecular networks. Under this framework, we define Biological Interacting units (BioInt-U) as groups of proteins that interact physically and are enriched in a common Gene Ontology. A search strategy was applied on 33 tissue-specific (TS) PPI networks to generate BioInt libraries associated with each particular human tissue. The cross-tissue comparison showed that housekeeping assemblies incorporate different proteins and exhibit distinct network properties depending on the tissue. Furthermore, disease genes (DGs) of tissue-associated pathologies preferentially accumulate in units in the expected tissues, which in turn were more central in the TS networks. Overall, the study reveals a tissue-specific functional diversification based on the identification of specific protein units and suggests vulnerabilities specific of each tissue network, which can be applied to refine protein-disease association methods.

Protein seldom performs biological activities in isolation. Understanding the protein-protein interactions\' physical rewiring in response to pathological conditions or pathogen infection can help advance our comprehension of disease etiology, progression, and pathogenesis, which allow us to explore the alternate route to control the regulation of key target interactions, timely and effectively. Nonalcoholic steatohepatitis (NASH) is now a global public health problem exacerbated due to the lack of appropriate treatments. The most advanced anti-NASH lead compound (selonsertib) is withdrawn, though it is able to inhibit its target Apoptosis signal-regulating kinase 1 (ASK1) completely, indicating the necessity to explore alternate routes rather than complete inhibition. Understanding the interaction fingerprints of endogenous regulators at the molecular level that underpin disease formation and progression may spur the rationale of designing therapeutic strategies. Based on our analysis and thorough literature survey of the various key regulators and PTMs, the current review emphasizes PPI-based drug discovery\'s relevance for NASH conditions. The lack of structural detail (interface sites) of ASK1 and its regulators makes it challenging to characterize the PPI interfaces. This review summarizes key regulators interaction fingerprinting of ASK1, which can be explored further to restore the homeostasis from its hyperactive states for therapeutics intervention against NASH.

UNASSIGNED: Hertwig\'s Εpithelial Root Sheath (HΕRS) has a major function in the developing tooth roots. Earlier research revealed that it undergoes epithelial-mesenchymal transition, a vital process for the morphogenesis and complete development of the tooth and its surrounding periodontium. Few studies have demonstrated the role of HERS in cementogenesis through ΕMΤ. The background of this in-silico system biology approach is to find a hub protein and gene involved in the EMT of HERS that may uncover novel insights in periodontal regenerative drug targets.
UNASSIGNED: The protein and gene list involved in epithelial-mesenchymal transition were obtained from literature sources. The protein interaction was constructed using STRING software and the protein interaction network was analyzed. Molecular docking simulation checks the binding energy and stability of protein-ligand complex.
UNASSIGNED: Results revealed the hub gene to be DYRK1A(Hepcidin), and the ligand was identified as isoetharine. SΤRIΝG results showed a confidence cutoff of 0.9 in sensitivity analysis with a condensed protein interaction network. Overall, 98 nodes from 163 nodes of expected edges were found with an average node degree of 11.9. Docking results show binding energy of -4.70, and simulation results show an RMSD value of 5.6 Å at 50 ns.
UNASSIGNED: Isoetharine could be a potential drug for periodontal regeneration.

Since the beginning of the of SARS-CoV-2 (Covid-19) pandemic, variants of concern (VOC) have emerged taxing health systems worldwide. In October 2020, a new variant of SARS-CoV-2 (B.1.617+/Delta variant) emerged in India, triggering a deadly wave of Covid-19. Epidemiological data strongly suggests that B.1.617+ is more transmissible and previous reports have revealed that B.1.617+ has numerous mutations compared to wild type (WT), including several changes in the spike protein (SP). The main goal of this study was to use In Silico (computer simulation) techniques to examine mutations in the SP, specifically L452R and E484Q (part of the receptor binding domain (RBD) for human angiotensin-converting enzyme 2 (hACE2)) and P681R (upstream of the Furin cleavage motif), for effects in modulating the transmissibility of the B.1.617+ variant. Using computational models, the binding free energy (BFE) and H-bond lengths were calculated for SP-hACE2 and SP-Furin complexes. Comparison of the SP-hACE2 complex in the WT and B.1.617+ revealed both complexes have identical receptor-binding modes but the total BFE of B.1.617+ binding was more favorable for complex formation than WT, suggesting L452R and E484Q have a moderate impact on binding affinity. In contrast, the SP-Furin complex of B.1.617+ substantially lowered the BFE and revealed changes in molecular interactions compared to the WT complex, implying stronger complex formation between the variant and Furin. This study provides an insight into mutations that modulate transmissibility of the B.1.617+ variant, specifically the P681R mutation which appears to enhance transmissibility of the B.1.617+ variant by rendering it more receptive to Furin.

Breast cancer accounts for nearly half of all cancer-related deaths in women worldwide. However, the molecular mechanisms that lead to tumour development and progression remain poorly understood and there is a need to identify candidate genes associated with primary and metastatic breast cancer progression and prognosis. In this study, candidate genes associated with prognosis of primary and metastatic breast cancer were explored through a novel bioinformatics approach. Primary and metastatic breast cancer tissues and adjacent normal breast tissues were evaluated to identify biomarkers characteristic of primary and metastatic breast cancer. The Cancer Genome Atlas-breast invasive carcinoma (TCGA-BRCA) dataset (ID: HS-01619) was downloaded using the mRNASeq platform. Genevestigator 8.3.2 was used to analyse TCGA-BRCA gene expression profiles between the sample groups and identify the differentially-expressed genes (DEGs) in each group. For each group, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were used to determine the function of DEGs. Networks of protein-protein interactions were constructed to identify the top hub genes with the highest degree of interaction. Additionally, the top hub genes were validated based on overall survival and immunohistochemistry using The Human Protein Atlas. Of the top 20 hub genes identified, four (KRT14, KIT, RAD51, and TTK) were considered as prognostic risk factors based on overall survival. KRT14 and KIT expression levels were upregulated while those of RAD51 and TTK were downregulated in patients with breast cancer. The four proposed candidate hub genes might aid in further understanding the molecular changes that distinguish primary breast tumours from metastatic tumours as well as help in developing novel therapeutics. Furthermore, they may serve as effective prognostic risk markers based on the strong correlation between their expression and patient overall survival.