Activity-Directed Synthesis of Inhibitors of the p53/hDM2 Protein-Protein Interaction

Protein-protein interactions (PPIs) provide a rich source of potential targets for drug discovery and biomedical science research. However, the identification of structural-diverse starting points for discovery of PPI inhibitors remains a significant challenge. Activity-directed synthesis (ADS), a function-driven discovery approach, was harnessed in the discovery of the p53/hDM2 PPI. Over two rounds of ADS, 346 microscale reactions were performed, with prioritisation on the basis of the activity of the resulting product mixtures. Four distinct and novel series of PPI inhibitors were discovered that, through biophysical characterisation, were shown to have promising ligand efficiencies. It was thus shown that ADS can facilitate ligand discovery for a target that does not have a defined small-molecule binding site, and can provide distinctive starting points for the discovery of PPI inhibitors.

Quantitative phosphoproteomic analysis provides insights into the aluminum-responsiveness of Tamba black soybean

Aluminum (Al3+) toxicity is one of the most important limitations to agricultural production worldwide. The overall response of plants to Al3+ stress has been documented, but the contribution of protein phosphorylation to Al3+ detoxicity and tolerance in plants is unclear. Using a combination of tandem mass tag (TMT) labeling, immobilized metal affinity chromatography (IMAC) enrichment and liquid chromatography-tandem mass spectrometry (LC-MS/MS), Al3+-induced phosphoproteomic changes in roots of Tamba black soybean (TBS) were investigated in this study. The Data collected in this study are available via ProteomeXchange with the identifier PXD019807. After the Al3+ treatment, 189 proteins harboring 278 phosphosites were significantly changed (fold change > 1.2 or < 0.83, p < 0.05), with 88 upregulated, 96 downregulated and 5 up-/downregulated. Enrichment and protein interaction analyses revealed that differentially phosphorylated proteins (DPPs) under the Al3+ treatment were mainly related to G-protein-mediated signaling, transcription and translation, transporters and carbohydrate metabolism. Particularly, DPPs associated with root growth inhibition or citric acid synthesis were identified. The results of this study provide novel insights into the molecular mechanisms of TBS post-translational modifications in response to Al3+ stress.

An integrated drug repurposing strategy for the rapid identification of potential SARS-CoV-2 viral inhibitors

The Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2). The virus has rapidly spread in humans, causing the ongoing Coronavirus pandemic. Recent studies have shown that, similarly to SARS-CoV, SARS-CoV-2 utilises the Spike glycoprotein on the envelope to recognise and bind the human receptor ACE2. This event initiates the fusion of viral and host cell membranes and then the viral entry into the host cell. Despite several ongoing clinical studies, there are currently no approved vaccines or drugs that specifically target SARS-CoV-2. Until an effective vaccine is available, repurposing FDA approved drugs could significantly shorten the time and reduce the cost compared to de novo drug discovery. In this study we attempted to overcome the limitation of in silico virtual screening by applying a robust in silico drug repurposing strategy. We combined and integrated docking simulations, with molecular dynamics (MD), Supervised MD (SuMD) and Steered MD (SMD) simulations to identify a Spike protein - ACE2 interaction inhibitor. Our data showed that Simeprevir and Lumacaftor bind the receptor-binding domain of the Spike protein with high affinity and prevent ACE2 interaction.

Interactions between functionalised silica nanoparticles and Pseudomonas fluorescens biofilm matrix: A focus on the protein corona

Biofilms are microbial communities embedded in an extracellular polymeric matrix and display an enhanced tolerance to the action of antimicrobials. The emergence of novel functionalised nanoparticles is considered a promising avenue for the development of biofilm-specific antimicrobial technologies. However, there is a gap in the understanding of interactions between nanoparticles and the biofilm matrix. Particularly, questions are raised on how nanoparticle charge and surface groups play a role in aggregation when in contact with biofilm components. Herein we present the synthesis of four types of silica nanoparticles and undertake an analysis of their interactions with Pseudomonas fluorescens biofilm matrix. The effect of the biofilm matrix components on the charge and aggregation of the nanoparticles was assessed. Additionally, the study focused on the role of matrix proteins, with the in-depth characterisation of the protein corona of each nanoparticle by Liquid Chromatography with Tandem Mass Spectrometry experiments. The protein corona composition is dependent on the nanoparticle type; non-functionalised nanoparticles show less protein selectivity, whereas carboxylate-functionalised nanoparticles prefer proteins with a higher isoelectric point. These outcomes provide insights into the field of biofilm-nanoparticle interactions that can be valuable for the design of new nano-based targeting systems in future anti-biofilm applications.

