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Medicinal Chemistry

Editor-in-Chief

ISSN (Print): 1573-4064
ISSN (Online): 1875-6638

Review Article

Structural Variability in the RLR-MAVS Pathway and Sensitive Detection of Viral RNAs

Author(s): Qiu-Xing Jiang *

Volume 15, Issue 5, 2019

Page: [443 - 458] Pages: 16

DOI: 10.2174/1573406415666181219101613

Price: $65

Abstract

Cells need high-sensitivity detection of non-self molecules in order to fight against pathogens. These cellular sensors are thus of significant importance to medicinal purposes, especially for treating novel emerging pathogens. RIG-I-like receptors (RLRs) are intracellular sensors for viral RNAs (vRNAs). Their active forms activate mitochondrial antiviral signaling protein (MAVS) and trigger downstream immune responses against viral infection. Functional and structural studies of the RLR-MAVS signaling pathway have revealed significant supramolecular variability in the past few years, which revealed different aspects of the functional signaling pathway. Here I will discuss the molecular events of RLR-MAVS pathway from the angle of detecting single copy or a very low copy number of vRNAs in the presence of non-specific competition from cytosolic RNAs, and review key structural variability in the RLR / vRNA complexes, the MAVS helical polymers, and the adapter-mediated interactions between the active RLR / vRNA complex and the inactive MAVS in triggering the initiation of the MAVS filaments. These structural variations may not be exclusive to each other, but instead may reflect the adaptation of the signaling pathways to different conditions or reach different levels of sensitivity in its response to exogenous vRNAs.

Keywords: Cryo-electron microscopy, exogenous microorganisms, NMR technique, RLR and MAVS, viral RNAs, X-ray crystallography.

