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Design and in vitro evaluation of novel tetrazole derivatives of dianisidine as anticancer agents targeting Bcl-2 apoptosis regulator

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Scientific reports 2025年第1期15卷 17634页

作者： Wioletta Olejarz Karol Sadowski Piotr Roszkowski Anna Bielenica Maciej Wiśniewski Marta Struga Daniel Szulczyk Department of Biochemistry and Pharmacogenomics Faculty of Pharmacy Medical University of Warsaw 02-097 Warsaw Poland. Centre for Preclinical Research Medical University of Warsaw 02-097 Warsaw Poland. Faculty of Chemistry University of Warsaw Pasteura 1 02-093 Warszawa Poland. Department of Biochemistry Medical University of Warsaw 02-097 Warsaw Poland. Laboratory of Bioinformatics and Computational Genomics Faculty of Mathematics and Information Science Warsaw University of Technology Warsaw Poland. Laboratory of Functional and Structural Genomics Centre of New Technologies University of Warsaw Warsaw Poland. Department of Biochemistry Medical University of Warsaw 02-097 Warsaw Poland. daniel.szulczyk@wum.edu.pl.

This study examines the synthesis and biological evaluation of novel tetrazole derivatives of 3,3'-dimethoxybenzidine as potential anticancer agents, focusing on their cytotoxic, apoptotic, and anti-inflammatory properties. Ten derivatives were synthesized using thioureas as precursors, characterized through spectroscopic methods, and assessed for their in silico toxicological profiles using the ADMET-AI and ProTox 3.0 platforms. In vitro cytotoxic activity was evaluated against four human cancer cell lines (HTB-140, A549, HeLa, SW620) and one normal cell line (HaCaT) using MTT and LDH assays. Mechanistic studies included apoptosis assessment via flow cytometry and interleukin-6 (IL-6) analysis using ELISA. The synthesized tetrazole derivatives demonstrated significant anticancer potential, exhibiting selective cytotoxicity against cancer cell lines, robust induction of apoptosis, and a notable reduction in IL-6 levels. Their favorable toxicity profiles, as observed in both in silico and in vitro evaluations, support their potential as promising candidates for further development. The tested compounds showed strong inhibitory activity against the apoptosis regulator Bcl-2, with binding affinities comparable to those of native ligands. Western blot analysis revealed a dramatic loss of Bcl-2 protein expression in selected cancer cells during exposure to compound 5. Additionally, this research highlights the innovative use of hazardous substrates in drug discovery, aligning with the principles of green chemistry. Future efforts should focus on optimizing the most active derivatives and conducting in vivo studies to confirm their therapeutic potential and safety.

关键词： Anticancer Apoptosis Cytotoxicity Tetrazoles Toxicology

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OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials

arXiv

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arXiv 2023年

作者： Eastman, Peter Galvelis, Raimondas Peláez, Raúl P. Abreu, Charlles R.A. Farr, Stephen E. Gallicchio, Emilio Gorenko, Anton Henry, Michael M. Hu, Frank Huang, Jing Krämer, Andreas Michel, Julien Mitchell, Joshua A. Pande, Vijay S. Rodrigues, João P.G.L.M. Rodriguez-Guerra, Jaime Simmonett, Andrew C. Singh, Sukrit Swails, Jason Turner, Philip Wang, Yuanqing Zhang, Ivy Chodera, John D. De Fabritiis, Gianni Markland, Thomas E. Department of Chemistry Stanford University StanfordCA94305 United States Acellera Labs C Dr Trueta 183 Barcelona08005 Spain C Dr. Aiguader 88 Barcelona08003 Spain Chemical Engineering Department School of Chemistry Federal University of Rio de Janeiro Rio de Janeiro68542 Brazil Redesign Science Inc. 180 Varick St. New YorkNY10014 United States EaStCHEM School of Chemistry University of Edinburgh EH9 3FJ United Kingdom Department of Chemistry and Biochemistry Brooklyn College The City University of New York NY United States Ph.D. Program in Chemistry Ph.D. Program in Biochemistry The Graduate Center of the City University of New York New YorkNY United States Stream HPC Koningin Wilhelminaplein 1 - 40601 Amsterdam1062 HG Netherlands Computational and Systems Biology Program Sloan Kettering Institute Memorial Sloan Kettering Cancer Center New YorkNY10065 United States Key Laboratory of Structural Biology of Zhejiang Province School of Life Sciences Westlake University 18 Shilongshan Road Zhejiang Hangzhou310024 China Department of Mathematics and Computer Science Freie Universität Berlin Arnimallee 12 Berlin14195 Germany The Open Force Field Initiative Open Molecular Software Foundation DavisCA95616 United States Andreessen Horowitz 2865 Sand Hill Rd Menlo ParkCA94025 United States Department of Structural Biology Stanford University StanfordCA94305 United States Charité Universitätsmedizin Berlin In silico Toxicology and Structural Bioinformatics Virchowweg 6 Berlin10117 Germany Laboratory of Computational Biology National Heart Lung and Blood Institute National Institutes of Health BethesdaMD20892 United States Entos Inc. 9310 Athena Circle La Jolla CA92037 United States College of Engineering Virginia Polytechnic Institute State University BlacksburgVA24061 United States Simons Center for Computational Physical Chemistry Center for Data Science New York University 24 Waverly Place New YorkNY10004 United States T