Exploring Drug Treatment Patterns Based on the Action of Drug and Multilayer Network Model

Some drugs can be used to treat multiple diseases, suggesting potential patterns in drug treatment. Determination of drug treatment patterns can improve our understanding of the mechanisms of drug action, enabling drug repurposing. A drug can be associated with a multilayer tissue-specific protein-protein interaction (TSPPI) network for the diseases it is used to treat. Proteins usually interact with other proteins to achieve functions that cause diseases. Hence, studying drug treatment patterns is similar to studying common module structures in multilayer TSPPI networks. Therefore, we propose a network-based model to study the treatment patterns of drugs. The method was designated SDTP (studying drug treatment pattern) and was based on drug effects and a multilayer network model. To demonstrate the application of the SDTP method, we focused on analysis of trichostatin A (TSA) in leukemia, breast cancer, and prostate cancer. We constructed a TSPPI multilayer network and obtained candidate drug-target modules from the network. Gene ontology analysis provided insights into the significance of the drug-target modules and co-expression networks. Finally, two modules were obtained as potential treatment patterns for TSA. Through analysis of the significance, composition, and functions of the selected drug-target modules, we validated the feasibility and rationality of our proposed SDTP method for identifying drug treatment patterns. In summary, our novel approach used a multilayer network model to overcome the shortcomings of single-layer networks and combined the network with information on drug activity. Based on the discovered drug treatment patterns, we can predict the potential diseases that the drug can treat. That is, if a disease-related protein module has a similar structure, then the drug is likely to be a potential drug for the treatment of the disease.

A general-purpose Nanohybrid fabricated by Polymeric Au(I)-peptide precursor to wake the function of Peptide Therapeutics

Peptide-derived nanocomposites have been exhibiting fascinating biological advantages, including but not limited to excellent biocompatibility, biological degradation, high targetability and subsequent potent therapeutic efficacy. While some successes have been achieved in the nanoengineering of peptide-based architectures with defined dimensions and medical functions, enormous challenges remain about clinical nano-pharmaceutics of peptides, especially those modulating intracellular protein-protein interactions (PPIs). Methods: We developed a general method to translate intracellular-PPI-targeted peptides into a bioavailable peptide-auric spheroidal nanohybrid (SNH), for which polymeric peptide-Auric precursors [Au1+-S-peptide]n are in-situ reduced on the surface of gold nanoseeds via a simple and mild reaction. As proofs of concept, three cytomembrane-impenetrable peptides with different physicochemical properties were successfully engineered into stable and tumor-specific SNH respectively. Results: To highlight the advantage of SNH, PMI, a hydrophobic and enzyme-intolerant peptide capable of p53 restoration, was selected to challenge the power of SNH in a colon tumor xenografts model. PMI-Au SNH in vivo suppressed tumor growth potently after three administrations: intravenous injection, intraperitoneal injection and gastric perfusion, and maintained a favorable therapeutic safety. Conclusion: This therapeutically feasible strategy of peptide nanoengineering will allow us to fabricate a series of nanomedicines to modulate carcinogenic PPIs that hide and multiply inside cells, and in all likelihood reinvigorate the development of peptide drug against wide varieties of human diseases.