Graphical Abstract

[1]
Kramer, R.; Cohen, D. Functional genomics to new drug targets. Nat. Rev. Drug Discov., 2004, 3, 965-972.
[2]
Chou, K.C. Some remarks on protein attribute prediction and pseudo amino acid composition. J. Theor. Biol., 2011, 273, 236-247.
[3]
Chen, W.; Ding, H.; Feng, P.; Lin, H.; Chou, K.C. iACP: A sequence-based tool for identifying anticancer peptides. Oncotarget, 2016, 7, 16895-16909.
[4]
Chen, W.; Ding, H.; Zhou, X.; Lin, H.; Chou, K.C. iRNA(m6A)-PseDNC: Identifying N(6)-methyladenosine sites using pseudo dinucleotide composition. Anal. Biochem., 2018, 561-562, 59-65.
[5]
Chen, W.; Feng, P.; Ding, H.; Lin, H.; Chou, K.C. iRNA-Methyl: Identifying N(6)-methyladenosine sites using pseudo nucleotide composition. Anal. Biochem., 2015, 490, 26-33.
[6]
Chen, W.; Feng, P.; Ding, H.; Lin, H.; Chou, K.C. Using deformation energy to analyze nucleosome positioning in genomes. Genomics, 2016, 107, 69-75.
[7]
Chen, W.; Feng, P.; Yang, H.; Ding, H.; Lin, H.; Chou, K.C. iRNA-AI: Identifying the adenosine to inosine editing sites in RNA sequences. Oncotarget, 2017, 8, 4208-4217.
[8]
Chen, W.; Feng, P.; Yang, H.; Ding, H.; Lin, H.; Chou, K.C. iRNA-3typeA: Identifying three types of modification at RNA’s adenosine sites. Mol. Ther. Nucleic Acids, 2018, 11, 468-474.
[9]
Chen, W.; Feng, P.M.; Lin, H.; Chou, K.C. iRSpot-PseDNC: Identify recombination spots with pseudo dinucleotide composition. Nucleic Acids Res., 2013, 41e68
[10]
Chen, W.; Feng, P.M.; Lin, H.; Chou, K.C. iSS-PseDNC: Identifying splicing sites using pseudo dinucleotide composition. BioMed Res. Int., 2014, 2014623149
[11]
Chen, W.; Tang, H.; Ye, J.; Lin, H.; Chou, K.C. iRNA-PseU: Identifying RNA pseudouridine sites. Mol. Ther. Nucleic Acids, 2016, 5e332
[12]
Ding, H.; Deng, E.Z.; Yuan, L.F.; Liu, L.; Lin, H.; Chen, W.; Chou, K.C. iCTX-type: A sequence-based predictor for identifying the types of conotoxins in targeting ion channels. BioMed Res. Int., 2014, 2014286419
[13]
Feng, P.; Ding, H.; Yang, H.; Chen, W.; Lin, H.; Chou, K.C. iRNA-PseColl: Identifying the occurrence sites of different RNA modifications by incorporating collective effects of nucleotides into PseKNC. Mol. Ther. Nucleic Acids, 2017, 7, 155-163.
[14]
Feng, P.M.; Chen, W.; Lin, H.; Chou, K.C. iHSP-PseRAAAC: Identifying the heat shock protein families using pseudo reduced amino acid alphabet composition. Anal. Biochem., 2013, 442, 118-125.
[15]
Lin, H.; Deng, E.Z.; Ding, H.; Chen, W.; Chou, K.C. iPro54-PseKNC: A sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition. Nucleic Acids Res., 2014, 42, 12961-12972.
[16]
Yang, H.; Lv, H.; Ding, H.; Chen, W.; Lin, H. iRNA-2OM: A sequence-based predictor for identifying 2′-O-Methylation sites in Homo sapiens. J. Comput. Biol., 2018, 25(11), 1266-1277.
[17]
Zhang, C.J.; Tang, H.; Li, W.C.; Lin, H.; Chen, W.; Chou, K.C. iOri-Human: Identify human origin of replication by incorporating dinucleotide physicochemical properties into pseudo nucleotide composition. Oncotarget, 2016, 7, 69783-69793.
[18]
Feng, P.; Yang, H.; Ding, H.; Lin, H.; Chen, W.; Chou, K.C. iDNA6mA-PseKNC: Identifying DNA N(6)-methyladenosine sites by incorporating nucleotide physicochemical properties into PseKNC. Genomics, 2018, 111(1), 96-102.
[19]
Su, Z.D.; Huang, Y.; Zhang, Z.Y.; Zhao, Y.W.; Wang, D.; Chen, W.; Chou, K.C.; Lin, H. iLoc-lncRNA: Predict the subcellular location of lncRNAs by incorporating octamer composition into general PseKNC. Bioinformatics, 2018, 34(24), 4196-4204.
[20]
Yang, H.; Qiu, W.R.; Liu, G.; Guo, F.B.; Chen, W.; Chou, K.C.; Lin, H. iRSpot-Pse6NC: Identifying recombination spots in Saccharomyces cerevisiae by incorporating hexamer composition into general PseKNC. Int. J. Biol. Sci., 2018, 14, 883-891.
[21]
Sharma, A.K.; Zhou, G.P.; Kupferman, J.; Surks, H.K.; Christensen, E.N.; Chou, J.J.; Mendelsohn, M.E.; Rigby, A.C. Probing the interaction between the coiled coil leucine zipper of cGMP-dependent protein kinase Ialpha and the C terminus of the myosin binding subunit of the myosin light chain phosphatase. J. Biol. Chem., 2008, 283, 32860-32869.
[22]
Schnell, J.R.; Chou, J.J. Structure and mechanism of the M2 proton channel of influenza A virus. Nature, 2008, 451, 591-595.
[23]
Berardi, M.J.; Shih, W.M.; Harrison, S.C.; Chou, J.J. Mitochondrial uncoupling protein 2 structure determined by NMR molecular fragment searching. Nature, 2011, 476, 109-113.
[24]
Chen, B.; Chou, J.J. Structure of the transmembrane domain of HIV-1 envelope glycoprotein. FEBS J., 2017, 284, 1171-1177.
[25]
Dev, J.; Park, D.; Fu, Q.; Chen, J.; Ha, H.J.; Ghantous, F.; Herrmann, T.; Chang, W.; Liu, Z.; Frey, G.; Seaman, M.S.; Chen, B.; Chou, J.J. Structural basis for membrane anchoring of HIV-1 envelope spike. Science, 2016, 353, 172-175.
[26]
Oxenoid, K.; Dong, Y.; Cao, C.; Cui, T.; Sancak, Y.; Markhard, A.L.; Grabarek, Z.; Kong, L.; Liu, Z.; Ouyang, B.; Cong, Y.; Mootha, V.K.; Chou, J.J. Architecture of the mitochondrial calcium uniporter. Nature, 2016, 533, 269-273.
[27]
OuYang, B.; Xie, S.; Berardi, M.J.; Zhao, X.; Dev, J.; Yu, W.; Sun, B.; Chou, J.J. Unusual architecture of the p7 channel from hepatitis C virus. Nature, 2013, 498, 521-525.
[28]
Hiller, S.; Garces, R.G.; Malia, T.J.; Orekhov, V.Y.; Colombini, M.; Wagner, G. Solution structure of the integral human membrane protein VDAC-1 in detergent micelles. Science, 2008, 321, 1206-1210.
[29]
Colombini, M. The published 3D structure of the VDAC channel: Native or not? Trends Biochem. Sci., 2009, 34, 382-389.
[30]
Hiller, S.; Wagner, G. The role of solution NMR in the structure determinations of VDAC-1 and other membrane proteins. Curr. Opin. Struct. Biol., 2009, 19, 396-401.
[31]
Zeth, K.; Zachariae, U. Ten years of high resolution structural research on the Voltage Dependent Anion Channel (VDAC)-recent developments and future directions. Front. Physiol., 2018, 9, 108.
[32]
Hu, J.; Asbury, T.; Achuthan, S.; Li, C.; Bertram, R.; Quine, J.R.; Fu, R.; Cross, T.A. Backbone structure of the amantadine-blocked trans-membrane domain M2 proton channel from Influenza a virus. Biophys. J., 2007, 92, 4335-4343.
[33]
Li, C.; Qin, H.; Gao, F.P.; Cross, T.A. Solid-state NMR characterization of conformational plasticity within the transmembrane domain of the influenza A M2 proton channel. Biochim. Biophys. Acta, 2007, 1768(12), 3162-3170.
[34]
Cady, S.D.; Schmidt-Rohr, K.; Wang, J.; Soto, C.S.; Degrado, W.F.; Hong, M. Structure of the amantadine binding site of Influenza M2 proton channels in lipid bilayers. Nature, 2010, 463, 689-692.
[35]
Hu, F.; Luo, W.; Hong, M. Mechanisms of proton conduction and gating in Influenza M2 proton channels from solid-state NMR. Science, 2010, 330, 505-508.
[36]
Wu, B.; Chien, E.Y.; Mol, C.D.; Fenalti, G.; Liu, W.; Katritch, V.; Abagyan, R.; Brooun, A.; Wells, P.; Bi, F.C.; Hamel, D.J.; Kuhn, P.; Handel, T.M.; Cherezov, V.; Stevens, R.C. Structures of the CXCR4 chemokine GPCR with small-molecule and cyclic peptide antagonists. Science, 2010, 330, 1066-1071.
[37]
