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Published on January 31, 2023
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Network pharmacology study of the mechanism underlying the therapeutic effect of Zhujing pill and its main component oleanolic acid against diabetic retinopathy.

Authors: Cui J, Shi E, Wang Y, Liu T

Abstract: Diabetic retinopathy (DR) is the leading cause of blindness in the working population worldwide, with few effective drugs available for its treatment in the early stages. The Zhujing pill (ZJP) is well-established to enhance the early symptoms of DR, but the mechanism underlying its therapeutic effect remains unclear. In the present study, we used systems biology and multidirectional pharmacology to screen the main active ingredients of ZJP and retrieved DrugBank and Genecards databases to obtain 'drug-disease' common targets. Using bioinformatics analysis, we obtained the core targets, and potential mechanisms of action of ZJP and its main components for the treatment of DR. Molecular docking was used to predict the binding sites and the binding affinity of the main active ingredients to the core targets. The predicted mechanism was verified in animal experiments. We found that the main active ingredient of ZJP was oleanolic acid, and 63 common 'drug-disease' targets were identified. Topological analysis and cluster analysis based on the protein-protein interaction network of the Metascape database screened the core targets as PRKCA, etc. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that these core targets were significantly enriched in the pro-angiogenic pathway of the VEGF signaling pathway. Molecular docking and surface plasmon resonance revealed that ZJP and its main active component, oleanolic acid had the highest binding affinity with PKC-alpha, the core target of the VEGF signaling pathway. Animal experiments validated that ZJP and oleanolic acid could improve DR.
Published in January 2023
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An integrated LSTM-HeteroRGNN model for interpretable opioid overdose risk prediction.

Authors: Dong X, Wong R, Lyu W, Abell-Hart K, Deng J, Liu Y, Hajagos JG, Rosenthal RN, Chen C, Wang F

Abstract: Opioid overdose (OD) has become a leading cause of accidental death in the United States, and overdose deaths reached a record high during the COVID-19 pandemic. Combating the opioid crisis requires targeting high-need populations by identifying individuals at risk of OD. While deep learning emerges as a powerful method for building predictive models using large scale electronic health records (EHR), it is challenged by the complex intrinsic relationships among EHR data. Further, its utility is limited by the lack of clinically meaningful explainability, which is necessary for making informed clinical or policy decisions using such models. In this paper, we present LIGHTED, an integrated deep learning model combining long short term memory (LSTM) and graph neural networks (GNN) to predict patients' OD risk. The LIGHTED model can incorporate the temporal effects of disease progression and the knowledge learned from interactions among clinical features. We evaluated the model using Cerner's Health Facts database with over 5 million patients. Our experiments demonstrated that the model outperforms traditional machine learning methods and other deep learning models. We also proposed a novel interpretability method by exploiting embeddings provided by GNNs to cluster patients and EHR features respectively, and conducted qualitative feature cluster analysis for clinical interpretations. Our study shows that LIGHTED can take advantage of longitudinal EHR data and the intrinsic graph structure of EHRs among patients to provide effective and interpretable OD risk predictions that may potentially improve clinical decision support.
Published in January 2023
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Identification of PIK3CG as a hub in septic myocardial injury using network pharmacology and weighted gene co-expression network analysis.

Authors: Liu Q, Dong Y, Escames G, Wu X, Ren J, Yang W, Zhang S, Zhu Y, Tian Y, Acuna-Castroviejo D, Yang Y

Abstract: Sepsis causes multiple organ injuries, among which the heart is one most severely damaged organ. Melatonin (MEL) alleviates septic myocardial injury, although a systematic and comprehensive approach is still lacking to understand the precise protective machinery of MEL. This study aimed to examine the underlying mechanisms of MEL on improvement of septic myocardial injury at a systematic level. This study integrated three analytic modalities including database investigations, RNA-seq analysis, and weighted gene co-expression network analysis (WCGNA), in order to acquire a set of genes associated with the pathogenesis of sepsis. The Drugbank database was employed to predict genes that may serve as pharmacological targets for MEL-elicited benefits, if any. A pharmacological protein-protein interaction network was subsequently constructed, and 66 hub genes were captured which were enriched in a variety of immune response pathways. Notably, PIK3CG, one of the hub genes, displayed high topological characteristic values, strongly suggesting its promise as a novel target for MEL-evoked treatment of septic myocardial injury. Importantly, molecular docking simulation experiments as well as in vitro and in vivo studies supported an essential role for PIK3CG in MEL-elicited effect on septic myocardial injury. This study systematically clarified the mechanisms of MEL intervention in septic myocardial injury involved multiple targets and multiple pathways. Moreover, PIK3CG-governed signaling cascade plays an important role in the etiology of sepsis and septic myocardial injury. Findings from our study provide valuable information on novel intervention targets for the management of septic myocardial injury. More importantly, this study has indicated the utility of combining a series of techniques for disease target discovery and exploration of possible drug targets, which should shed some light on elucidation of experimental and clinical drug action mechanisms systematically.
Published on January 31, 2023
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Design, Synthesis, Antifungal Activity, and Molecular Docking of Streptochlorin Derivatives Containing the Nitrile Group.