Bioinformatic and biochemical findings disclosed anti-hepatic steatosis mechanism of calycosin

As revealed in previous reports, calycosin is a functional flavonoid characterized with identified pharmacological activities. Most of evidences are used to demonstrate the anti-cancer benefits of calycosin, however, the existing study of anti-fatty liver medicated by calycosin is limitedly reported. Recently, an emerging avenue based on network pharmacology may contribute to excavate the biological targets and molecular mechanisms of calycosin for anti-fatty liver. In confirmatory experiments, the human and animal studies were subjected to verify some of bioinformatic results. Accordingly, bioinformatic data based on network pharmacology suggested that discoverable biotargets of calycosin for anti-fatty liver were aldehyde dehydrogenase (ALDH2), Niemann pick C1 (NPC1), high mobility group protein 1 (HMGB1), bilirubin UDP glucuronosyltransferase 1 (UGT1A1), mitogen-activated protein kinase 3 (MAPK3), epidermal growth factor receptor (EGFR), hydroxytryptamine receptor 2 (HTR2), migration inhibitory factor (MIF), cytochrome P450, family 19A1 (CYP19A1). Furthermore, all significant biological characteristics and mechanisms of to treat fatty liver were revealed in several. In human findings, the blood tests showed changed glucose and lipid contents, elevated insulin resistance and inflammatory stress. And fatty liver sections from patients resulted in negative expressions of ALDH2, NPC1, and positive HMGB1 expression. In a study in vivo, calycosin-treated high fat diet (HFD)-fed mice exhibited reduced liver weights, decreased fasting serum glucose and insulin, liver functional transaminases, blood lipids, metabolic enzymes, and inflammatory cytokines. And the data in gene tests displayed up-regulations of ALDH2, NPC1 mRNAs, and down-regulation of HMGB1 mRNA in calycosin-treated liver samples. Together, the current bioinformatic data demonstrate biological targets, functions and mechanisms of calycosin for anti-fatty liver. Interestingly, these bioinformatic findings can be partially verified with clinical and animal samples.

Understanding Protein Networks Using Vester's Sensitivity Model

Magnesium-based biomaterials belong to the third generation of biomaterials that are also bioactive. These smart materials combine bioactivity and biodegradability, and elicit specific cellular responses at the molecular level. In fact, osteoinductive properties have been observed in mesenchymal stem cells in the presence of Magnesium. The mechanistic understanding of the physiological effects however, remains a difficult task as Mg is involved in a multitude of biological reactions. The study of protein interactions may shed light on the molecular processes in Mg-stimulated cells, therefore, suitable data mining tools are required to analyze the large amount data generated via proteomics. Protein compositions over time between two conditions (human mesenchymal stem cells cultured with and without Mg degradation products) were analyzed using Vester's Sensitivity Model. Proteins whose dynamics significantly change from one setup to the other were classified into four categories: passive, active, critical, and buffering according to their regulatory activity. In this work, we demonstrated the use of Vester's Sensitivity Model as an appropriate data mining tool. Protein network analyses highlighted the primary role of Mg-based implant degradation on cell metabolism without deleterious effect on cell viability. Furthermore, key proteins involved in calcium-dependant cellular activities were emphasized leading to further studies.

Drug mechanism-of-action discovery through the integration of pharmacological and CRISPR screens

Low success rates during drug development are due, in part, to the difficulty of defining drug mechanism-of-action and molecular markers of therapeutic activity. Here, we integrated 199,219 drug sensitivity measurements for 397 unique anti-cancer drugs with genome-wide CRISPR loss-of-function screens in 484 cell lines to systematically investigate cellular drug mechanism-of-action. We observed an enrichment for positive associations between the profile of drug sensitivity and knockout of a drug's nominal target, and by leveraging protein-protein networks, we identified pathways underpinning drug sensitivity. This revealed an unappreciated positive association between mitochondrial E3 ubiquitin-protein ligase MARCH5 dependency and sensitivity to MCL1 inhibitors in breast cancer cell lines. We also estimated drug on-target and off-target activity, informing on specificity, potency and toxicity. Linking drug and gene dependency together with genomic data sets uncovered contexts in which molecular networks when perturbed mediate cancer cell loss-of-fitness and thereby provide independent and orthogonal evidence of biomarkers for drug development. This study illustrates how integrating cell line drug sensitivity with CRISPR loss-of-function screens can elucidate mechanism-of-action to advance drug development.