Rosenbaum, D.M.; Cherezov, V.; Hanson, M.A.; Rasmussen, S.G.; Thian, F.S.; Kobilka, T.S.; Choi, H.J.; Yao, X.J.; Weis, W.I.; Stevens, R.C.; Kobilka, B.K. GPCR engineering yields high-resolution structural insights into beta2-adrenergic receptor function. Science, 2007, 318, 1266-1273.
[38]
Sun, Y.; Huang, J.; Xiang, Y.; Bastepe, M.; Juppner, H.; Kobilka, B.K.; Zhang, J.J.; Huang, X.Y. Dosage-dependent switch from G protein-coupled to G protein-independent signaling by a GPCR. EMBO J., 2007, 26, 53-64.
[39]
Rasmussen, S.G.; Choi, H.J.; Rosenbaum, D.M.; Kobilka, T.S.; Thian, F.S.; Edwards, P.C.; Burghammer, M.; Ratnala, V.R.; Sanishvili, R.; Fischetti, R.F.; Schertler, G.F.; Weis, W.I.; Kobilka, B.K. Crystal structure of the human beta2 adrenergic G-protein-coupled receptor. Nature, 2007, 450, 383-387.
[40]
Rosenbaum, D.M.; Rasmussen, S.G.; Kobilka, B.K. The structure and function of G-protein-coupled receptors. Nature, 2009, 459, 356-363.
[41]
Chae, P.S.; Rasmussen, S.G.; Rana, R.R.; Gotfryd, K.; Chandra, R.; Goren, M.A.; Kruse, A.C.; Nurva, S.; Loland, C.J.; Pierre, Y.; Drew, D.; Popot, J.L.; Picot, D.; Fox, B.G.; Guan, L.; Gether, U.; Byrne, B.; Kobilka, B.; Gellman, S.H. Maltose-neopentyl glycol (MNG) amphiphiles for solubilization, stabilization and crystallization of membrane proteins. Nat. Methods, 2010, 7, 1003-1008.
[42]
Rasmussen, S.G.; Choi, H.J.; Fung, J.J.; Pardon, E.; Casarosa, P.; Chae, P.S.; Devree, B.T.; Rosenbaum, D.M.; Thian, F.S.; Kobilka, T.S.; Schnapp, A.; Konetzki, I.; Sunahara, R.K.; Gellman, S.H.; Pautsch, A.; Steyaert, J.; Weis, W.I.; Kobilka, B.K. Structure of a nanobody-stabilized active state of the beta(2) adrenoceptor. Nature, 2011, 469, 175-180.
[43]
Rasmussen, S.G.; DeVree, B.T.; Zou, Y.; Kruse, A.C.; Chung, K.Y.; Kobilka, T.S.; Thian, F.S.; Chae, P.S.; Pardon, E.; Calinski, D.; Mathiesen, J.M.; Shah, S.T.; Lyons, J.A.; Caffrey, M.; Gellman, S.H.; Steyaert, J.; Skiniotis, G.; Weis, W.I.; Sunahara, R.K.; Kobilka, B.K. Crystal structure of the beta2 adrenergic receptor-Gs protein complex. Nature, 2011, 477, 549-555.
[44]
Granier, S.; Manglik, A.; Kruse, A.C.; Kobilka, T.S.; Thian, F.S.; Weis, W.I.; Kobilka, B.K. Structure of the delta-opioid receptor bound to naltrindole. Nature, 2012, 485, 400-404.
[45]
Haga, K.; Kruse, A.C.; Asada, H.; Yurugi-Kobayashi, T.; Shiroishi, M.; Zhang, C.; Weis, W.I.; Okada, T.; Kobilka, B.K.; Haga, T.; Kobayashi, T. Structure of the human M2 muscarinic acetylcholine receptor bound to an antagonist. Nature, 2012, 482, 547-551.
[46]
Manglik, A.; Kruse, A.C.; Kobilka, T.S.; Thian, F.S.; Mathiesen, J.M.; Sunahara, R.K.; Pardo, L.; Weis, W.I.; Kobilka, B.K.; Granier, S. Crystal structure of the micro-opioid receptor bound to a morphinan antagonist. Nature, 2012, 485, 321-326.
[47]
Zhang, C.; Srinivasan, Y.; Arlow, D.H.; Fung, J.J.; Palmer, D.; Zheng, Y.; Green, H.F.; Pandey, A.; Dror, R.O.; Shaw, D.E.; Weis, W.I.; Coughlin, S.R.; Kobilka, B.K. High-resolution crystal structure of human protease-activated receptor 1. Nature, 2012, 492, 387-392.
[48]
Kobilka, B. The structural basis of G-protein-coupled receptor signaling (Nobel Lecture). Angew. Chem. Int. Ed. Engl., 2013, 52, 6380-6388.
[49]
Shukla, A.K.; Manglik, A.; Kruse, A.C.; Xiao, K.; Reis, R.I.; Tseng, W.C.; Staus, D.P.; Hilger, D.; Uysal, S.; Huang, L.Y.; Paduch, M.; Tripathi-Shukla, P.; Koide, A.; Koide, S.; Weis, W.I.; Kossiakoff, A.A.; Kobilka, B.K.; Lefkowitz, R.J. Structure of active beta-arrestin-1 bound to a G-protein-coupled receptor phosphopeptide. Nature, 2013, 497, 137-141.
[50]
Thal, D.M.; Sun, B.; Feng, D.; Nawaratne, V.; Leach, K.; Felder, C.C.; Bures, M.G.; Evans, D.A.; Weis, W.I.; Bachhawat, P.; Kobilka, T.S.; Sexton, P.M.; Kobilka, B.K.; Christopoulos, A. Crystal structures of the M1 and M4 muscarinic acetylcholine receptors. Nature, 2016, 531, 335-340.
[51]
Sun, B.; Bachhawat, P.; Chu, M.L.; Wood, M.; Ceska, T.; Sands, Z.A.; Mercier, J.; Lebon, F.; Kobilka, T.S.; Kobilka, B.K. Crystal structure of the adenosine A2A receptor bound to an antagonist reveals a potential allosteric pocket. Proc. Natl. Acad. Sci. USA, 2017, 114, 2066-2071.
[52]
Kato, H.E.; Kim, Y.S.; Paggi, J.M.; Evans, K.E.; Allen, W.E.; Richardson, C.; Inoue, K.; Ito, S.; Ramakrishnan, C.; Fenno, L.E.; Yamashita, K.; Hilger, D.; Lee, S.Y.; Berndt, A.; Shen, K.; Kandori, H.; Dror, R.O.; Kobilka, B.K.; Deisseroth, K. Structural mechanisms of selectivity and gating in anion channelrhodopsins. Nature, 2018, 561, 349-354.
[53]
Kim, Y.S.; Kato, H.E.; Yamashita, K.; Ito, S.; Inoue, K.; Ramakrishnan, C.; Fenno, L.E.; Evans, K.E.; Paggi, J.M.; Dror, R.O.; Kandori, H.; Kobilka, B.K.; Deisseroth, K. Crystal structure of the natural anion-conducting channelrhodopsin GtACR1. Nature, 2018, 561, 343-348.
[54]
Liang, Y.L.; Khoshouei, M.; Radjainia, M.; Zhang, Y.; Glukhova, A.; Tarrasch, J.; Thal, D.M.; Furness, S.G.B.; Christopoulos, G.; Coudrat, T.; Danev, R.; Baumeister, W.; Miller, L.J.; Christopoulos, A.; Kobilka, B.K.; Wootten, D.; Skiniotis, G.; Sexton, P.M. Phase-plate cryo-EM structure of a class B GPCR-G-protein complex. Nature, 2017, 546, 118-123.
[55]
Zhang, Y.; Sun, B.; Feng, D.; Hu, H.; Chu, M.; Qu, Q.; Tarrasch, J.T.; Li, S.; Sun, K.T.; Kobilka, B.K.; Skiniotis, G. Cryo-EM structure of the activated GLP-1 receptor in complex with a G protein. Nature, 2017, 546, 248-253.
[56]
Gao, Y.; Cao, E.; Julius, D.; Cheng, Y. TRPV1 structures in nanodiscs reveal mechanisms of ligand and lipid action. Nature, 2016, 534, 347-351.
[57]
Huynh, K.W.; Cohen, M.R.; Jiang, J.; Samanta, A.; Lodowski, D.T.; Zhou, Z.H.; Moiseenkova-Bell, V.Y. Structure of the full-length TRPV2 channel by cryo-EM. Nat. Commun., 2016, 7, 11130.
[58]
Zagotta, W.N.; Gordon, M.T.; Senning, E.N.; Munari, M.A.; Gordon, S.E. Measuring distances between TRPV1 and the plasma membrane using a noncanonical amino acid and transition metal ion FRET. J. Gen. Physiol., 2016, 147, 201-216.
[59]
Zubcevic, L.; Herzik, M.A. Jr.; Chung, B.C.; Liu, Z.; Lander, G.C.; Lee, S.Y. Cryo-electron microscopy structure of the TRPV2 ion channel. Nat. Struct. Mol. Biol., 2016, 23, 180-186.
[60]
Chen, Q.; She, J.; Zeng, W.; Guo, J.; Xu, H.; Bai, X.C.; Jiang, Y. Structure of mammalian endolysosomal TRPML1 channel in nanodiscs. Nature, 2017, 550, 415-418.
[61]
Hirschi, M.; Herzik, M.A. Jr.; Wie, J.; Suo, Y.; Borschel, W.F.; Ren, D.; Lander, G.C.; Lee, S.Y. Cryo-electron microscopy structure of the lysosomal calcium-permeable channel TRPML3. Nature, 2017, 550, 411-414.
[62]
Rosasco, M.G.; Gordon, S.E. TRP Channels: What Do They Look Like?In: Emir TLR; Ed.SourceNeurobiology of TRP Channels, 2nd ed; CRC Press/Taylor & Francis: Boca Raton, FL, 2017. Chapter 1, pp. 1-9.
[63]
Zhang, S.; Li, N.; Zeng, W.; Gao, N.; Yang, M. Cryo-EM structures of the mammalian endo-lysosomal TRPML1 channel elucidate the combined regulation mechanism. Protein Cell, 2017, 8, 834-847.
[64]
Zhou, X.; Li, M.; Su, D.; Jia, Q.; Li, H.; Li, X.; Yang, J. Cryo-EM structures of the human endolysosomal TRPML3 channel in three distinct states. Nat. Struct. Mol. Biol., 2017, 24, 1146-1154.