Authors: Liu JR, Gao Y, Jin B, Guo D, Deng F, Bian Q, Zhang HF, Han XY, Ali AS, Zhang MZ, Zhang WH, Gu YC

Abstract: Based on the structures of natural products streptochlorin and pimprinine derived from marine or soil microorganisms, a series of streptochlorin derivatives containing the nitrile group were designed and synthesized through acylation and oxidative annulation. Evaluation for antifungal activity showed that compound 3a could be regarded as the most promising candidate-it demonstrated over 85% growth inhibition against Botrytis cinerea, Gibberella zeae, and Colletotrichum lagenarium, as well as a broad antifungal spectrum in primary screening at the concentration of 50 mug/mL. The SAR study revealed that non-substituent or alkyl substituent at the 2-position of oxazole ring were favorable for antifungal activity, while aryl and monosubstituted aryl were detrimental to activity. Molecular docking models indicated that 3a formed hydrogen bonds and hydrophobic interactions with Leucyl-tRNA Synthetase, offering a perspective for the possible mechanism of action for antifungal activity of the target compounds.
Published in January 2023
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Zhijing powder manages blood pressure by regulating PI3K/AKT signal pathway in hypertensive rats.

Authors: Wang Y, Zhang P, Li H, Chen P, Zhang X, Wang B, Zhang M

Abstract: BACKGROUND: Zhijing Powder (ZJP) is a traditional Chinese medicine containing two kinds of Chinese medicine. Those studies analyze the molecular mechanism of ZJP in treating hypertension through network pharmacology, combined with animal experiments. METHODS: First, the effective ingredients and potential targets of the drug were obtained through drug databases, while the targets of disease obtained through disease target databases. The potential targets, cellular bioanalysis and signaling pathways were found in some platforms by analyzing collected targets. Further experiments were conducted to verify the effect and mechanism of drugs on cold and high salt in an induced-hypertension rat model. RESULTS: There are 17 effective components of centipedes and 10 of scorpions, with 464 drug targets obtained after screening. A total of 1263 hypertension targets were obtained after screening and integration, resulting in a protein-protein interaction network (PPI) with 145 points and 1310 edges. Gene ontology (GO) analysis shows that blood circulation regulation and activation of G protein-coupled receptors are mainly biological processes. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis shows that neuroactive ligand-receptor interaction, calcium signaling pathways, PI3K-AKT signaling pathways are the most abundant gene-enriched pathway. Animal experiments indicated that ZJP can reduce blood pressure (BP), affect expression of the PI3K-AKT signaling pathway, and improve oxidative stress in the body. CONCLUSION: ZJP ameliorates oxidative stress and reduces BP in hypertensive rats caused by cold stimuli and high salt, revealing its effect on the expression of the PI3K/AKT signaling pathway in the rat aorta.
Published in January 2023
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Using reported pathogenic variants to identify therapeutic opportunities for genetic diseases.

Authors: Ressler AK, Goldstein DB

Abstract: PURPOSE: Drug development strategies for genetic diseases depend critically on accurate knowledge of how pathogenic variants cause disease. For some well-studied genes, the direct effects of pathogenic variants are well documented as loss-of-function, gain-of-function or hypermorphic, or a combination of the two. For many genes, however, even the direction of effect of variants remains unclear. Classification of Mendelian disease genes in terms of whether pathogenic variants are loss- or gain-of-function would directly inform drug development strategies. METHODS: We leveraged the recent dramatic increase in reported pathogenic variants to provide a novel approach to inferring the direction of effect of pathogenic variants. Specifically, we quantify the ratio of reported pathogenic variants that are missense compared to loss-of-function. RESULTS: We first show that for many genes that cause dominant Mendelian disease, the ratio of reported pathogenic missense variants is diagnostic of whether the gene causes disease through loss- or gain-of-function, or a combination. Second, we identify a set of genes that appear to cause disease largely or entirely through gain-of-function or hypermorphic pathogenic variants. CONCLUSIONS: We suggest a set of 16 genes suitable for drug developmental efforts utilizing direct inhibition.
Published on January 29, 2023
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In Silico Targeting of Fascin Protein for Cancer Therapy: Benchmarking, Virtual Screening and Molecular Dynamics Approaches.