Time-series proteomic study of the response of HK-2 cells to hyperglycemic, hypoxic diabetic-like milieu

During diabetes, renal proximal tubular cells (PTC) are exposed to a combination of high glucose and hypoxic conditions, which plays a relevant role in the development of diabetic kidney disease (DKD). In this work, a time-series proteomic study was performed to analyse the effect of a diabetic-like microenvironment induced changes on HK-2 cells, a human cell line derived from normal proximal tubular epithelial cells. Cells simultaneously exposed to high glucose (25 mM) and hypoxia (1% O₂) were compared to cells in control conditions for up to 48 h. Diabetic conditions increased the percentage of death cells after 24 and 48 h, but no differences in the protein/cell ratio were found. The relative protein quantification using dimethyl-labeling and UHPLC-MS/MS analysis allowed the identification of 317, 296 and 259 proteins at 5, 24 and 48 h, respectively. The combination of statistical and time expression profile analyses indicated an increased expression of proteins involved in glycolysis, and a decrease of cytoskeletal-related proteins. The exposure of HK-2 cells to high glucose and hypoxia reproduces some of the effects of diabetes on PTC and, with the limitations inherent to in vitro studies, propose new mechanisms and targets to be considered in the management of DKD.

Phenotypic Screening of Chemical Libraries Enriched by Molecular Docking to Multiple Targets Selected from Glioblastoma Genomic Data

Like most solid tumors, glioblastoma multiforme (GBM) harbors multiple overexpressed and mutated genes that affect several signaling pathways. Suppressing tumor growth of solid tumors like GBM without toxicity may be achieved by small molecules that selectively modulate a collection of targets across different signaling pathways, also known as selective polypharmacology. Phenotypic screening can be an effective method to uncover such compounds, but the lack of approaches to create focused libraries tailored to tumor targets has limited its impact. Here, we create rational libraries for phenotypic screening by structure-based molecular docking chemical libraries to GBM-specific targets identified using the tumor's RNA sequence and mutation data along with cellular protein-protein interaction data. Screening this enriched library of 47 candidates led to several active compounds, including 1 (IPR-2025), which (i) inhibited cell viability of low-passage patient-derived GBM spheroids with single-digit micromolar IC50 values that are substantially better than standard-of-care temozolomide, (ii) blocked tube-formation of endothelial cells in Matrigel with submicromolar IC50 values, and (iii) had no effect on primary hematopoietic CD34+ progenitor spheroids or astrocyte cell viability. RNA sequencing provided the potential mechanism of action for 1, and mass spectrometry-based thermal proteome profiling confirmed that the compound engages multiple targets. The ability of 1 to inhibit GBM phenotypes without affecting normal cell viability suggests that our screening approach may hold promise for generating lead compounds with selective polypharmacology for the development of treatments of incurable diseases like GBM.

The Proteins of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS CoV-2 or n-COV19), the Cause of COVID-19

The devastating effects of the recent global pandemic (termed COVID-19 for "coronavirus disease 2019") caused by the severe acute respiratory syndrome coronavirus-2 (SARS CoV-2) are paramount with new cases and deaths growing at an exponential rate. In order to provide a better understanding of SARS CoV-2, this article will review the proteins found in the SARS CoV-2 that caused this global pandemic.

Identification of inhibitors of Bcl-2 family protein-protein interaction by combining the BRET screening platform with virtual screening

Bcl-2 family proteins play key roles in tumor initiation, progression, and resistance to therapy. Therefore, the protein-protein interactions (PPIs) between the pro-survival proteins, B-cell lymphoma (Bcl)-2 and Bcl-xL, and the pro-apoptotic proteins, Bax and Bak, could be attractive therapeutic targets for anti-cancer drug discovery. Here, we found new small molecules, BIP-A1001 and BIP-A2001 that modulated Bak/Bax and Bcl-xL interactions by combining the Nanoluc/YFP-based bioluminescence resonance energy transfer (BRET) assay with structure based virtual screening. In addition, we chose compounds with similar structures to BIP-A1001 and BIP-A2001 and tested their inhibitory effects using the BRET assay as a dose-response function. The results indicated that identifying compounds that inhibit interactions between Bak/Bax and Bcl-xL could be a promising approach to enhance cancer therapy.

