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Showing 1001 to 1004 of 5186 entries
Published on February 1, 2022
The nsp15 Nuclease as a Good Target to Combat SARS-CoV-2: Mechanism of Action and Its Inactivation with FDA-Approved Drugs.
Abstract: The pandemic caused by SARS-CoV-2 is not over yet, despite all the efforts from the scientific community. Vaccination is a crucial weapon to fight this virus; however, we still urge the development of antivirals to reduce the severity and progression of the COVID-19 disease. For that, a deep understanding of the mechanisms involved in viral replication is necessary. nsp15 is an endoribonuclease critical for the degradation of viral polyuridine sequences that activate host immune sensors. This enzyme is known as one of the major interferon antagonists from SARS-CoV-2. In this work, a biochemical characterization of SARS-CoV-2 nsp15 was performed. We saw that nsp15 is active as a hexamer, and zinc can block its activity. The role of conserved residues from SARS-CoV-2 nsp15 was investigated, and N164 was found to be important for protein hexamerization and to contribute to the specificity to degrade uridines. Several chemical groups that impact the activity of this ribonuclease were also identified. Additionally, FDA-approved drugs with the capacity to inhibit the in vitro activity of nsp15 are reported in this work. This study is of utmost importance by adding highly valuable information that can be used for the development and rational design of therapeutic strategies.
Published on February 1, 2022
Metabolic and Metabo-Clinical Signatures of Type 2 Diabetes, Obesity, Retinopathy, and Dyslipidemia.
Abstract: Macro- and microvascular complications of type 2 diabetes (T2D), obesity, and dyslipidemia share common metabolic pathways. In this study, using a total of 1,300 metabolites from 996 Qatari adults (57% with T2D) and 1,159 metabolites from an independent cohort of 2,618 individuals from the Qatar BioBank (11% with T2D), we identified 373 metabolites associated with T2D, obesity, retinopathy, dyslipidemia, and lipoprotein levels, 161 of which were novel. Novel metabolites included phospholipids, sphingolipids, lysolipids, fatty acids, dipeptides, and metabolites of the urea cycle and xanthine, steroid, and glutathione metabolism. The identified metabolites enrich pathways of oxidative stress, lipotoxicity, glucotoxicity, and proteolysis. Second, we identified 15 patterns we defined as "metabo-clinical signatures." These are clusters of patients with T2D who group together based on metabolite levels and reveal the same clustering in two or more clinical variables (obesity, LDL, HDL, triglycerides, and retinopathy). These signatures revealed metabolic pathways associated with different clinical patterns and identified patients with extreme (very high/low) clinical variables associated with extreme metabolite levels in specific pathways. Among our novel findings are the role of N-acetylmethionine in retinopathy in conjunction with dyslipidemia and the possible roles of N-acetylvaline and pyroglutamine in association with high cholesterol levels and kidney function.
Published in January 2022
Emerging technologies and their impact on regulatory science.
Abstract: There is an evolution and increasing need for the utilization of emerging cellular, molecular and in silico technologies and novel approaches for safety assessment of food, drugs, and personal care products. Convergence of these emerging technologies is also enabling rapid advances and approaches that may impact regulatory decisions and approvals. Although the development of emerging technologies may allow rapid advances in regulatory decision making, there is concern that these new technologies have not been thoroughly evaluated to determine if they are ready for regulatory application, singularly or in combinations. The magnitude of these combined technical advances may outpace the ability to assess fit for purpose and to allow routine application of these new methods for regulatory purposes. There is a need to develop strategies to evaluate the new technologies to determine which ones are ready for regulatory use. The opportunity to apply these potentially faster, more accurate, and cost-effective approaches remains an important goal to facilitate their incorporation into regulatory use. However, without a clear strategy to evaluate emerging technologies rapidly and appropriately, the value of these efforts may go unrecognized or may take longer. It is important for the regulatory science field to keep up with the research in these technically advanced areas and to understand the science behind these new approaches. The regulatory field must understand the critical quality attributes of these novel approaches and learn from each other's experience so that workforces can be trained to prepare for emerging global regulatory challenges. Moreover, it is essential that the regulatory community must work with the technology developers to harness collective capabilities towards developing a strategy for evaluation of these new and novel assessment tools.
Published in January 2022
Project-based learning course on metabolic network modelling in computational systems biology.
