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5,117 results on '"Yin, Xin"'

240. SARS-CoV-2 Orf6 hijacks Nup98 to block STAT nuclear import and antagonize interferon signaling

Author

Miorin, Lisa, Kehrer, Thomas, Sanchez-Aparicio, Maria Teresa, Zhang, Ke, Cohen, Phillip, Patel, Roosheel S, Cupic, Anastasija, Makio, Tadashi, Mei, Menghan, Moreno, Elena, Danziger, Oded, White, Kris M, Rathnasinghe, Raveen, Uccellini, Melissa, Gao, Shengyan, Aydillo, Teresa, Mena, Ignacio, Yin, Xin, Martin-Sancho, Laura, Krogan, Nevan J, Chanda, Sumit K, Schotsaert, Michael, Wozniak, Richard W, Ren, Yi, Rosenberg, Brad R, Fontoura, Beatriz MA, and García-Sastre, Adolfo

Subjects
Biodefense, Emerging Infectious Diseases, Vaccine Related, Infectious Diseases, Pneumonia, Prevention, Lung, Aetiology, 2.1 Biological and endogenous factors, Infection, Good Health and Well Being, Active Transport, Cell Nucleus, Animals, Binding Sites, COVID-19, Chlorocebus aethiops, HEK293 Cells, Humans, Interferons, Nuclear Matrix-Associated Proteins, Nuclear Pore, Nuclear Pore Complex Proteins, Nucleocytoplasmic Transport Proteins, Protein Binding, STAT1 Transcription Factor, STAT2 Transcription Factor, Signal Transduction, Vero Cells, Viral Proteins, Immunization, Pneumonia & Influenza, Biotechnology, Development of treatments and therapeutic interventions, 5.1 Pharmaceuticals, SARS-CoV-2, interferon signaling antagonism, STATs, ORF6, Nup98
Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the ongoing coronavirus disease 2019 (COVID-19) pandemic that is a serious global health problem. Evasion of IFN-mediated antiviral signaling is a common defense strategy that pathogenic viruses use to replicate and propagate in their host. In this study, we show that SARS-CoV-2 is able to efficiently block STAT1 and STAT2 nuclear translocation in order to impair transcriptional induction of IFN-stimulated genes (ISGs). Our results demonstrate that the viral accessory protein Orf6 exerts this anti-IFN activity. We found that SARS-CoV-2 Orf6 localizes at the nuclear pore complex (NPC) and directly interacts with Nup98-Rae1 via its C-terminal domain to impair docking of cargo-receptor (karyopherin/importin) complex and disrupt nuclear import. In addition, we show that a methionine-to-arginine substitution at residue 58 impairs Orf6 binding to the Nup98-Rae1 complex and abolishes its IFN antagonistic function. All together our data unravel a mechanism of viral antagonism in which a virus hijacks the Nup98-Rae1 complex to overcome the antiviral action of IFN.

Published
2020

241. SARS-CoV-2 Infection Depends on Cellular Heparan Sulfate and ACE2

Author

Clausen, Thomas Mandel, Sandoval, Daniel R, Spliid, Charlotte B, Pihl, Jessica, Perrett, Hailee R, Painter, Chelsea D, Narayanan, Anoop, Majowicz, Sydney A, Kwong, Elizabeth M, McVicar, Rachael N, Thacker, Bryan E, Glass, Charles A, Yang, Zhang, Torres, Jonathan L, Golden, Gregory J, Bartels, Phillip L, Porell, Ryan N, Garretson, Aaron F, Laubach, Logan, Feldman, Jared, Yin, Xin, Pu, Yuan, Hauser, Blake M, Caradonna, Timothy M, Kellman, Benjamin P, Martino, Cameron, Gordts, Philip LSM, Chanda, Sumit K, Schmidt, Aaron G, Godula, Kamil, Leibel, Sandra L, Jose, Joyce, Corbett, Kevin D, Ward, Andrew B, Carlin, Aaron F, and Esko, Jeffrey D

Subjects
Biochemistry and Cell Biology, Biological Sciences, Coronaviruses, Emerging Infectious Diseases, Infectious Diseases, Coronaviruses Therapeutics and Interventions, Infection, Amino Acid Sequence, Angiotensin-Converting Enzyme 2, Betacoronavirus, Binding Sites, COVID-19, Cell Line, Coronavirus Infections, Heparin, Heparitin Sulfate, Humans, Kidney, Lung, Molecular Dynamics Simulation, Pandemics, Peptidyl-Dipeptidase A, Pneumonia, Viral, Protein Binding, Protein Domains, Recombinant Proteins, SARS-CoV-2, Spike Glycoprotein, Coronavirus, Virus Internalization, coronavirus, heparan sulfate, heparan sulfate-binding proteins, heparin, lung epithelial cells, pseudotyped virus, spike proteins, Medical and Health Sciences, Developmental Biology, Biological sciences, Biomedical and clinical sciences
Abstract

We show that SARS-CoV-2 spike protein interacts with both cellular heparan sulfate and angiotensin-converting enzyme 2 (ACE2) through its receptor-binding domain (RBD). Docking studies suggest a heparin/heparan sulfate-binding site adjacent to the ACE2-binding site. Both ACE2 and heparin can bind independently to spike protein in vitro, and a ternary complex can be generated using heparin as a scaffold. Electron micrographs of spike protein suggests that heparin enhances the open conformation of the RBD that binds ACE2. On cells, spike protein binding depends on both heparan sulfate and ACE2. Unfractionated heparin, non-anticoagulant heparin, heparin lyases, and lung heparan sulfate potently block spike protein binding and/or infection by pseudotyped virus and authentic SARS-CoV-2 virus. We suggest a model in which viral attachment and infection involves heparan sulfate-dependent enhancement of binding to ACE2. Manipulation of heparan sulfate or inhibition of viral adhesion by exogenous heparin presents new therapeutic opportunities.