[65]
Autzen, H.E.; Myasnikov, A.G.; Campbell, M.G.; Asarnow, D.; Julius, D.; Cheng, Y. Structure of the human TRPM4 ion channel in a lipid nanodisc. Science, 2018, 359, 228-232.
[66]
Duan, J.; Li, Z.; Li, J.; Santa-Cruz, A.; Sanchez-Martinez, S.; Zhang, J.; Clapham, D.E. Structure of full-length human TRPM4. Proc. Natl. Acad. Sci. USA, 2018, 115, 2377-2382.
[67]
McGoldrick, L.L.; Singh, A.K.; Saotome, K.; Yelshanskaya, M.V.; Twomey, E.C.; Grassucci, R.A.; Sobolevsky, A.I. Opening of the human epithelial calcium channel TRPV6. Nature, 2018, 553, 233-237.
[68]
Yin, Y.; Wu, M.; Zubcevic, L.; Borschel, W.F.; Lander, G.C.; Lee, S.Y. Structure of the cold- and menthol-sensing ion channel TRPM8. Science, 2018, 359, 237-241.
[69]
Zhang, Z.; Chen, J. Atomic structure of the cystic fibrosis transmembrane conductance regulator. Cell., 2016, 167, 1586-1597. e9
[70]
Liu, F.; Zhang, Z.; Csanady, L.; Gadsby, D.C.; Chen, J. Molecular structure of the human CFTR ion channel. Cell., 2017, 169, 85-95. e8
[71]
Zhang, Z.; Liu, F.; Chen, J. Conformational changes of CFTR upon phosphorylation and ATP binding. Cell., 2017, 170, 483-491. e8
[72]
Morris, E.P.; da Fonseca, P.C.A. High-resolution cryo-EM proteasome structures in drug development. Acta Crystallogr. D Struct. Biol., 2017, 73, 522-533.
[73]
van Montfort, R.L.M.; Workman, P. Structure-based drug design: Aiming for a perfect fit. Essays Biochem., 2017, 61, 431-437.
[74]
Christopher, J.A.; Orgovan, Z.; Congreve, M.; Dore, A.S.; Errey, J.C.; Marshall, F.H.; Mason, J.S.; Okrasa, K.; Rucktooa, P.; Serrano-Vega, M.J.; Ferenczy, G.G.; Keseru, G.M. Structure-based optimization strategies for G Protein-Coupled Receptor (GPCR) allosteric modulators: A case study from analyses of new Metabotropic Glutamate Receptor 5 (mGlu5) x-ray structures. J. Med. Chem., 2019, 62(1), 207-222.
[75]
Ciancetta, A.; Jacobson, K.A. Breakthrough in GPCR crystallography and its impact on computer-aided drug design. Methods Mol. Biol., 2018, 1705, 45-72.
[76]
Scapin, G.; Potter, C.S.; Carragher, B. Cryo-EM for small molecules discovery, design, understanding, and application. Cell Chem. Biol., 2018, 25(11), 1318-1325.
[77]
Tautermann, C.S. GPCR homology model generation for lead optimization. Methods Mol. Biol., 2018, 1705, 115-131.
[78]
Topiol, S. Current and future challenges in GPCR drug discovery. Methods Mol. Biol., 2018, 1705, 1-21.
[79]
Kowiel, M.; Brzezinski, D.; Porebski, P.J.; Shabalin, I.G.; Jaskolski, M.; Minor, W. Automatic recognition of ligands in electron density by machine learning. Bioinformatics, 2019, 35(3), 452-461.
[80]
Chou, K.C. Modeling the tertiary structure of human cathepsin-E. Biochem. Biophys. Res. Commun., 2005, 331, 56-60.
[81]
Cheng, X.; Xiao, X.; Chou, K.C. pLoc-mGneg: Predict subcellular localization of Gram-negative bacterial proteins by deep gene ontology learning via general PseAAC. Genomics, 2017, pii: S0888-7543. 17, 30102-30107.
[82]
Cheng, X.; Xiao, X.; Chou, K.C. pLoc-mVirus: Predict subcellular localization of multi-location virus proteins via incorporating the optimal GO information into general PseAAC. Gene, 2017, 628, 315-321.
[83]
Cheng, X.; Xiao, X.; Chou, K.C. pLoc-mPlant: Predict subcellular localization of multi-location plant proteins by incorporating the optimal GO information into general PseAAC. Mol. Biosyst., 2017, 13, 1722-1727.
[84]
Cheng, X.; Zhao, S.G.; Lin, W.Z.; Xiao, X.; Chou, K.C. pLoc-mAnimal: Predict subcellular localization of animal proteins with both single and multiple sites. Bioinformatics, 2017, 33, 3524-3531.
[85]
Cheng, X.; Xiao, X.; Chou, K.C. pLoc-mHum: Predict subcellular localization of multi-location human proteins via general PseAAC to winnow out the crucial GO information. Bioinformatics, 2018, 34, 1448-1456.
[86]
Cheng, X.; Xiao, X.; Chou, K.C. pLoc-mEuk: Predict subcellular localization of multi-label eukaryotic proteins by extracting the key GO information into general PseAAC. Genomics, 2018, 110, 50-58.
[87]
Chou, K.C.; Cheng, X.; Xiao, X. pLoc_bal-mHum: Predict subcellular localization of human proteins by PseAAC and quasibalancing training dataset. Genomics, 2018, , pii: S0888- 7543. 18, 30276-30283.
[88]
Xiao, X.; Cheng, X.; Chen, G.; Mao, Q.; Chou, K.C. pLoc_balmGpos: Predict subcellular localization of Gram-positive bacterial proteins by quasi-balancing training dataset and PseAAC. Genomics, 2018, , pii: S0888-7543. 18, 30260-X.
[89]
Chou, K.C. Impacts of bioinformatics to medicinal chemistry. Med. Chem., 2015, 11, 218-234.
[90]
Chou, K.C.; Kezdy, F.J.; Reusser, F. Kinetics of processive nucleic acid polymerases and nucleases. Anal. Biochem., 1994, 221, 217-230.
[91]
Althaus, I.W.; Chou, K.C.; Lemay, R.J.; Franks, K.M.; Deibel, M.R.; Kezdy, F.J.; Resnick, L.; Busso, M.E.; So, A.G.; Downey, K.M.; Romero, D.L.; Thomas, R.C.; Aristoff, P.A.; Tarpley, W.G.; Reusser, F. The benzylthio-pyrimidine U-31,355, a potent inhibitor of HIV-1 reverse transcriptase. Biochem. Pharmacol., 1996, 51, 743-750.
[92]
Althaus, I.W.; LeMay, R.J.; Gonzales, A.J.; Deibel, M.R.; Sharma, S.K.; Kezdy, F.J.; Resnick, L.; Busso, M.E.; Aristoff, P.A.; Reusser, F. Enzymatic kinetic studies with the non-nucleoside HIV reverse transcriptase inhibitor U-9843. Experientia, 1992, 48, 1127-1132.
[93]
Althaus, I.W.; Chou, J.J.; Gonzales, A.J.; Deibel, M.R.; Chou, K.C.; Kezdy, F.J.; Romero, D.L.; Palmer, J.R.; Thomas, R.C.; Aristoff, P.A. Kinetic studies with the non-nucleoside HIV-1 reverse transcriptase inhibitor U-88204E. Biochemistry, 1993, 32, 6548-6554.
[94]
Althaus, I.W.; Chou, J.J.; Gonzales, A.J.; Deibel, M.R.; Chou, K.C.; Kezdy, F.J.; Romero, D.L.; Thomas, R.C.; Aristoff, P.A.; Tarpley, W.G. Kinetic studies with the non-nucleoside human immunodeficiency virus type-1 reverse transcriptase inhibitor U-90152E. Biochem. Pharmacol., 1994, 47, 2017-2028.
[95]
Althaus, I.W.; Gonzales, A.J.; Chou, J.J.; Romero, D.L.; Deibel, M.R.; Chou, K.C.; Kezdy, F.J.; Resnick, L.; Busso, M.E.; So, A.G. The quinoline U-78036 is a potent inhibitor of HIV-1 reverse transcriptase. J. Biol. Chem., 1993, 268, 14875-14880.
[96]
Althaus, I.W.; Chou, J.J.; Gonzales, A.J.; Deibel, M.R.; Chou, K.C.; Kezdy, F.J.; Romero, D.L.; Aristoff, P.A.; Tarpley, W.G.; Reusser, F. Steady-state kinetic studies with the non-nucleoside HIV-1 reverse transcriptase inhibitor U-87201E. J. Biol. Chem., 1993, 268, 6119-6124.
[97]
Althaus, I.W.; Chou, J.J.; Gonzales, A.J.; LeMay, R.J.; Deibel, M.R.; Chou, K.C.; Kezdy, F.J.; Romero, D.L.; Thomas, R.C.; Aristoff, P.A. Steady-state kinetic studies with the polysulfonate U-9843, an HIV reverse transcriptase inhibitor. Experientia, 1994, 50, 23-28.
[98]
Chou, K.C.; Forsen, S. Graphical rules for enzyme-catalysed rate laws. Biochem. J., 1980, 187, 829-835.
[99]
Zhou, G.P.; Deng, M.H. An extension of Chou’s graphic rules for deriving enzyme kinetic equations to systems involving parallel reaction pathways. Biochem. J., 1984, 222, 169-176.
[100]
Zhou, G.P.; Chen, D.; Liao, S.; Huang, R.B. recent progresses in studying Helix-Helix interactions in proteins by incorporating the Wenxiang diagram into the NMR spectroscopy. Curr. Top. Med. Chem., 2016, 16, 581-590.