Naked mole-rat very-high-molecular-mass hyaluronan exhibits superior cytoprotective properties

Naked mole-rat (NMR), the longest-living rodent, produces very-high-molecular-mass hyaluronan (vHMM-HA), compared to other mammalian species. However, it is unclear if exceptional polymer length of vHMM-HA is important for longevity. Here, we show that vHMM-HA (>6.1 MDa) has superior cytoprotective properties compared to the shorter HMM-HA. It protects not only NMR cells, but also mouse and human cells from stress-induced cell-cycle arrest and cell death in a polymer length-dependent manner. The cytoprotective effect is dependent on the major HA-receptor, CD44. We find that vHMM-HA suppresses CD44 protein-protein interactions, whereas HMM-HA promotes them. As a result, vHMM-HA and HMM-HA induce opposing effects on the expression of CD44-dependent genes, which are associated with the p53 pathway. Concomitantly, vHMM-HA partially attenuates p53 and protects cells from stress in a p53-dependent manner. Our results implicate vHMM-HA in anti-aging mechanisms and suggest the potential applications of vHMM-HA for enhancing cellular stress resistance.

Epigallocatechin gallate inhibits dimethylhydrazine-induced colorectal cancer in rats

BACKGROUND

Epigallocatechin gallate (EGCG) is a polyhydroxy phenolic compound extracted from tea and its antitumor effect has received widespread attention. We explored the inhibitory effect of EGCG on dimethylhydrazine (DMH)-induced colorectal cancer (CRC) using a rat model, predicted the interaction between EGCG and CRC target genes using a database, and explained the EGCG associated target pathways and mechanisms in CRC.

AIM

To understand the inhibitory mechanisms of EGCG on CRC cell proliferation and identify its pharmacological targets by network pharmacology analysis.

METHODS

DMH (40 mg/kg, s.c., twice weekly for eight weeks) was used to induce CRC in rats. After model establishment, the rats were administered with EGCG (50, 100, or 200 mg/kg, p.o., once daily for eight weeks) and killed 12 and 20 wk after the start of the experiment. Formation of aberrant crypt foci and tumor was studied by histological analysis. Using network pharmacology analysis, candidate and collective targets of EGCG and CRC were identified, and Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes analyses were used to predict the pathways altered by EGCG.

RESULTS

At week 12, high-dose EGCG treatment significantly reduced the tumor formation rate, total number of tumors, cancerous and non-cancerous tumors, tumor volume, ascites formation, and aberrant crypt foci count. At week 20, all three doses of EGCG were effective. Seventy-eight collective targets of EGCG and CRC were identified, of which 28 genes were dysregulated in CRC. Kyoto Encyclopedia of Genes and Genomes and GO analyses showed that the dysregulated genes were enriched in hsa05210 (CRC), hsa04115 (p53 signaling pathway), and hsa04151 (PI3K-Akt signaling pathway), GO:0043124 (negative regulation of I-kappaB kinase/NF-kappaB signaling pathway), GO:0043409 (negative regulation of mitogen-activated protein kinase cascade), and GO:2001244 (positive regulation of intrinsic apoptotic signaling pathway) respectively.

CONCLUSION

EGCG inhibits the formation of DMH-induced CRC by regulating key pathways involved in tumorigenesis.

