[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..
Download PDF Flyer