Abstract: Project-based learning (PBL) is a dynamic student-centred teaching method that encourages students to solve real-life problems while fostering engagement and critical thinking. Here, we report on a PBL course on metabolic network modelling that has been running for several years within the Master in Integrated Systems Biology (MISB) at the University of Luxembourg. This 2-week full-time block course comprises an introduction into the core concepts and methods of constraint-based modelling (CBM), applied to toy models and large-scale networks alongside the preparation of individual student projects in week 1 and, in week 2, the presentation and execution of these projects. We describe in detail the schedule and content of the course, exemplary student projects, and reflect on outcomes and lessons learned. PBL requires the full engagement of students and teachers and gives a rewarding teaching experience. The presented course can serve as a role model and inspiration for other similar courses.
Published in January 2022
De novo individualized disease modules reveal the synthetic penetrance of genes and inform personalized treatment regimens.
Abstract: Current understandings of individual disease etiology and therapeutics are limited despite great need. To fill the gap, we propose a novel computational pipeline that collects potent disease gene cooperative pathways to envision individualized disease etiology and therapies. Our algorithm constructs individualized disease modules de novo, which enables us to elucidate the importance of mutated genes in specific patients and to understand the synthetic penetrance of these genes across patients. We reveal that importance of the notorious cancer drivers TP53 and PIK3CA fluctuate widely across breast cancers and peak in tumors with distinct numbers of mutations and that rarely mutated genes such as XPO1 and PLEKHA1 have high disease module importance in specific individuals. Furthermore, individualized module disruption enables us to devise customized singular and combinatorial target therapies that were highly varied across patients, showing the need for precision therapeutics pipelines. As the first analysis of de novo individualized disease modules, we illustrate the power of individualized disease modules for precision medicine by providing deep novel insights on the activity of diseased genes in individuals.
Published in January 2022
The possible mechanism of Hippophae fructus oil applied in tympanic membrane repair identified based on network pharmacology and molecular docking.
Abstract: OBJECTIVE: This study aimed to explore the mechanisms of Hippophae fructus oil (HFO) in the treatment of tympanic membrane (TM) perforation through network pharmacology-based identification. METHODS: The compounds and related targets of HFO were extracted from the TCMSP database, and disease information was obtained from the OMIM, GeneCards, PharmGkb, TTD, and DrugBank databases. A Venn diagram was generated to show the common targets of HFO and TM, and GO and KEGG analyses were performed to explore the potential biological processes and signaling pathways. The PPI network and core gene subnetwork were constructed using the STRING database and Cytoscape software. A molecular docking analysis was also conducted to simulate the combination of compounds and gene proteins. RESULTS: A total of 33 compounds and their related targets were obtained from the TCMSP database. After screening the 393 TM-related targets, 21 compounds and 22 gene proteins were selected to establish the network diagram. GO and KEGG enrichment analyses revealed that HFO may promote TM healing by influencing cellular oxidative stress and related signaling pathways. A critical subnetwork was obtained by analyzing the PPI network with nine core genes: CASP3, MMP2, IL1B, TP53, EGFR, CXCL8, ESR1, PTGS2, and IL6. In addition, a molecular docking analysis revealed that quercetin strongly binds the core proteins. CONCLUSION: According to the analysis, HFO can be utilized to repair perforations by influencing cellular oxidative stress. Quercetin is one of the active compounds that potentially plays an important role in TM regeneration by influencing 17 gene proteins.
Published in January - December 2022
A network pharmacology approach to explore and validate the potential targets of ginsenoside on osteoporosis.
Abstract: Background: Osteoporosis (OP) is determined as a chronic systemic bone disorder to increase the susceptibility to fracture. Ginsenosides have been found the anti-osteoporotic activity of in vivo and in vitro. However, its mechanism remains unknown.Methods: The potential mechanism of ginsenosides in anti-osteoporotic activity was identified by using network phamacology analysis. The active compounds of ginsenosides and their targets associated to OP were retrieved from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, Drug Bank, Pharmmapper, and Cytoscape. The Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis target genes were performed in String, Phenopedia, DisGeNET database, and Metascape software. The protein to protein interaction were created by String database and Cytoscape software. The molecular docking was used to investigate the interactions between active coumpounds and potential targets by utilizing SwissDock tool, UCSF Chimera, and Pymol software. Results: A total of eight important active ingredients and 17 potential targets related to OP treatment were subjected to analyze. GO analysis showed the anti-osteoporosis targets of ginsenoside mainly play a role in the response to steroid hormone. KEGG enrichment analysis indicated that ginsenoside treats OP by osteoblast differentiation signal pathway. Lastly, the molecular docking outcomes indicated that ginsenoside rh2 had a good binding ability with four target proteins IL1B, TNF, IFNG, and NFKBIA. Conclusion: IL1B, TNF, IFNG, and NFKBIA are the most important targets and osteoblast differentiation is the most valuable signaling pathways in ginsenoside for the treatment of OP, which might be beneficial to elucidate the mechanism concerned to the action of ginsenoside and might supply a better understanding of its anti-OP effects.