SL2MF: Predicting Synthetic Lethality in Human Cancers via Logistic Matrix Factorization

Synthetic lethality (SL) is a promising concept for novel discovery of anti-cancer drug targets. However, wet-lab experiments for detecting SLs are faced with various challenges, such as high cost, low consistency across platforms, or cell lines. Therefore, computational prediction methods are needed to address these issues. This paper proposes a novel SL prediction method, named SL² MF, which employs logistic matrix factorization to learn latent representations of genes from the observed SL data. The probability that two genes are likely to form SL is modeled by the linear combination of gene latent vectors. As known SL pairs are more trustworthy than unknown pairs, we design importance weighting schemes to assign higher importance weights for known SL pairs and lower importance weights for unknown pairs in SL² MF. Moreover, we also incorporate biological knowledge about genes from protein-protein interaction (PPI) data and Gene Ontology (GO). In particular, we calculate the similarity between genes based on their GO annotations and topological properties in the PPI network. Extensive experiments on the SL interaction data from SynLethDB database have been conducted to demonstrate the effectiveness of SL² MF.

Nanoparticles: Synthesis, Morphophysiological Effects, and Proteomic Responses of Crop Plants

Plant cells are frequently challenged with a wide range of adverse environmental conditions that restrict plant growth and limit the productivity of agricultural crops. Rapid development of nanotechnology and unsystematic discharge of metal containing nanoparticles (NPs) into the environment pose a serious threat to the ecological receptors including plants. Engineered nanoparticles are synthesized by physical, chemical, biological, or hybrid methods. In addition, volcanic eruption, mechanical grinding of earthquake-generating faults in Earth's crust, ocean spray, and ultrafine cosmic dust are the natural source of NPs in the atmosphere. Untying the nature of plant interactions with NPs is fundamental for assessing their uptake and distribution, as well as evaluating phytotoxicity. Modern mass spectrometry-based proteomic techniques allow precise identification of low abundant proteins, protein-protein interactions, and in-depth analyses of cellular signaling networks. The present review highlights current understanding of plant responses to NPs exploiting high-throughput proteomics techniques. Synthesis of NPs, their morphophysiological effects on crops, and applications of proteomic techniques, are discussed in details to comprehend the underlying mechanism of NPs stress acclimation.

Gamma-Aminobutyric Acid Increases Erythropoietin by Activation of Citrate Cycle and Stimulation of Hypoxia-Inducible Factors Expression in Rats

Erythropoietin (EPO) is the primary regulator of erythropoiesis in the mammalian fetus and adult. Deficiency of EPO induces anemia. In this study, we investigated the effect of gamma-aminobutyric acid (GABA) on serum EPO levels and erythropoiesis in rats. Expression levels of Epo-related genes were measured by quantitative real-time PCR (qPCR) and expression of Epo and Epo receptor (Epor) proteins were measured by immunohistochemistry. The gene and protein expression profiles of kidney tissue in GABA-treated rats were evaluated by ribonucleic acid (RNA) sequencing and two-dimensional electrophoresis (2-DE), respectively. GABA significantly increased serum EPO levels and expression levels of Epo and Epor. GABA increased expression levels of hypoxia-inducible factor (Hif)-1 and Hif-2. Seven proteins with expression levels showing >2-fold change were identified by 2-DE followed by MALDI-TOF MS in GABA-treated rat kidney. The top KEGG pathway from the identified proteins was the tricarboxylic acid cycle, and nicotinamide adenine dinucleotide (NADH) dehydrogenase, succinate dehydrogenase, and isocitrate dehydrogenase were identified as key proteins. GABA treatment significantly increased ATP levels and NADH dehydrogenase activity in a dose-dependent manner. In conclusion, GABA shows a new physiological role in EPO production, and it can thus can contribute to the prevention of anemia when used alone or in combination with other anemia treating drugs.