[101]
Zhou, G.P.; Huang, R.B. The pH-triggered conversion of the PrP(c) to PrP(sc.). Curr. Top. Med. Chem., 2013, 13, 1152-1163.
[102]
Cheng, X.; Lin, W.Z.; Xiao, X.; Chou, K.C. pLoc_bal-mAnimal: predict subcellular localization of animal proteins by balancing training dataset and PseAAC. Bioinformatics, 2018, 35(3), 398-406.
[103]
Qiu, W.R.; Xiao, X.; Lin, W.Z.; Chou, K.C. iUbiq-Lys: Prediction of lysine ubiquitination sites in proteins by extracting sequence evolution information via a gray system model. J. Biomol. Struct. Dyn., 2015, 33, 1731-1742.
[104]
Jia, J.; Liu, Z.; Xiao, X.; Liu, B.; Chou, K.C. iCar-PseCp: Identify carbonylation sites in proteins by Monte Carlo sampling and incorporating sequence coupled effects into general PseAAC. Oncotarget, 2016, 7, 34558-34570.
[105]
Jia, J.; Zhang, L.; Liu, Z.; Xiao, X.; Chou, K.C. pSumo-CD: predicting sumoylation sites in proteins with covariance discriminant algorithm by incorporating sequence-coupled effects into general PseAAC. Bioinformatics, 2016, 32, 3133-3141.
[106]
Liu, Z.; Xiao, X.; Yu, D.J.; Jia, J.; Qiu, W.R.; Chou, K.C. pRNAm-PC: Predicting N(6)-methyladenosine sites in RNA sequences via physical-chemical properties. Anal. Biochem., 2016, 497, 60-67.
[107]
Xu, Y.; Wen, X.; Shao, X.J.; Deng, N.Y.; Chou, K.C. iHyd-PseAAC: Predicting hydroxyproline and hydroxylysine in proteins by incorporating dipeptide position-specific propensity into pseudo amino acid composition. Int. J. Mol. Sci., 2014, 15, 7594-7610.
[108]
Qiu, W.R.; Sun, B.Q.; Xiao, X.; Xu, Z.C.; Chou, K.C. iHyd-PseCp: Identify hydroxyproline and hydroxylysine in proteins by incorporating sequence-coupled effects into general PseAAC. Oncotarget, 2016, 7, 44310-44321.
[109]
Qiu, W.R.; Sun, B.Q.; Xiao, X.; Xu, Z.C.; Chou, K.C. iPTM-mLys: Identifying multiple lysine PTM sites and their different types. Bioinformatics, 2016, 32, 3116-3123.
[110]
Nankabirwa, J.I.; Wandera, B.; Amuge, P.; Kiwanuka, N.; Dorsey, G.; Rosenthal, P.J.; Brooker, S.J.; Staedke, S.G.; Kamya, M.R. Impact of intermittent preventive treatment with dihydroartemisinin-piperaquine on malaria in Ugandan schoolchildren: A randomized, placebo-controlled trial. Clin. Infect. Dis., 2014, 58, 1404-1412.
[111]
Hou, T.; Zheng, G.; Zhang, P.; Jia, J.; Li, J.; Xie, L.; Wei, C.; Li, Y. LAceP: lysine acetylation site prediction using logistic regression classifiers. PLoS One, 2014, 9e89575
[112]
Qiu, W.R.; Sun, B.Q.; Xiao, X.; Xu, D.; Chou, K.C. iPhos-PseEvo: Identifying human phosphorylated proteins by incorporating evolutionary information into general PseAAC via grey system theory. Mol. Inform., 2017, 36(5-6)
[113]
Xiao, X.; Min, J.L.; Wang, P.; Chou, K.C. Predict drug-protein interaction in cellular networking. Curr. Top. Med. Chem., 2013, 13, 1707-1712.
[114]
Chou, K.C. Prediction of protein cellular attributes using pseudo-amino acid composition. Proteins, 2001, 43, 246-255.
[115]
Chen, W.; Zhang, X.; Brooker, J.; Lin, H.; Zhang, L.; Chou, K.C. PseKNC-General: A cross-platform package for generating various modes of pseudo nucleotide compositions. Bioinformatics, 2015, 31, 119-120.
[116]
Chen, W.; Lin, H.; Chou, K.C. Pseudo nucleotide composition or PseKNC: An effective formulation for analyzing genomic sequences. Mol. Biosyst., 2015, 11, 2620-2634.
[117]
Chen, W.; Lei, T.Y.; Jin, D.C.; Lin, H.; Chou, K.C. PseKNC: A flexible web server for generating pseudo K-tuple nucleotide composition. Anal. Biochem., 2014, 456, 53-60.
[118]
Medzhitov, R.; Janeway, C.A. Jr. Innate immunity: Impact on the adaptive immune response. Curr. Opin. Immunol., 1997, 9, 4-9.
[119]
Janeway, C.A. Jr. Approaching the asymptote? Evolution and revolution in immunology. Cold Spring Harb. Symp. Quant. Biol., 1989, 54(Pt 1), 1-13.
[120]
Kato, H.; Fujita, T. Autoimmunity caused by constitutive activation of cytoplasmic viral RNA sensors. Cytokine Growth Factor Rev., 2014, 25, 739-743.
[121]
Yoneyama, M.; Onomoto, K.; Jogi, M.; Akaboshi, T.; Fujita, T. Viral RNA detection by RIG-I-like receptors. Curr. Opin. Immunol., 2015, 32, 48-53.
[122]
Hornung, V.; Ellegast, J.; Kim, S.; Brzozka, K.; Jung, A.; Kato, H.; Poeck, H.; Akira, S.; Conzelmann, K.K.; Schlee, M.; Endres, S.; Hartmann, G. 5′-Triphosphate RNA is the ligand for RIG-I. Science, 2006, 314, 994-997.
[123]
Goubau, D.; Schlee, M.; Deddouche, S.; Pruijssers, A.J.; Zillinger, T.; Goldeck, M.; Schuberth, C.; Van der Veen, A.G.; Fujimura, T.; Rehwinkel, J.; Iskarpatyoti, J.A.; Barchet, W.; Ludwig, J.; Dermody, T.S.; Hartmann, G.; Reis, E.S.C. Antiviral immunity via RIG-I-mediated recognition of RNA bearing 5′-diphosphates. Nature, 2014, 514, 372-375.
[124]
Kell, A.M.; Gale, M., Jr RIG-I in RNA virus recognition. Virology, 2015, 479-480, 110-121.
[125]
Satoh, T.; Kato, H.; Kumagai, Y.; Yoneyama, M.; Sato, S.; Matsushita, K.; Tsujimura, T.; Fujita, T.; Akira, S.; Takeuchi, O. LGP2 is a positive regulator of RIG-I- and MDA5-mediated antiviral responses. Proc. Natl. Acad. Sci. USA, 2010, 107, 1512-1517.
[126]
Seth, R.B.; Sun, L.; Ea, C.K.; Chen, Z.J. Identification and characterization of MAVS, a mitochondrial antiviral signaling protein that activates NF-kappaB and IRF 3. Cell, 2005, 122, 669-682.
[127]
McWhirter, S.M.; Tenoever, B.R.; Maniatis, T. Connecting mitochondria and innate immunity. Cell, 2005, 122, 645-647.
[128]
Xu, L.G.; Wang, Y.Y.; Han, K.J.; Li, L.Y.; Zhai, Z.; Shu, H.B. VISA is an adapter protein required for virus-triggered IFN-beta signaling. Mol. Cell, 2005, 19, 727-740.
[129]
Kawai, T.; Takahashi, K.; Sato, S.; Coban, C.; Kumar, H.; Kato, H.; Ishii, K.J.; Takeuchi, O.; Akira, S. IPS-1, an adaptor triggering RIG-I- and Mda5-mediated type I interferon induction. Nat. Immunol., 2005, 6, 981-988.
[130]
Meylan, E.; Curran, J.; Hofmann, K.; Moradpour, D.; Binder, M.; Bartenschlager, R.; Tschopp, J. Cardif is an adaptor protein in the RIG-I antiviral pathway and is targeted by hepatitis C virus. Nature, 2005, 437, 1167-1172.
[131]
Xu, H.; He, X.; Zheng, H.; Huang, L.J.; Hou, F.; Yu, Z.; de la Cruz, M.J.; Borkowski, B.; Zhang, X.; Chen, Z.J.; Jiang, Q.X. Structural basis for the prion-like MAVS filaments in antiviral innate immunity. eLife, 2014, 3e01489
[132]
Xu, H.; He, X.; Zheng, H.; Huang, L.J.; Hou, F.; Yu, Z.; de la Cruz, M.J.; Borkowski, B.; Zhang, X.; Chen, Z.J.; Jiang, Q.X. Correction: Structural basis for the prion-like MAVS filaments in antiviral innate immunity. eLife, 2015, 4, 07546.
[133]
Zhou, H.; Yu, M.; Fukuda, K. Im, J.; Yao, P.; Cui, W.; Bulek, K.; Zepp, J.; Wan, Y.; Kim, T.W.; Yin, W.; Ma, V.; Thomas, J.; Gu, J.; Wang, J.A.; DiCorleto, P.E.; Fox, P.L.; Qin, J.; Li,X. IRAK-M mediates Toll-like receptor/IL-1R-induced NFkappaB activation and cytokine production. EMBO J., 2013, 32, 583-596.
[134]
Jiang, Q.X.; Chen, Z.J. Structural insights into the activation of RIG-I, a nanosensor for viral RNAs. EMBO Rep., 2011, 13, 7-8.
[135]
Okamoto, M.; Kouwaki, T.; Fukushima, Y.; Oshiumi, H. Regulation of RIG-I activation by K63-Linked polyubiquitination. Front. Immunol., 2017, 8, 1942.