Published in January 2022
RCSB Protein Data Bank: Celebrating 50 years of the PDB with new tools for understanding and visualizing biological macromolecules in 3D.
Abstract: The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), funded by the US National Science Foundation, National Institutes of Health, and Department of Energy, has served structural biologists and Protein Data Bank (PDB) data consumers worldwide since 1999. RCSB PDB, a founding member of the Worldwide Protein Data Bank (wwPDB) partnership, is the US data center for the global PDB archive housing biomolecular structure data. RCSB PDB is also responsible for the security of PDB data, as the wwPDB-designated Archive Keeper. Annually, RCSB PDB serves tens of thousands of three-dimensional (3D) macromolecular structure data depositors (using macromolecular crystallography, nuclear magnetic resonance spectroscopy, electron microscopy, and micro-electron diffraction) from all inhabited continents. RCSB PDB makes PDB data available from its research-focused RCSB.org web portal at no charge and without usage restrictions to millions of PDB data consumers working in every nation and territory worldwide. In addition, RCSB PDB operates an outreach and education PDB101.RCSB.org web portal that was used by more than 800,000 educators, students, and members of the public during calendar year 2020. This invited Tools Issue contribution describes (i) how the archive is growing and evolving as new experimental methods generate ever larger and more complex biomolecular structures; (ii) the importance of data standards and data remediation in effective management of the archive and facile integration with more than 50 external data resources; and (iii) new tools and features for 3D structure analysis and visualization made available during the past year via the RCSB.org web portal.
Published in January 2022
Molecular Modeling and Preliminary Clinical Data Suggesting Antiviral Activity for Chlorpheniramine (Chlorphenamine) Against COVID-19.
Abstract: Chlorpheniramine maleate, a widely used over-the-counter antihistamine, has been identified as a structural analog of aminoquinolines known to possess antiviral activity against the Betacoronavirus severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). Structural similarities include the chlorophenyl group, pyridine ring, alkyl sidechain, and terminal tertiary amine; the comparison of aqueous energy-minimized structures indicates significant three-dimensional similarity as well. Preliminary clinical evidence supports these conclusions. The present study suggests that chlorpheniramine possesses antiviral activity against COVID-19.
Published in January 2022
Natural Language Processing-Assisted Literature Retrieval and Analysis for Combination Therapy in Cancer.
Abstract: PURPOSE: Despite advances in molecular therapeutics, few anticancer agents achieve durable responses. Rational combinations using two or more anticancer drugs have the potential to achieve a synergistic effect and overcome drug resistance, enhancing antitumor efficacy. A publicly accessible biomedical literature search engine dedicated to this domain will facilitate knowledge discovery and reduce manual search and review. METHODS: We developed RetriLite, an information retrieval and extraction framework that leverages natural language processing and domain-specific knowledgebase to computationally identify highly relevant papers and extract key information. The modular architecture enables RetriLite to benefit from synergizing information retrieval and natural language processing techniques while remaining flexible to customization. We customized the application and created an informatics pipeline that strategically identifies papers that describe efficacy of using combination therapies in clinical or preclinical studies. RESULTS: In a small pilot study, RetriLite achieved an F(1) score of 0.93. A more extensive validation experiment was conducted to determine agents that have enhanced antitumor efficacy in vitro or in vivo with poly (ADP-ribose) polymerase inhibitors: 95.9% of the papers determined to be relevant by our application were true positive and the application's feature of distinguishing a clinical paper from a preclinical paper achieved an accuracy of 97.6%. Interobserver assessment was conducted, which resulted in a 100% concordance. The data derived from the informatics pipeline have also been made accessible to the public via a dedicated online search engine with an intuitive user interface. CONCLUSION: RetriLite is a framework that can be applied to establish domain-specific information retrieval and extraction systems. The extensive and high-quality metadata tags along with keyword highlighting facilitate information seekers to more effectively and efficiently discover knowledge in the combination therapy domain.
Showing 1001 to 1004 of 5186 entries