Published
2020

242. Discovery of SARS-CoV-2 antiviral drugs through large-scale compound repurposing

Author

Riva, Laura, Yuan, Shuofeng, Yin, Xin, Martin-Sancho, Laura, Matsunaga, Naoko, Pache, Lars, Burgstaller-Muehlbacher, Sebastian, De Jesus, Paul D, Teriete, Peter, Hull, Mitchell V, Chang, Max W, Chan, Jasper Fuk-Woo, Cao, Jianli, Poon, Vincent Kwok-Man, Herbert, Kristina M, Cheng, Kuoyuan, Nguyen, Tu-Trinh H, Rubanov, Andrey, Pu, Yuan, Nguyen, Courtney, Choi, Angela, Rathnasinghe, Raveen, Schotsaert, Michael, Miorin, Lisa, Dejosez, Marion, Zwaka, Thomas P, Sit, Ko-Yung, Martinez-Sobrido, Luis, Liu, Wen-Chun, White, Kris M, Chapman, Mackenzie E, Lendy, Emma K, Glynne, Richard J, Albrecht, Randy, Ruppin, Eytan, Mesecar, Andrew D, Johnson, Jeffrey R, Benner, Christopher, Sun, Ren, Schultz, Peter G, Su, Andrew I, García-Sastre, Adolfo, Chatterjee, Arnab K, Yuen, Kwok-Yung, and Chanda, Sumit K

Subjects
Medical Microbiology, Biomedical and Clinical Sciences, Emerging Infectious Diseases, Rare Diseases, Lung, Orphan Drug, Biodefense, Infectious Diseases, Vaccine Related, Pneumonia & Influenza, Pneumonia, Prevention, Development of treatments and therapeutic interventions, 5.1 Pharmaceuticals, 6.1 Pharmaceuticals, Evaluation of treatments and therapeutic interventions, Infection, Good Health and Well Being, Adenosine Monophosphate, Alanine, Alveolar Epithelial Cells, Antiviral Agents, Betacoronavirus, COVID-19, Cell Line, Coronavirus Infections, Cysteine Proteinase Inhibitors, Dose-Response Relationship, Drug, Drug Evaluation, Preclinical, Drug Repositioning, Drug Synergism, Gene Expression Regulation, Humans, Hydrazones, Induced Pluripotent Stem Cells, Models, Biological, Morpholines, Pandemics, Pneumonia, Viral, Pyrimidines, Reproducibility of Results, SARS-CoV-2, Small Molecule Libraries, Triazines, Virus Internalization, Virus Replication, COVID-19 Drug Treatment, General Science & Technology
Abstract

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019 has triggered an ongoing global pandemic of the severe pneumonia-like disease coronavirus disease 2019 (COVID-19)1. The development of a vaccine is likely to take at least 12-18 months, and the typical timeline for approval of a new antiviral therapeutic agent can exceed 10 years. Thus, repurposing of known drugs could substantially accelerate the deployment of new therapies for COVID-19. Here we profiled a library of drugs encompassing approximately 12,000 clinical-stage or Food and Drug Administration (FDA)-approved small molecules to identify candidate therapeutic drugs for COVID-19. We report the identification of 100 molecules that inhibit viral replication of SARS-CoV-2, including 21 drugs that exhibit dose-response relationships. Of these, thirteen were found to harbour effective concentrations commensurate with probable achievable therapeutic doses in patients, including the PIKfyve kinase inhibitor apilimod2-4 and the cysteine protease inhibitors MDL-28170, Z LVG CHN2, VBY-825 and ONO 5334. Notably, MDL-28170, ONO 5334 and apilimod were found to antagonize viral replication in human pneumocyte-like cells derived from induced pluripotent stem cells, and apilimod also demonstrated antiviral efficacy in a primary human lung explant model. Since most of the molecules identified in this study have already advanced into the clinic, their known pharmacological and human safety profiles will enable accelerated preclinical and clinical evaluation of these drugs for the treatment of COVID-19.

Published
2020

246. STHSGCN: Spatial-temporal heterogeneous and synchronous graph convolution network for traffic flow prediction

Author

Xian Yu, Yin-Xin Bao, and Quan Shi

Subjects
Traffic flow prediction, Graph convolution, Heterogeneity, Causality, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

Nowadays, as a crucial component of intelligent transportation systems, traffic flow prediction has received extensive concern. However, most of the existing studies extracted spatial-temporal features with modules that do not differentiate with time and space, and failed to consider spatial-temporal heterogeneities. Furthermore, although previous works have achieved synchronous modeling of spatial-temporal dependencies, the consideration of temporal causality is still lacking in their graph structures. To address these shortcomings, a spatial-temporal heterogeneous and synchronous graph convolution network (STHSGCN) is proposed for traffic flow prediction. To be specific, separate dilated causal spatial-temporal synchronous graph convolutional networks (DCSTSGCNs) for various node clusters are designed to reflect spatial heterogeneity, different dilated causal spatial-temporal synchronous graph convolutional modules (DCSTSGCMs) for diverse time steps are deployed to take account of temporal heterogeneity. In addition, causal spatial-temporal synchronous graph (CSTSG) is proposed to capture temporal causality in spatial-temporal synchronous learning. We further conducted extensive experiments on four real-world datasets, and the results verified the consistent superiority of our proposed approach compared with various existing baselines.

Published
2023
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