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy. A higher-level interface allows users to easily model their molecules of interest with general purpose, pretrained potential functions. A collection of optimized CUDA kernels and custom PyTorch operations greatly improves the speed of simulations. We demonstrate these features on simulations of cyclin-dependent kinase 8 (CDK8) and the green fluorescent protein (GFP) chromophore in water. Taken together, these features make it practical to use machine learning to improve the accuracy of simulations at only a modest increase in cost. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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Front Cover: Design, Synthesis, and Characterization of Novel Styryl Dyes as Fluorescent Probes for Tau Aggregate Detectionin Vitroand in Cells (Chem. Asian J. 6/2024)

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Chemistry – An Asian Journal 2024年第6期19卷

作者： Withsakorn Sangsuwan Kriangsak Faikhruea Kotchakorn Supabowornsathit Don Sangsopon Praewphan Ingrungruanglert Hathaichanok Chuntakaruk Napatsaporn Nuntavanotayan Kittiporn Nakprasit Nipan Israsena Thanyada Rungrotmongkol Pitak Chuawong Tirayut Vilaivan Chanat Aonbangkhen Center of Excellence in Natural Products Chemistry (CENP) Department of Chemistry Faculty of Science Chulalongkorn University Bangkok 10330 Thailand Department of Chemistry and Center of Excellence for Innovation in Chemistry Faculty of Science Special Research Unit for Advanced Magnetic Resonance (AMR) Kasetsart University Bangkok 10900 Thailand These authors are contributed equally. Organic Synthesis Research Unit Department of Chemistry Faculty of Science Chulalongkorn University Bangkok 10330 Thailand Stem Cell and Cell Therapy Research Unit and Department of Pharmacology Faculty of Medicine Chulalongkorn University Bangkok 10330 Thailand Program in Bioinformatics and Computational Biology Graduate School Chulalongkorn University Bangkok 10330 Thailand Center of Excellence in Structural and Computational Biology Department of Biochemistry Faculty of Science Chulalongkorn University Bangkok 10330 Thailand

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Guidelines for public database submission of uncultivated virus genome sequences for taxonomic classification (vol 41, pg 898, 2023)

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NATURE BIOTECHNOLOGY 2023年第9期41卷 1346-1346页