Network Systems Pharmacology-Based Mechanism Study on the Beneficial Effects of Vitamin D against Psychosis in Alzheimer's Disease

Alzheimer's disease (AD) is a chronic neurodegenerative disease with significant financial costs and negative impacts on quality of life. Psychotic symptoms, i.e., the presence of delusions and/or hallucinations, is a frequent complication of AD. About 50% of AD patients will develop psychotic symptoms (AD with Psychosis, or AD + P) and these patients will experience an even more rapid cognitive decline than AD patients without psychosis (AD-P). In a previous analysis on medication records of 776 AD patients, we had shown that use of Vitamin D was associated with delayed time to psychosis in AD patients and Vitamin D was used more by AD-P than AD + P patients. To explore the potential molecular mechanism behind our findings, we applied systems pharmacology approaches to investigate the crosstalk between AD and psychosis. Specifically, we built protein-protein interaction (PPI) networks with proteins encoded by AD- and psychosis-related genes and Vitamin D-perturbed genes. Using network analysis we identified several high-impact genes, including NOTCH4, COMT, CACNA1C and DRD3 which are related to calcium homeostasis. The new findings highlight the key role of calcium-related signaling pathways in AD + P development and may provide a new direction and facilitate hypothesis generation for future drug development.

β-Sitosterol Reverses Multidrug Resistance via BCRP Suppression by Inhibiting the p53-MDM2 Interaction in Colorectal Cancer

Phytosterols are widely present in vegetable oils, nuts, cereal products, fruits, and berries. Phytosterol-induced treatment sensitivity has recently shed light on alleviating multidrug resistance in cancer therapy. Here, we demonstrated that β-sitosterol, the most common dietary phytosterol, recovers oxaliplatin (OXA) sensitivity in drug-resistant colorectal cancer (CRC) cells by inhibiting breast cancer resistance protein (BCRP) expression. We further showed evidence that β-sitosterol could activate p53 by disrupting the p53-MDM2 interaction, leading to an increase in p53 translocation to the nucleus and silencing the nuclear factor-κB (NF-κB) pathway, which is necessary for BCRP expression. Finally, we suggested that the combination of OXA and β-sitosterol has a synergistic tumor suppression effect in vivo using a xenograft mouse model. These results revealed that β-sitosterol is able to mediate the p53/NF-κB/BCRP signaling axis to regulate the response of CRC to chemotherapy. The combined application of β-sitosterol and OXA can be a potential way to improve CRC treatment.

Personalized therapy design for systemic lupus erythematosus based on the analysis of protein-protein interaction networks

We analyzed protein expression data for Lupus patients, which have been obtained from publicly available databases. A combination of systems biology and statistical thermodynamics approaches was used to extract topological properties of the associated protein-protein interaction networks for each of the 291 patients whose samples were used to provide the molecular data. We have concluded that among the many proteins that appear to play critical roles in this pathology, most of them are either ribosomal proteins, ubiquitination pathway proteins or heat shock proteins. We propose some of the proteins identified in this study to be considered for drug targeting.

Identification of the Molecular Mechanisms of Peimine in the Treatment of Cough Using Computational Target Fishing

Peimine (also known as verticine) is the major bioactive and characterized compound of Fritillariae Thunbergii Bulbus, a traditional Chinese medicine that is most frequently used to relieve a cough. Nevertheless, its molecular targets and mechanisms of action for cough are still not clear. In the present study, potential targets of peimine for cough were identified using computational target fishing combined with manual database mining. In addition, protein-protein interaction (PPI), gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using, GeneMANIA and Database for Annotation, Visualization and Integrated Discovery (DAVID) databases respectively. Finally, an interaction network of drug-targets-pathways was constructed using Cytoscape. The results identified 23 potential targets of peimine associated with cough, and suggested that MAPK1, AKT1 and PPKCB may be important targets of pemine for the treatment of cough. The functional annotations of protein targets were related to the regulation of immunological and neurological function through specific biological processes and related pathways. A visual representation of the multiple targets and pathways that form a network underlying the systematic actions of peimine was generated. In summary, peimine is predicted to exert its systemic pharmacological effects on cough by targeting a network composed of multiple proteins and pathways.