[136]
Oshiumi, H.; Matsumoto, M.; Seya, T. Ubiquitin-mediated modulation of the cytoplasmic viral RNA sensor RIG-I. J. Biochem., 2012, 151, 5-11.
[137]
Peisley, A.; Wu, B.; Yao, H.; Walz, T.; Hur, S. RIG-I forms signaling-competent filaments in an ATP-dependent, ubiquitin-independent manner. Mol. Cell, 2013, 51, 573-583.
[138]
Zeng, W.; Sun, L.; Jiang, X.; Chen, X.; Hou, F.; Adhikari, A.; Xu, M.; Chen, Z.J. Reconstitution of the RIG-I pathway reveals a signaling role of unanchored polyubiquitin chains in innate immunity. Cell, 2010, 141, 315-330.
[139]
Liu, B.; Zhang, M.; Chu, H.; Zhang, H.; Wu, H.; Song, G.; Wang, P.; Zhao, K.; Hou, J.; Wang, X.; Zhang, L.; Gao, C. The ubiquitin E3 ligase TRIM31 promotes aggregation and activation of the signaling adaptor MAVS through Lys63-linked polyubiquitination. Nat. Immunol., 2017, 18, 214-224.
[140]
Oshiumi, H.; Matsumoto, M.; Hatakeyama, S.; Seya, T. Riplet/RNF135, a RING finger protein, ubiquitinates RIG-I to promote interferon-beta induction during the early phase of viral infection. J. Biol. Chem., 2009, 284, 807-817.
[141]
Lin, B.; Ke, Q.; Li, H.; Pheifer, N.S.; Velliquette, D.C.; Leaman, D.W. Negative regulation of the RLH signaling by the E3 ubiquitin ligase RNF114. Cytokine, 2017, 99, 186-193.
[142]
van Kasteren, P.B.; Beugeling, C.; Ninaber, D.K.; Frias-Staheli, N.; van Boheemen, S.; Garcia-Sastre, A.; Snijder, E.J.; Kikkert, M. Arterivirus and nairovirus ovarian tumor domain-containing Deubiquitinases target activated RIG-I to control innate immune signaling. J. Virol., 2012, 86, 773-785.
[143]
Nakhaei, P.; Genin, P.; Civas, A.; Hiscott, J. RIG-I-like receptors: sensing and responding to RNA virus infection. Semin. Immunol., 2009, 21, 215-222.
[144]
Lee, N.R.; Ban, J.; Lee, N.J.; Yi, C.M.; Choi, J.Y.; Kim, H.; Lee, J.K.; Seong, J.; Cho, N.H.; Jung, J.U.; Inn, K.S. Activation of RIG-I-mediated antiviral signaling triggers autophagy through the MAVS-TRAF6-Beclin-1 signaling axis. Front. Immunol., 2018, 9, 2096.
[145]
Jin, S.; Cui, J. BST2 inhibits type I IFN (interferon) signaling by accelerating MAVS degradation through CALCOCO2-directed autophagy. Autophagy, 2018, 14, 171-172.
[146]
Cheng, J.; Liao, Y.; Xiao, L.; Wu, R.; Zhao, S.; Chen, H.; Hou, B.; Zhang, X.; Liang, C.; Xu, Y.; Yuan, Z. Autophagy regulates MAVS signaling activation in a phosphorylation-dependent manner in microglia. Cell Death Differ., 2017, 24, 276-287.
[147]
Sun, X.; Sun, L.; Zhao, Y.; Li, Y.; Lin, W.; Chen, D.; Sun, Q. MAVS maintains mitochondrial homeostasis via autophagy. Cell Discov., 2016, 2, 16024.
[148]
Huang, X.; Yue, Y.; Li, D.; Zhao, Y.; Qiu, L.; Chen, J.; Pan, Y.; Xi, J.; Wang, X.; Sun, Q.; Li, Q. Antibody-dependent enhancement of dengue virus infection inhibits RLR-mediated Type-I IFN-independent signalling through upregulation of cellular autophagy. Sci. Rep., 2016, 6, 22303.
[149]
Lei, Y.; Wen, H.; Ting, J.P. The NLR protein, NLRX1, and its partner, TUFM, reduce type I interferon, and enhance autophagy. Autophagy, 2013, 9, 432-433.
[150]
Jin, R.; Zhu, W.; Cao, S.; Chen, R.; Jin, H.; Liu, Y.; Wang, S.; Wang, W.; Xiao, G. Japanese encephalitis virus activates autophagy as a viral immune evasion strategy. PLoS One, 2013, 8e52909
[151]
Lei, Y.; Wen, H.; Yu, Y.; Taxman, D.J.; Zhang, L.; Widman, D.G.; Swanson, K.V.; Wen, K.W.; Damania, B.; Moore, C.B.; Giguere, P.M.; Siderovski, D.P.; Hiscott, J.; Razani, B.; Semenkovich, C.F.; Chen, X.; Ting, J.P. The mitochondrial proteins NLRX1 and TUFM form a complex that regulates type I interferon and autophagy. Immunity, 2012, 36, 933-946.
[152]
Sun, J.; Desai, M.M.; Soong, L.; Ou, J.H. IFN-alpha/beta and autophagy: Tug-of-war between HCV and the host. Autophagy, 2011, 7, 1394-1396.
[153]
Liu, B.; Gao, C. Regulation of MAVS activation through post-translational modifications. Curr. Opin. Immunol., 2018, 50, 75-81.
[154]
Chow, K.T.; Gale, M., Jr; Loo, Y.M. RIG-I and other RNA sensors in antiviral immunity. Annu. Rev. Immunol., 2018, 36, 667-694.
[155]
Stone, A.E.L.; Gale, M.J. Jr. Beyond sensing: Retinoic acid inducible gene-I (RIG-I) continues to expand its antiviral effector functions. Hepatology, 2017, 65, 1792-1795.
[156]
Alvarez-Torres, D.; Gomez-Abellan, V.; Arizcun, M.; Garcia-Rosado, E.; Bejar, J.; Sepulcre, M.P. Identification of an interferon-stimulated gene, isg15, involved in host immune defense against viral infections in gilthead seabream (Sparus aurata L.). Fish Shellfish Immunol., 2018, 73, 220-227.
[157]
Chen, K.; Liu, J.; Cao, X. Regulation of type I interferon signaling in immunity and inflammation: A comprehensive review. J. Autoimmun., 2017, 83, 1-11.
[158]
Xu, D.; Zhang, T.; Xiao, J.; Zhu, K.; Wei, R.; Wu, Z.; Meng, H.; Li, Y.; Yuan, J. Modification of BECN1 by ISG15 plays a crucial role in autophagy regulation by type I IFN/interferon. Autophagy, 2015, 11, 617-628.
[159]
Radoshevich, L.; Impens, F.; Ribet, D.; Quereda, J.J.; Nam Tham, T.; Nahori, M.A.; Bierne, H.; Dussurget, O.; Pizarro-Cerda, J.; Knobeloch, K.P.; Cossart, P. ISG15 counteracts Listeria monocytogenes infection. eLife, 2015, 4e06848
[160]
Bogunovic, D.; Boisson-Dupuis, S.; Casanova, J.L. ISG15: Leading a double life as a secreted molecule. Exp. Mol. Med., 2013, 45e18
[161]
Harty, R.N.; Pitha, P.M.; Okumura, A. Antiviral activity of innate immune protein ISG15. J. Innate Immun., 2009, 1, 397-404.
[162]
Kim, K.I.; Yan, M.; Malakhova, O.; Luo, J.K.; Shen, M.F.; Zou, W.; de la Torre, J.C.; Zhang, D.E. Ube1L and protein ISGylation are not essential for alpha/beta interferon signaling. Mol. Cell. Biol., 2006, 26, 472-479.
[163]
Ritchie, K.J.; Hahn, C.S.; Kim, K.I.; Yan, M.; Rosario, D.; Li, L.; de la Torre, J.C.; Zhang, D.E. Role of ISG15 protease UBP43 (USP18) in innate immunity to viral infection. Nat. Med., 2004, 10, 1374-1378.
[164]
Liu, S.; Cai, X.; Wu, J.; Cong, Q.; Chen, X.; Li, T.; Du, F.; Ren, J.; Wu, Y.T.; Grishin, N.V.; Chen, Z.J. Phosphorylation of innate immune adaptor proteins MAVS, STING, and TRIF induces IRF3 activation. Science, 2015, 347aaa2630
[165]
Ye, J.S.; Kim, N.; Lee, K.J.; Nam, Y.R.; Lee, U.; Joo, C.H. Lysine 63-linked TANK-binding kinase 1 ubiquitination by mindbomb E3 ubiquitin protein ligase 2 is mediated by the mitochondrial antiviral signaling protein. J. Virol., 2014, 88, 12765-12776.
[166]
Liu, X.Y.; Chen, W.; Wei, B.; Shan, Y.F.; Wang, C. IFN-induced TPR protein IFIT3 potentiates antiviral signaling by bridging MAVS and TBK1. J. Immunol., 2011, 187, 2559-2568.
[167]
Gack, M.U.; Nistal-Villan, E.; Inn, K.S.; Garcia-Sastre, A.; Jung, J.U. Phosphorylation-mediated negative regulation of RIG-I antiviral activity. J. Virol., 2010, 84, 3220-3229.
[168]
Okabe, Y.; Sano, T.; Nagata, S. Regulation of the innate immune response by threonine-phosphatase of Eyes absent. Nature, 2009, 460, 520-524.
[169]
Johnsen, I.B.; Nguyen, T.T.; Bergstroem, B.; Fitzgerald, K.A.; Anthonsen, M.W. The tyrosine kinase c-Src enhances RIG-I (retinoic acid-inducible gene I)-elicited antiviral signaling. J. Biol. Chem., 2009, 284, 19122-19131.