作者： Adriaenssens, Evelien M. M. Roux, Simon Brister, J. Rodney Karsch-Mizrachi, Ilene Kuhn, Jens H. Varsani, Arvind Yigang, Tong Reyes, Alejandro Lood, Cedric Lefkowitz, Elliot J. Sullivan, Matthew B. B. Edwards, Robert A. A. Simmonds, Peter Rubino, Luisa Sabanadzovic, Sead Krupovic, Mart Dutilh, Bas E. E. Quadram Institute Bioscience Norwich Research Park Rosalind Franklin Road Norwich UK United States Department of Energy Joint Genome Institute Lawrence Berkeley National Laboratory Berkeley CA USA National Center for Biotechnology Information National Library of Medicine National Institutes of Health Bethesda MD USA Integrated Research Facility at Fort Detrick National Institute of Allergy and Infectious Diseases National Institutes of Health Fort Detrick Frederick MD USA The Biodesign Center for Fundamental and Applied Microbiomics Arizona State University Tempe AZ USA Structural Biology Research Unit Department of Clinical Laboratory Sciences University of Cape Town Cape Town South Africa Beijing Advanced Innovation Center for Soft Matter Science and Engineering College of Life Science and Technology Beijing University of Chemical Technology Beijing China Max Planck Tandem Group in Computational Biology Department of Biological Sciences Universidad de los Andes Bogotá Colombia Centre of Microbial and Plant Genetics Department of Microbial and Molecular Systems KU Leuven Leuven Belgium Laboratory of Gene Technology Department of Biosystems KU Leuven Leuven Belgium Institute of Biodiversity Faculty of Biological Sciences Cluster of Excellence Balance of the Microverse Friedrich Schiller University Jena Jena Germany Department of Microbiology University of Alabama at Birmingham Birmingham AL USA Department of Microbiology The Ohio State University Columbus OH USA Department of Civil Environmental and Geodetic Engineering The Ohio State University Columbus OH USA Center of Microbiome Science The Ohio State University Columbus OH USA College of Science and Engineering Flinders University Bedford Park South Australia Australia Nuffield Department of Medicine University of Oxford South Parks Road Oxford UK Consiglio Nazionale delle Ricerche Istituto per la Protezione Sostenibile delle Piante Bari Italy Department of Biochemistry Molecular Bio

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Binding-Site Purification of Actives (B-SPA) Enables Efficient Large-Scale Progression of Fragment Hits by Combining Multi-Step Array Synthesis With HT Crystallography

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Angewandte Chemie 2025年

作者： Harold Grosjean Anthony Aimon Storm Hassell-Hart Warren Thompson Lizbé Koekemoer James Bennett Anthony Bradley Cameron Anderson Conor Wild William J. Bradshaw Edward A. FitzGerald Tobias Krojer Oleg Fedorov Philip C. Biggin John Spencer Frank von Delft Diamond Light Source Ltd Harwell Science and Innovation Campus OX11 0QX Didcot UK Structural Bioinformatics and Computational Biochemistry Departement of Biochemistry University of Oxford South Parks Road OX1 3QU Oxford UK Joint first authors Research Complex at Harwell Harwell Science and Innovation Campus OX11 0FA Didcot UK Department of Chemistry School of Life Sciences University of Sussex Falmer BN1 9QJ UK Centre for Medicines Discovery University of Oxford Old Road Campus Roosevelt Drive OX3 7DQ Headington UK Structural Genomics Consortium University of Oxford Old Road Campus Roosevelt Drive OX3 7DQ Headington UK Creoptix AG Zugerstrasse 76 8820 Wädenswil Switzerland Sussex Drug Discovery Centre (SDDC) School of Life Sciences University of Sussex Falmer BN1 9QJ UK. Department of Biochemistry University of Johannesburg Auckland Park 2006 South Africa

Fragment approaches are long-established in target-based ligand discovery, yet their full transformative potential lies dormant because progressing the initial weakly binding hits to potency remains a formidable challenge. The only credible progression paradigm involves multiple cycles of costly conventional design-make-test-analyse medicinal chemistry. We propose an alternative approach to fragment elaboration, namely performing large numbers of parallel and diverse automated multiple step reactions, and evaluating the binding of the crude reaction products by high-throughput protein X-ray crystallography. We show it is effective and low-cost to perform, in parallel, large numbers of non-uniform multi-step reactions, because, even without compound purification, crystallography provides a high-quality readout of binding. This can detect low-level binding of weakly active compounds, which the target binding site extracts directly from crude reaction mixtures. In this proof-of-concept study, we have expanded a fragment hit, from a crystal-based screen of the second bromodomain of pleckstrin homology domain-interacting protein (PHIP(2)), using array synthesis on low-cost robotics. We were able to implement 6 independent multi-step reaction routes of up to 5 steps, attempting the synthesis of 1876 diverse expansions, designs entirely driven by synthetic tractability. The expected product was present in 1108 (59%) crude reaction mixtures, detected by liquid chromatography mass spectrometry (LCMS). 22 individual products were resolved in the crystal structures of crude reaction mixtures added to crystals, providing an initial structure activity relationship map. 19 of these showed binding pose stability, while, through binding instability in the remaining 3 products, we could resolve a stereochemical preference for mixtures containing racemic compounds. One compound showed biochemical potency (IC 50 =34 μM) and affinity (K d =50 μM) after resynthesis. This approach theref