Enhanced cardiomyocyte reactive oxygen species signaling promotes ibrutinib-induced atrial fibrillation

Atrial fibrillation (AF) occurs in up to 11% of cancer patients treated with ibrutinib. The pathophysiology of ibrutinib promoted AF is complicated, as there are multiple interactions involved; the detailed molecular mechanisms underlying this are still unclear. Here, we aimed to determine the electrophysiological and molecular mechanisms of burst-pacing-induced AF in ibrutinib-treated mice. The results indicated differentially expressed proteins in ibrutinib-treated mice, identified through proteomic analysis, were found to play a role in oxidative stress-related pathways. Finally, treatment with an inhibitor of NADPH oxidase (NOX) prevented and reversed AF development in ibrutinib-treated mice. It was showed that the related protein expression of reactive oxygen species (ROS) in the ibrutinib group was significantly increased, including NOX2, NOX4, p22-phox, XO and TGF-β protein expression. It was interesting that ibrutinib group also significantly increased the expression of ox-CaMKII, p-CaMKII (Thr-286) and p-RyR2 (Ser2814), causing enhanced abnormal sarcoplasmic reticulum (SR) Ca²⁺ release and mitochondrial structures, as well as atrial fibrosis and atrial hypertrophy in ibrutinib-treated mice, and apocynin reduced the expression of these proteins. Ibrutinib-treated mice were also more likely to develop AF, and AF occurred over longer periods. In conclusion, our study has established a pathophysiological role for ROS signaling in atrial cardiomyocytes, and it may be that ox-CaMKII and p-CaMKII (Thr-286) are activated by ROS to increase AF susceptibility following ibrutinib treatment. We have also identified the inhibition of NOX as a potential novel AF therapy approach.

Prediction of triptolide targets in rheumatoid arthritis using network pharmacology and molecular docking

Network pharmacology is a novel approach that uses bioinformatics to predict and identify multiple drug targets and interactions in disease. Here, we used network pharmacology to investigate the mechanism by which triptolide acts in rheumatoid arthritis (RA). We first searched public databases for genes and proteins known to be associated with RA, as well as those predicted to be targets of triptolide, and then used Ingenuity Pathway Analysis (IPA) to identify enriched gene pathways and networks. Networks and pathways that overlapped between RA-associated proteins and triptolide target proteins were then used to predict candidate protein targets of triptolide in RA. The following proteins were found to occur in both RA-associated networks and triptolide target networks: CD274, RELA, MCL1, MAPK8, CXCL8, STAT1, STAT3, c-JUN, JNK, c-Fos, NF-κB, and TNF-α. Docking studies suggested that triptolide can fit in the binding pocket of the six top candidate triptolide target proteins (CD274, RELA, MCL1, MAPK8, CXCL8 and STAT1). The overlapping pathways were activation of Th1 and Th2 cells, macrophages, fibroblasts and endothelial cells in RA, while the overlapping networks were involved in cellular movement, hematological system development and function, immune cell trafficking, cell-to-cell signaling and interaction, inflammatory response, cellular function and maintenance, and cell death and survival. These results show that network pharmacology can be used to generate hypotheses about how triptolide exerts therapeutic effects in RA. Network pharmacology may be a useful method for characterizing multi-target drugs in complex diseases.

Investigating the mechanism of ShuFeng JieDu capsule for the treatment of novel Coronavirus pneumonia (COVID-19) based on network pharmacology

ShuFeng JieDu capsule (SFJDC), a traditional Chinese medicine, has been recommended for the treatment of COVID-19 infections. However, the pharmacological mechanism of SFJDC still remains vague to date. The active ingredients and their target genes of SFJDC were collected from TCMSP. COVID-19 is a type of Novel Coronavirus Pneumonia (NCP). NCP-related target genes were collected from GeneCards database. The ingredients-targets network of SFJDC and PPI networks were constructed. The candidate genes were screened by Venn diagram package for enrichment analysis. The gene-pathway network was structured to obtain key target genes. In total, 124 active ingredients, 120 target genes of SFJDC and 251 NCP-related target genes were collected. The functional annotations cluster 1 of 23 candidate genes (CGs) were related to lung and Virus infection. RELA, MAPK1, MAPK14, CASP3, CASP8 and IL6 were the key target genes. The results suggested that SFJDC cloud be treated COVID-19 by multi-compounds and multi-pathways, and this study showed that the mechanism of traditional Chinese medicine (TCM) in the treatment of disease from the overall perspective.