[170]
Paz, S.; Sun, Q.; Nakhaei, P.; Romieu-Mourez, R.; Goubau, D.; Julkunen, I.; Lin, R.; Hiscott, J. Induction of IRF-3 and IRF-7 phosphorylation following activation of the RIG-I pathway. Cell. Mol. Biol., 2006, 52, 17-28.
[171]
Kouwaki, T.; Okamoto, M.; Tsukamoto, H.; Fukushima, Y.; Matsumoto, M.; Seya, T.; Oshiumi, H. Zyxin stabilizes RIG-I and MAVS interactions and promotes type I interferon response. Sci. Rep., 2017, 7, 11905.
[172]
Jiang, M.; Zhang, S.; Yang, Z.; Lin, H.; Zhu, J.; Liu, L.; Wang, W.; Liu, S.; Liu, W.; Ma, Y.; Zhang, L.; Cao, X. Self-Recognition of an inducible host lncRNA by RIG-I feedback restricts innate immune response. Cell., 2018, 173, 906-919. e13.
[173]
Han, J.; Sun, Y.; Song, W.; Xu, T. microRNA-145 regulates the RLR signaling pathway in miiuy croaker after poly(I:C) stimulation via targeting MDA5. Dev. Comp. Immunol., 2017, 68, 79-86.
[174]
Ranoa, D.R.; Parekh, A.D.; Pitroda, S.P.; Huang, X.; Darga, T.; Wong, A.C.; Huang, L.; Andrade, J.; Staley, J.P.; Satoh, T.; Akira, S.; Weichselbaum, R.R.; Khodarev, N.N. Cancer therapies activate RIG-I-like receptor pathway through endogenous non-coding RNAs. Oncotarget, 2016, 7, 26496-26515.
[175]
Pei, J.; Deng, J.; Ye, Z.; Wang, J.; Gou, H.; Liu, W.; Zhao, M.; Liao, M.; Yi, L.; Chen, J. Absence of autophagy promotes apoptosis by modulating the ROS-dependent RLR signaling pathway in classical swine fever virus-infected cells. Autophagy, 2016, 12, 1738-1758.
[176]
Chan, Y.K.; Gack, M.U. RIG-I-like receptor regulation in virus infection and immunity. Curr. Opin. Virol., 2015, 12, 7-14.
[177]
Ouda, R.; Onomoto, K.; Takahasi, K.; Edwards, M.R.; Kato, H.; Yoneyama, M.; Fujita, T. Retinoic acid-inducible gene I-inducible miR-23b inhibits infections by minor group rhinoviruses through down-regulation of the very low density lipoprotein receptor. J. Biol. Chem., 2011, 286, 26210-26219.
[178]
Jacobs, J.L.; Coyne, C.B. Mechanisms of MAVS regulation at the mitochondrial membrane. J. Mol. Biol., 2013, 425, 5009-5019.
[179]
Jacobs, J.L.; Zhu, J.; Sarkar, S.N.; Coyne, C.B. Regulation of mitochondrial antiviral signaling (MAVS) expression and signaling by the mitochondria-associated endoplasmic reticulum membrane (MAM) protein Gp78. J. Biol. Chem., 2014, 289, 1604-1616.
[180]
Pugh, C.; Kolaczkowski, O.; Manny, A.; Korithoski, B.; Kolaczkowski, B. Resurrecting ancestral structural dynamics of an antiviral immune receptor: Adaptive binding pocket reorganization repeatedly shifts RNA preference. BMC Evol. Biol., 2016, 16(1), 241.
[181]
Eckard, S.C.; Rice, G.I.; Fabre, A.; Badens, C.; Gray, E.E.; Hartley, J.L.; Crow, Y.J.; Stetson, D.B. The SKIV2L RNA exosome limits activation of the RIG-I-like receptors. Nat. Immunol., 2014, 15, 839-845.
[182]
Dixit, E.; Boulant, S.; Zhang, Y.; Lee, A.S.; Odendall, C.; Shum, B.; Hacohen, N.; Chen, Z.J.; Whelan, S.P.; Fransen, M.; Nibert, M.L.; Superti-Furga, G.; Kagan, J.C. Peroxisomes are signaling platforms for antiviral innate immunity. Cell, 2010, 141, 668-681.
[183]
Wu, B.; Hur, S. How RIG-I like receptors activate MAVS. Curr. Opin. Virol., 2015, 12, 91-98.
[184]
Luo, D.; Ding, S.C.; Vela, A.; Kohlway, A.; Lindenbach, B.D.; Pyle, A.M. Structural insights into RNA recognition by RIG-I. Cell, 2011, 147, 409-422.
[185]
Jiang, F.; Ramanathan, A.; Miller, M.T.; Tang, G.Q.; Gale, M., Jr; Patel, S.S.; Marcotrigiano, J. Structural basis of RNA recognition and activation by innate immune receptor RIG-I. Nature, 2011, 479, 423-427.
[186]
Kowalinski, E.; Lunardi, T.; McCarthy, A.A.; Louber, J.; Brunel, J.; Grigorov, B.; Gerlier, D.; Cusack, S. Structural basis for the activation of innate immune pattern-recognition receptor RIG-I by viral RNA. Cell, 2011, 147, 423-435.
[187]
Kohlway, A.; Luo, D.; Rawling, D.C.; Ding, S.C.; Pyle, A.M. Defining the functional determinants for RNA surveillance by RIG-I. EMBO Rep., 2013, 14, 772-779.
[188]
Ranjith-Kumar, C.T.; Murali, A.; Dong, W.; Srisathiyanarayanan, D.; Vaughan, R.; Ortiz-Alacantara, J.; Bhardwaj, K.; Li, X.; Li, P.; Kao, C.C. Agonist and antagonist recognition by RIG-I, a cytoplasmic innate immunity receptor. J. Biol. Chem., 2009, 284, 1155-1165.
[189]
Uchikawa, E.; Lethier, M.; Malet, H.; Brunel, J.; Gerlier, D.; Cusack, S. Structural analysis of dsRNA binding to anti-viral pattern recognition receptors LGP2 and MDA5. Mol. Cell, 2016, 62, 586-602.
[190]
Hadzic, E.; Catillon, M.; Halavatyi, A.; Medves, S.; Van Troys, M.; Moes, M.; Baird, M.A.; Davidson, M.W.; Schaffner-Reckinger, E.; Ampe, C.; Friederich, E. Delineating the Tes interaction site in Zyxin and studying cellular effects of its disruption. PLoS One, 2015, 10e0140511
[191]
Drees, B.; Friederich, E.; Fradelizi, J.; Louvard, D.; Beckerle, M.C.; Golsteyn, R.M. Characterization of the interaction between zyxin and members of the Ena/vasodilator-stimulated phosphoprotein family of proteins. J. Biol. Chem., 2000, 275, 22503-22511.
[192]
Goubau, D.; Deddouche, S.; Reis e Sousa, C. Cytosolic sensing of viruses. Immunity, 2013, 38, 855-869.
[193]
Jiang, Q.X.; Chen, Z.J. Structural insights into the activation of RIG-I, a nanosensor for viral RNAs. EMBO Rep., 2012, 13, 7-8.
[194]
Baum, A.; Sachidanandam, R.; Garcia-Sastre, A. Preference of RIG-I for short viral RNA molecules in infected cells revealed by next-generation sequencing. Proc. Natl. Acad. Sci. USA, 2010, 107, 16303-16308.
[195]
Llaguno, M.C.; Xu, H.; Shi, L.; Huang, N.; Zhang, H.; Liu, Q.; Jiang, Q.X. Chemically functionalized carbon films for single molecule imaging. J. Struct. Biol., 2014, 185, 405-417.
[196]
Yu, G.; Li, K.; Huang, P.; Jiang, X.; Jiang, W. Antibody-based affinity cryoelectron microscopy at 2.6-A resolution. Structure, 2016, 24, 1984-1990.
[197]
Pippig, D.A.; Hellmuth, J.C.; Cui, S.; Kirchhofer, A.; Lammens, K.; Lammens, A.; Schmidt, A.; Rothenfusser, S.; Hopfner, K.P. The regulatory domain of the RIG-I family ATPase LGP2 senses double-stranded RNA. Nucleic Acids Res., 2009, 37, 2014-2025.
[198]
Cui, S.; Eisenacher, K.; Kirchhofer, A.; Brzozka, K.; Lammens, A.; Lammens, K.; Fujita, T.; Conzelmann, K.K.; Krug, A.; Hopfner, K.P. The C-terminal regulatory domain is the RNA 5′-triphosphate sensor of RIG-I. Mol. Cell, 2008, 29, 169-179.
[199]
Myong, S.; Cui, S.; Cornish, P.V.; Kirchhofer, A.; Gack, M.U.; Jung, J.U.; Hopfner, K.P.; Ha, T. Cytosolic viral sensor RIG-I is a 5′-triphosphate-dependent translocase on double-stranded RNA. Science, 2009, 323, 1070-1074.
[200]
Linehan, M.M.; Dickey, T.H.; Molinari, E.S.; Fitzgerald, M.E.; Potapova, O.; Iwasaki, A.; Pyle, A.M. A minimal RNA ligand for potent RIG-I activation in living mice. Sci. Adv., 2018, 4e1701854
[201]
Allen, I.C.; Moore, C.B.; Schneider, M.; Lei, Y.; Davis, B.K.; Scull, M.A.; Gris, D.; Roney, K.E.; Zimmermann, A.G.; Bowzard, J.B.; Ranjan, P.; Monroe, K.M.; Pickles, R.J.; Sambhara, S.; Ting, J.P. NLRX1 protein attenuates inflammatory responses to infection by interfering with the RIG-I-MAVS and TRAF6-NF-kappaB signaling pathways. Immunity, 2011, 34, 854-865.
[202]