关键词： Fragment-based drug discovery high-throughput x-ray crystallography automated synthesis array synthesis bromodomain inhibitor

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Known allosteric proteins have central roles in genetic disease

arXiv

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arXiv 2021年

作者： Abrusán, György Ascher, David B. Inouye, Michael Cambridge Baker Systems Genomics Initiative Department of Public Health and Primary Care School of Medicine University of Cambridge United Kingdom Department of Biochemistry University of Cambridge Cambridge United Kingdom Structural Biology and Bioinformatics Department of Biochemistry Bio21 Institute University of Melbourne Melbourne Australia Computational Biology and Clinical Informatics Baker Heart and Diabetes Institute Melbourne Australia Cambridge Baker Systems Genomics Initiative Baker Heart and Diabetes Institute Melbourne Australia British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care University of Cambridge Cambridge United Kingdom British Heart Foundation Centre of Research Excellence University of Cambridge Cambridge United Kingdom Health Data Research UK Cambridge Wellcome Genome Campus and University of Cambridge Cambridge United Kingdom The Alan Turing Institute London United Kingdom

Allostery is a form of protein regulation, where ligands that bind sites located apart from the active site can modify the activity of the protein. The molecular mechanisms of allostery have been extensively studied, because allosteric sites are less conserved than active sites, and drugs targeting them are more specific than drugs binding the active sites. Here we quantify the importance of allostery in genetic disease. We show that 1) known allosteric proteins are central in disease networks, and contribute to genetic disease and comorbidities much more than non-allosteric proteins, in many major disease types like hematopoietic diseases, cardiovascular diseases, cancers, diabetes, or diseases of the central nervous system. 2) variants from cancer genome-wide association studies are enriched near allosteric proteins, indicating their importance to polygenic traits;and 3) the importance of allosteric proteins in disease is due, at least partly, to their central positions in protein-protein interaction networks, and probably not due to their dynamical properties. © 2021, CC BY.

关键词： Diseases

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How to learn from inconsistencies: Integrating molecular simulations with experimental data

arXiv

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arXiv 2019年

作者： Orioli, Simone Larsen, Andreas Haahr Bottaro, Sandro Lindorff-Larsen, Kresten Structural Biology NMR Laboratory Linderstrøm-Lang Centre for Protein Science Department of Biology University of Copenhagen Copenhagen Denmark Structural Biophysics Niels Bohr Institute Faculty of Science University of Copenhagen Copenhagen Denmark Structural Bioinformatics and Computational Biochemistry Unit Department of Biochemistry University of Oxford Oxford United Kingdom Atomistic Simulations Laboratory Istituto Italiano di Tecnologia Genova Italy

Molecular simulations and biophysical experiments can be used to provide independent and complementary insights into the molecular origin of biological processes. A particularly useful strategy is to use molecular simulations as a modelling tool to interpret experimental measurements, and to use experimental data to refine our biophysical models. Thus, explicit integration and synergy between molecular simulations and experiments is fundamental for furthering our understanding of biological processes. This is especially true in the case where discrepancies between measured and simulated observables emerge. In this chapter, we provide an overview of some of the core ideas behind methods that were developed to improve the consistency between experimental information and numerical predictions. We distinguish between situations where experiments are used to refine our understanding and models of specific systems, and situations where experiments are used more generally to refine transferable models. We discuss different philosophies and attempt to unify them in a single framework. Until now, such integration between experiments and simulations have mostly been applied to static data, and we discuss more recent developments aimed to analyse time-dependent or time-resolved data. Copyright © 2019, The Authors. All rights reserved.