Authors: Hassan HHA, Ismail MI, Abourehab MAS, Boeckler FM, Ibrahim TM, Arafa RK

Abstract: Fascin is an actin-bundling protein overexpressed in various invasive metastatic carcinomas through promoting cell migration and invasion. Therefore, blocking Fascin binding sites is considered a vital target for antimetastatic drugs. This inspired us to find new Fascin binding site blockers. First, we built an active compound set by collecting reported small molecules binding to Fascin's binding site 2. Consequently, a high-quality decoys set was generated employing DEKOIS 2.0 protocol to be applied in conducting the benchmarking analysis against the selected Fascin structures. Four docking programs, MOE, AutoDock Vina, VinaXB, and PLANTS were evaluated in the benchmarking study. All tools indicated better-than-random performance reflected by their pROC-AUC values against the Fascin crystal structure (PDB: ID 6I18). Interestingly, PLANTS exhibited the best screening performance and recognized potent actives at early enrichment. Accordingly, PLANTS was utilized in the prospective virtual screening effort for repurposing FDA-approved drugs (DrugBank database) and natural products (NANPDB). Further assessment via molecular dynamics simulations for 100 ns endorsed Remdesivir (DrugBank) and NANPDB3 (NANPDB) as potential binders to Fascin binding site 2. In conclusion, this study delivers a model for implementing a customized DEKOIS 2.0 benchmark set to enhance the VS success rate against new potential targets for cancer therapies.
Published on January 29, 2023
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Suppressing Hepatic UGT1A1 Increases Plasma Bilirubin, Lowers Plasma Urobilin, Reorganizes Kinase Signaling Pathways and Lipid Species and Improves Fatty Liver Disease.

Authors: Bates EA, Kipp ZA, Martinez GJ, Badmus OO, Soundarapandian MM, Foster D, Xu M, Creeden JF, Greer JR, Morris AJ, Stec DE, Hinds TD Jr

Abstract: Several population studies have observed lower serum bilirubin levels in patients with non-alcoholic fatty liver disease (NAFLD). Yet, treatments to target this metabolic phenotype have not been explored. Therefore, we designed an N-Acetylgalactosamine (GalNAc) labeled RNAi to target the enzyme that clears bilirubin from the blood, the UGT1A1 glucuronyl enzyme (GNUR). In this study, male C57BL/6J mice were fed a high-fat diet (HFD, 60%) for 30 weeks to induce NAFLD and were treated subcutaneously with GNUR or sham (CTRL) once weekly for six weeks while continuing the HFD. The results show that GNUR treatments significantly raised plasma bilirubin levels and reduced plasma levels of the bilirubin catabolized product, urobilin. We show that GNUR decreased liver fat content and ceramide production via lipidomics and lowered fasting blood glucose and insulin levels. We performed extensive kinase activity analyses using our PamGene PamStation kinome technology and found a reorganization of the kinase pathways and a significant decrease in inflammatory mediators with GNUR versus CTRL treatments. These results demonstrate that GNUR increases plasma bilirubin and reduces plasma urobilin, reducing NAFLD and inflammation and improving overall liver health. These data indicate that UGT1A1 antagonism might serve as a treatment for NAFLD and may improve obesity-associated comorbidities.
Published on January 28, 2023
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RHOA Therapeutic Targeting in Hematological Cancers.

Authors: Santos JC, Profitos-Peleja N, Sanchez-Vinces S, Roue G

Abstract: Primarily identified as an important regulator of cytoskeletal dynamics, the small GTPase Ras homolog gene family member A (RHOA) has been implicated in the transduction of signals regulating a broad range of cellular functions such as cell survival, migration, adhesion and proliferation. Deregulated activity of RHOA has been linked to the growth, progression and metastasis of various cancer types. Recent cancer genome-wide sequencing studies have unveiled both RHOA gain and loss-of-function mutations in primary leukemia/lymphoma, suggesting that this GTPase may exert tumor-promoting or tumor-suppressive functions depending on the cellular context. Based on these observations, RHOA signaling represents an attractive therapeutic target for the development of selective anticancer strategies. In this review, we will summarize the molecular mechanisms underlying RHOA GTPase functions in immune regulation and in the development of hematological neoplasms and will discuss the current strategies aimed at modulating RHOA functions in these diseases.
Published on January 26, 2023
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A Data-Driven Approach to Construct a Molecular Map of Trypanosoma cruzi to Identify Drugs and Vaccine Targets.

Authors: Nath SK, Pankajakshan P, Sharma T, Kumari P, Shinde S, Garg N, Mathur K, Arambam N, Harjani D, Raj M, Kwatra G, Venkatesh S, Choudhoury A, Bano S, Tayal P, Sharan M, Arora R, Strych U, Hotez PJ, Bottazzi ME, Rawal K

Abstract: Chagas disease (CD) is endemic in large parts of Central and South America, as well as in Texas and the southern regions of the United States. Successful parasites, such as the causative agent of CD, Trypanosoma cruzi have adapted to specific hosts during their phylogenesis. In this work, we have assembled an interactive network of the complex relations that occur between molecules within T. cruzi. An expert curation strategy was combined with a text-mining approach to screen 10,234 full-length research articles and over 200,000 abstracts relevant to T. cruzi. We obtained a scale-free network consisting of 1055 nodes and 874 edges, and composed of 838 proteins, 43 genes, 20 complexes, 9 RNAs, 36 simple molecules, 81 phenotypes, and 37 known pharmaceuticals. Further, we deployed an automated docking pipeline to conduct large-scale docking studies involving several thousand drugs and potential targets to identify network-based binding propensities. These experiments have revealed that the existing FDA-approved drugs benznidazole (Bz) and nifurtimox (Nf) show comparatively high binding energies to the T. cruzi network proteins (e.g., PIF1 helicase-like protein, trans-sialidase), when compared with control datasets consisting of proteins from other pathogens. We envisage this work to be of value to those interested in finding new vaccines for CD, as well as drugs against the T. cruzi parasite.