O’Neill, L.A. Innate immunity: Squelching anti-viral signalling with NLRX1. Curr. Biol., 2008, 18, R302-R304.
[203]
Koshiba, T.; Yasukawa, K.; Yanagi, Y.; Kawabata, S. Mitochondrial membrane potential is required for MAVS-mediated antiviral signaling. Sci. Signal., 2011, 4, ra7.
[204]
Yasukawa, K.; Oshiumi, H.; Takeda, M.; Ishihara, N.; Yanagi, Y.; Seya, T.; Kawabata, S.; Koshiba, T. Mitofusin 2 inhibits mitochondrial antiviral signaling. Sci. Signal., 2009, 2, ra47.
[205]
Beljanski, V.; Chiang, C.; Kirchenbaum, G.A.; Olagnier, D.; Bloom, C.E.; Wong, T.; Haddad, E.K.; Trautmann, L.; Ross, T.M.; Hiscott, J. Enhanced influenza virus-like particle vaccination with a structurally optimized RIG-I agonist as adjuvant. J. Virol., 2015, 89, 10612-10624.
[206]
Zheng, H.; Lee, S.; Llaguno, M.C.; Jiang, Q.X. bSUM: A bead-supported unilamellar membrane system facilitating unidirectional insertion of membrane proteins into giant vesicles. J. Gen. Physiol., 2016, 147, 77-93.
[207]
Wu, B.; Peisley, A.; Tetrault, D.; Li, Z.; Egelman, E.H.; Magor, K.E.; Walz, T.; Penczek, P.A.; Hur, S. Molecular imprinting as a signal-activation mechanism of the viral RNA sensor RIG-I. Mol. Cell, 2014, 55, 511-523.
[208]
Egelman, E.H. The iterative helical real space reconstruction method: surmounting the problems posed by real polymers. J. Struct. Biol., 2007, 157, 83-94.
[209]
Egelman, E.H. Single-particle reconstruction from EM images of helical filaments. Curr. Opin. Struct. Biol., 2007, 17, 556-561.
[210]
Khan, T.; Kandola, T.S.; Wu, J.; Ketter, E.; Venkatesan, S.; Lange, J.J.; Gama, A.R.; Box, A.; Unruh, J.R.; Cook, M.; Halfmann, R. Quinary structure kinetically controls protein function and dysfunction. bioRxiv, 2018, •••, 1-42.
[211]
Brubaker, S.W.; Gauthier, A.E.; Mills, E.W.; Ingolia, N.T.; Kagan, J.C. A bicistronic MAVS transcript highlights a class of truncated variants in antiviral immunity. Cell, 2014, 156, 800-811.
[212]
Kovtun, O.; Leneva, N.; Bykov, Y.S.; Ariotti, N.; Teasdale, R.D.; Schaffer, M.; Engel, B.D.; Owen, D.J.; Briggs, J.A.G.; Collins, B.M. Structure of the membrane-assembled retromer coat determined by cryo-electron tomography. Nature, 2018, 561, 561-564.
[213]
Wan, W.; Briggs, J.A. Cryo-electron tomography and subtomo-gram averaging. Methods Enzymol., 2016, 579, 329-367.
[214]
Lee, S.; Zheng, H.; Shi, L.; Jiang, Q.X. Reconstitution of a Kv channel into lipid membranes for structural and functional studies. J. Vis. Exp., 2013, (77)e50436
[215]
Qiu, L.; Wang, T.; Tang, Q.; Li, G.; Wu, P.; Chen, K. Long non-coding RNAs: Regulators of viral infection and the interferon antiviral response. Front. Microbiol., 2018, 9, 1621.
[216]
Ma, H.; Han, P.; Ye, W.; Chen, H.; Zheng, X.; Cheng, L.; Zhang, L.; Yu, L.; Wu, X.; Xu, Z.; Lei, Y.; Zhang, F. The long noncoding RNA NEAT1 exerts antihantaviral effects by acting as positive feedback for RIG-I signaling. J. Virol., 2017, 91(9), pii:e02250-e16.
[217]
Liu, Z.; Dou, C.; Yao, B.; Xu, M.; Ding, L.; Wang, Y.; Jia, Y.; Li, Q.; Zhang, H.; Tu, K.; Song, T.; Liu, Q. Ftx non coding RNA-derived miR-545 promotes cell proliferation by targeting RIG-I in hepatocellular carcinoma. Oncotarget, 2016, 7, 25350-25365.
[218]
Carnero, E.; Barriocanal, M.; Prior, C.; Pablo Unfried, J.; Segura, V.; Guruceaga, E.; Enguita, M.; Smerdou, C.; Gastaminza, P.; Fortes, P. Long noncoding RNA EGOT negatively affects the antiviral response and favors HCV replication. EMBO Rep., 2016, 17, 1013-1028.
[219]
Ingle, H.; Kumar, S.; Raut, A.A.; Mishra, A.; Kulkarni, D.D.; Kameyama, T.; Takaoka, A.; Akira, S.; Kumar, H. The microRNA miR-485 targets host and influenza virus transcripts to regulate antiviral immunity and restrict viral replication. Sci. Signal., 2015, 8, ra126.
[220]
Chiang, J.J.; Sparrer, K.M.J.; van Gent, M.; Lassig, C.; Huang, T.; Osterrieder, N.; Hopfner, K.P.; Gack, M.U. Viral unmasking of cellular 5S rRNA pseudogene transcripts induces RIG-I-mediated immunity. Nat. Immunol., 2018, 19, 53-62.
[221]
Chen, Y.G.; Kim, M.V.; Chen, X.; Batista, P.J.; Aoyama, S.; Wilusz, J.E.; Iwasaki, A.; Chang, H.Y. Sensing self and foreign circular RNAs by intron identity. Mol. Cell., 2017, 67, 228-238. e5
[222]
Hou, J.; Wang, P.; Lin, L.; Liu, X.; Ma, F.; An, H.; Wang, Z.; Cao, X. MicroRNA-146a feedback inhibits RIG-I-dependent type I IFN production in macrophages by targeting TRAF6, IRAK1, and IRAK2. J. Immunol., 2009, 183, 2150-2158.
[223]
Pestal, K.; Funk, C.C.; Snyder, J.M.; Price, N.D.; Treuting, P.M.; Stetson, D.B. Isoforms of RNA-editing enzyme ADAR1 independently control nucleic acid sensor MDA5-driven autoimmunity and multi-organ development. Immunity, 2015, 43, 933-944.
[224]
Ahmad, S.; Mu, X.; Yang, F.; Greenwald, E.; Park, J.W.; Jacob, E.; Zhang, C.Z.; Hur, S. Breaching self-tolerance to Alu duplex RNA underlies MDA5-mediated inflammation. Cell., 2018, 172, 797-810. e13
[225]
Chung, H.; Calis, J.J.A.; Wu, X.; Sun, T.; Yu, Y.; Sarbanes, S.L.; Dao Thi, V.L.; Shilvock, A.R.; Hoffmann, H.H.; Rosenberg, B.R.; Rice, C.M. Human ADAR1 prevents endogenous RNA from triggering translational shutdown. Cell., 2018, 172, 811-824. e14
[226]
Goulet, M.L.; Olagnier, D.; Xu, Z.; Paz, S.; Belgnaoui, S.M.; Lafferty, E.I.; Janelle, V.; Arguello, M.; Paquet, M.; Ghneim, K.; Richards, S.; Smith, A.; Wilkinson, P.; Cameron, M.; Kalinke, U.; Qureshi, S.; Lamarre, A.; Haddad, E.K.; Sekaly, R.P.; Peri, S.; Balachandran, S.; Lin, R.; Hiscott, J. Systems analysis of a RIG-I agonist inducing broad spectrum inhibition of virus infectivity. PLoS Pathog., 2013, 9e1003298
[227]
Chou, K.C.; Shen, H.B. Recent advances in developing web-servers for predicting protein attributes. Natural Science, 2009, 1, 63-92.
[228]
Xiao, X.; Wang, P.; Chou, K.C. GPCR-CA: A cellular automaton image approach for predicting G-protein-coupled receptor functional classes. J. Comput. Chem., 2009, 30, 1414-1423.
[229]
Xiao, X.; Min, J.L.; Wang, P.; Chou, K.C. iGPCR-drug: A web server for predicting interaction between GPCRs and drugs in cellular networking. PLoS One, 2013, 8e72234
[230]
Jia, J.; Liu, Z.; Xiao, X.; Liu, B.; Chou, K.C. iPPI-Esml: An ensemble classifier for identifying the interactions of proteins by incorporating their physicochemical properties and wavelet transforms into PseAAC. J. Theor. Biol., 2015, 377, 47-56.
[231]
Liu, B.; Yang, F.; Chou, K.C. 2L-piRNA: A two-layer ensemble classifier for identifying Piwi-interacting RNAs and their function. Mol. Ther. Nucleic Acids, 2017, 7, 267-277.
[232]
Liu, B.; Weng, F.; Huang, D.S.; Chou, K.C. iRO-3wPseKNC: identify DNA replication origins by three-window-based PseKNC. Bioinformatics, 2018, 34, 3086-3093.
[233]
Chou, K.C. An unprecedented revolution in medicinal chemistry driven by the progress of biological science. Curr. Top. Med. Chem., 2017, 17, 2337-2358.
[234]
Xu, H. Structural basis for the activation of RIG-I/MAVS antiviral immune signaling. PhD dissertation at University of Texas Southwestern Medical Center at Dallas, Texas, USA.. 2015., Page 14..

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