关键词： Philosophical aspects

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Exploring Unconventional SAM Analogues To Build Cell-Potent Bisubstrate Inhibitors for NicotinamideN-Methyltransferase

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Angewandte Chemie 2022年第16期134卷

作者： Iredia D. Iyamu Jonah Z. Vilseck Ravi Yadav Nicholas Noinaj Rong Huang Department of Medicinal Chemistry and Molecular Pharmacology Purdue Institute for Drug Discovery Purdue University Center for Cancer Research Purdue University West Lafayette IN 47907 USA Department of Biochemistry and Molecular Biology Center for Computational Biology and Bioinformatics Indiana University School of Medicine Indianapolis IN 46202 USA Department of Biological Sciences Markey Center for Structural Biology and the Purdue Institute of Inflammation Immunology and Infectious Disease Purdue University West Lafayette IN 47907 USA

Nicotinamide N -methyltransferase (NNMT) methylates nicotinamide and has been associated with various diseases. Herein, we report the first cell-potent NNMT bisubstrate inhibitor II399 , demonstrating a K i of 5.9 nM in a biochemical assay and a cellular IC 50 value of 1.9 μM. The inhibition mechanism and cocrystal structure confirmed II399 engages both the substrate and cofactor binding pockets. computational modeling and binding data reveal a balancing act between enthalpic and entropic components that lead to II399′ s low nM binding affinity. Notably, II399 is 1 000-fold more selective for NNMT than closely related methyltransferases. We expect that II399 would serve as a valuable probe to elucidate NNMT biology. Furthermore, this strategy provides the first case of introducing unconventional SAM mimics, which can be adopted to develop cell-potent inhibitors for other SAM-dependent methyltransferases.

关键词： Bisubstrate Analogues Bisubstrate Inhibitors Cell-Potent Inhibitors Enzymes SAM Analogues

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PDBe-KB: collaboratively defining the biological context of structural data

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NUCLEIC ACIDS RESEARCH 2022年第D1期50卷 D534-D542页

作者： Varadi, Mihaly Anyango, Stephen Armstrong, David Berrisford, John Choudhary, Preeti Deshpande, Mandar Nadzirin, Nurul Nair, Sreenath S. Pravda, Lukas Tanweer, Ahsan Al-Lazikani, Bissan Andreini, Claudia Barton, Geoffrey J. Bednar, David Berka, Karel Blundell, Tom Brock, Kelly P. Carazo, Jose Maria Damborsky, Jiri David, Alessia Dey, Sucharita Dunbrack, Roland Recio, Juan Fernandez Fraternali, Franca Gibson, Toby Helmer-Citterich, Manuela Hoksza, David Hopf, Thomas Jakubec, David Kannan, Natarajan Krivak, Radoslav Kumar, Manjeet Levy, Emmanuel D. London, Nir Macias, Jose Ramon Srivatsan, Madhusudhan M. Marks, Debora S. Martens, Lennart McGowan, Stuart A. McGreig, Jake E. Modi, Vivek Parra, R. Gonzalo Pepe, Gerardo Piovesan, Damiano Prilusky, Jaime Putignano, Valeria Radusky, Leandro G. Ramasamy, Pathmanaban Rausch, Atilio O. Reuter, Nathalie Rodriguez, Luis A. Rollins, Nathan J. Rosato, Antonio Rubach, Pawel Serrano, Luis Singh, Gulzar Skoda, Petr Sorzano, Carlos Oscar S. Stourac, Jan Sulkowska, Joanna, I Svobodova, Radka Tichshenko, Natalia Tosatto, Silvio C. E. Vranken, Wim Wass, Mark N. Xue, Dandan Zaidman, Daniel Thornton, Janet Sternberg, Michael Orengo, Christine Velankar, Sameer European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Wellcome Genome Campus Hinxton United Kingdom Cancer Research UK Cancer Therapeutics Unit Division of Cancer Therapeutics The Institute of Cancer Research London United Kingdom University of Florence C.I.R.M.M.P. Magnetic Resonance Center Sesto Fiorentino Italy School of Life Sciences University of Dundee Dundee United Kingdom Masaryk University International Centre for Clinical Research St. Anne’s University Hospital Brno Department of Experimental Biology and RECETOX Brno Czech Republic Palacky University Olomouc Department of Physical Chemistry Olomouc Czech Republic University of Cambridge Department of Biochemistry Cambridge United Kingdom Computational and Systems Biology Massachusetts Institute of Technology Cambridge MA United States CNB-CSIC Biocomputing Unit - Instruct Image Processing Center Madrid Spain Imperial College London London United Kingdom Weizmann Institute of Science Rehovot Israel Fox Chase Cancer Center Institute for Cancer Research Philadelphia PA United States Instituto de Ciencias de la Vid y del Vino (CSIC - Universidad de La Rioja - Gobierno de La Rioja) Oenology Barcelona Spain Randall Centre for Cell & Molecular Biophysics King’s College London London United Kingdom European Molecular Biology Laboratory Heidelberg Germany Centre for Molecular Bioinformatics Department of Biology University of Rome Tor Vergata Rome Italy Charles University Prague Czech Republic University of Georgia Department of Biochemistry and Molecular Biology Institute of Bioinformatics Athens United States Indian Institute of Science Education and Research Pune India Ghent University Department of Biomolecular Medicine Ghent Belgium VIB-UGent Center for Medical Biotechnology Ghent Belgium University of Kent Canterbury Kent United Kingdom Barcelona Supercomputing Center Life Sciences Department Barcelona Spain University of Padova Deptartment of Biomedical

The Protein Data Bank in Europe - Knowledge Base (PDBe-KB, https://***) is an open collaboration between world-leading specialist data resources contributing functional and biophysical annotations derived from or relevant to the Protein Data Bank (PDB). The goal of PDBe-KB is to place macromolecular structure data in their biological context by developing standardised data exchange formats and integrating functional annotations from the contributing partner resources into a knowledge graph that can provide valuable biological insights. Since we described PDBe-KB in 2019, there have been significant improvements in the variety of available annotation data sets and user functionality. Here, we provide an overview of the consortium, highlighting the addition of annotations such as predicted covalent binders, phosphorylation sites, effects of mutations on the protein structure and energetic local frustration. In addition, we describe a library of reusable web-based visualisation components and introduce new features such as a bulk download data service and a novel superposition service that generates clusters of superposed protein chains weekly for the whole PDB archive.

关键词： mutation biophysics frustration internet libraries molecular structure phosphorylation graphical displays protein structure protein data bank molecule knowledge bases datasets

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Multiscale molecular dynamics simulations of lipid interactions with P-glycoprotein in a complex membrane (vol 78, pg 250, 2017)

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JOURNAL OF MOLECULAR GRAPHICS & MODELLING 2017年 77卷 250-250页

作者： Domicevica, L. Koldso, H. Biggin, P. C. Structural Bioinformatics and Computational Biochemistry Department of Biochemistry University of Oxford South Parks Road Oxford OX1 3QU United Kingdom. Structural Bioinformatics and Computational Biochemistry Department of Biochemistry University of Oxford South Parks Road Oxford OX1 3QU United Kingdom. Electronic address: philip.biggin@bioch.ox.ac.uk.

P-glycoprotein (P-gp) can transport a wide range of very different hydrophobic organic molecules across the membrane. Its ability to extrude molecules from the cell creates delivery problems for drugs that target proteins in the central nervous system (CNS) and also causes drug-resistance in many forms of cancer. Whether a drug will be susceptible to export by P-gp is difficult to predict and currently this is usually assessed with empirical and/or animal models. Thus, there is a need to better understand how P-gp works at the molecular level in order to fulfil the 3Rs: Refinement, reduction and replacement of animals in research. As structural information increasingly becomes available, our understanding at the molecular level improves. Proteins like P-gp are however very dynamic entities and thus one of the most appropriate ways to study them is with molecular dynamics simulations, especially as this can capture the influence of the surrounding environment. Recent parameterization developments have meant that it is now possible to simulate lipid bilayers that more closely resemble in vivo membranes in terms of their composition. In this report we construct a complex lipid bilayer that mimics the composition of brain epithelial cells and examine the interactions of it with P-gp. We find that the negatively charged phosphatidylserine lipids in the inner leaflet of the membrane tend to form an annulus around P-gp. We also observed the interaction of cholesterol with three distinct areas of the P-gp. Potential of mean force (PMF) calculations suggest that a crevice between transmembrane helices 10 and 12 has particularly favourable interaction energy for cholesterol.

关键词： ABCB1 Bilayer Coarse-grained Efflux pump Lipids Membrane Molecular dynamics P-glycoprotein

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