Advances in protein chemistry and structural biology, volume 101

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Academic Press is an imprint of Elsevier 225 Wyman Street, Waltham, MA 02451, USA 525 B Street, Suite 1800, San Diego, CA 92101-4495, USA The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, UK 125 London Wall, London, EC2Y 5AS, UK First edition 2015 Copyright © 2015 Elsevier Inc All rights reserved No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein) Notices Knowledge and best practice in this field are constantly changing As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein ISBN: 978-0-12-803367-8 ISSN: 1876-1623 For information on all Academic Press publications visit our website at http://store.elsevier.com CONTRIBUTORS Khaled Alawam Forensic Medicine Department, Ministry of Interior, Kuwait City, Kuwait Daniela Amicizia Department of Health Sciences (DISSAL), Via Antonio Pastore 1, University of Genoa, Genoa, Italy Claudia Andrieu INSERM, U1068, CRCM; Institut Paoli-Calmettes; Aix-Marseille University, and CNRS, UMR7258, Marseille, France Martin R Berger German Cancer Research Center, Toxicology and Chemotherapy Unit, Heidelberg, Germany Nicola Luigi Bragazzi Department of Health Sciences (DISSAL), Via Antonio Pastore 1, University of Genoa, Genoa, Italy Rossen Donev Biomed Consult Ltd., Swansea, United Kingdom Roberto Gasparini Department of Health Sciences (DISSAL), Via Antonio Pastore 1, University of Genoa, Genoa, Italy Nadya V Ilicheva Institute of Cytology RAS, St Petersburg, Russia Ilinka Ivanoska Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, Skopje, Macedonia Slobodan Kalajdziski Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, Skopje, Macedonia Sara Karaki INSERM, U1068, CRCM; Institut Paoli-Calmettes; Aix-Marseille University, and CNRS, UMR7258, Marseille, France Ljupco Kocarev Faculty of Computer Science and Engineering, University Ss Cyril and Methodius; Macedonian Academy of Sciences and Arts, Skopje, Macedonia, and BioCircuits Institute, University of California, San Diego, California, USA Aneliya Kostadinova Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria ix x Contributors Claudio Larosa Department of Surgical Sciences and Integrated Diagnostics, University of Genoa, Genoa, Italy Xi Liu Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China Albena Momchilova Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria Donatella Panatto Department of Health Sciences (DISSAL), Via Antonio Pastore 1, University of Genoa, Genoa, Italy Olga I Podgornaya Institute of Cytology RAS; Cytology and Histology Chair, Biological Faculty, St Petersburg State University, St Petersburg, Russia, and FEF University, Vladivostok Emanuela Rizzitelli Department of Health Sciences (DISSAL), Via Antonio Pastore 1, University of Genoa, Genoa, Italy Palma Rocchi INSERM, U1068, CRCM; Institut Paoli-Calmettes; Aix-Marseille University, and CNRS, UMR7258, Marseille, France Ruixian Song Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China Biljana Risteska Stojkoska Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, Skopje, Macedonia Tanya Topouzova-Hristova Faculty of Biology, Cytology, Histology and Embryology, Sofia University, Sofia, Bulgaria Daniela Tramalloni Department of Health Sciences (DISSAL), Via Antonio Pastore 1, University of Genoa, Genoa, Italy Kire Trivodaliev Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, Skopje, Macedonia Rumiana Tzoneva Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria Ivana Valle SSD “Popolazione a rischio,” Health Prevention Department, Local Health Unit ASL3 Genovese, Genoa, Italy Contributors xi Alex P Voronin Institute of Cytology RAS, and Cytology and Histology Chair, Biological Faculty, St Petersburg State University, St Petersburg, Russia Nan Wu Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China Jingwen Yang Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China Hao Zhu Bioinformatics Section, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China Hajer Ziouziou INSERM, U1068, CRCM; Institut Paoli-Calmettes; Aix-Marseille University, and CNRS, UMR7258, Marseille, France CHAPTER ONE The Eukaryotic Translation Initiation Factor 4E (eIF4E) as a Therapeutic Target for Cancer Sara Karaki*,†,{,}, Claudia Andrieu*,†,{,}, Hajer Ziouziou*,†,{,}, Palma Rocchi*,†,{,},1 *INSERM, U1068, CRCM, Marseille, France † Institut Paoli-Calmettes, Marseille, France { Aix-Marseille University, Marseille, France } CNRS, UMR7258, Marseille, France Corresponding author: e-mail address: palma.rocchi@inserm.fr Contents Introduction eIF4E's Structure and Expression 2.1 Structure 2.2 eIF4E's Expression and Regulation eIF4E's Functions 3.1 mRNA Translation Initiation 3.2 Nuclear Export eIF4E: A Therapeutic Target in Cancer 4.1 eIF4E in Cancers 4.2 EIF4E’s Mechanisms in Cancer 4.3 Targeting eIF4E in Cancers Conclusion References 2 9 11 14 14 15 16 20 21 Abstract Cancer cells depend on cap-dependent translation more than normal tissue This explains the emergence of proteins involved in the cap-dependent translation as targets for potential anticancer drugs Cap-dependent translation starts when eIF4E binds to mRNA cap domain This review will present eIF4E's structure and functions It will also expose the use of eIF4E as a therapeutic target in cancer Advances in Protein Chemistry and Structural Biology, Volume 101 ISSN 1876-1623 http://dx.doi.org/10.1016/bs.apcsb.2015.09.001 # 2015 Elsevier Inc All rights reserved Sara Karaki et al INTRODUCTION When eIF4E was discovered, it was considered as an isolated protein, not belonging to any known protein family Research of the last decade showed that all eukaryotes have several members of the eIF4E family Joshi et al (2005) identified, through sequence analysis, 411 eIF4E family members, in 230 species Three isoforms (eIFF-1, 4EHP, and eIF4E-3) are present in mammals ( Joshi, Cameron, & Jagus, 2004) Not all proteins from eIF4E’s family bind to methylguanosine mRNA cap (m7GDP) and to the same ligand ( Joshi et al., 2004; Robalino et al., 2004; Rosettani et al., 2007), which give them different physiological functions Hernandez and Vazquez-Pianzola (2005) suggested that in each organism, there is one member of the eIF4E family expressed that intervenes in translation and that other members have other functions (development, translation repression, specific mRNA nuclear transport) This hypothesis is being confirmed since eIF4E’s isoforms are thought to be involved in many functions such as spermatogenesis, oogenesis, aging, and other functions (Amiri et al., 2001; Dinkova et al., 2005; Evsikov & Marin de Evsikova, 2009; Minshall et al., 2007; Syntichaki, Troulinaki, & Tavernarakis, 2007) Cap-dependent translation starts when eIF4E binds to the mRNA cap domain Cancer cells depend on cap-dependent translation more than normal tissues ( Jia et al., 2012) This review will expose eIF4E’s structure and functions and will expose the use of eIF4E as an anticancer target eIF4E'S STRUCTURE AND EXPRESSION 2.1 Structure eIF4E’s primary structure (Fig 1A) is highly conserved in all eukaryotes because of the important role they play in the cell In the N-terminal end, sequences are variable between different organisms, but this end does not seem to be involved in the initiation to translation function The tertiary structure was characterized in mice, men, yeast, and wheat (Monzingo et al., 2007; Tomoo et al., 2002) This structure is composed of eight antiparallel β strands and three helices on the convex side (Fig 1B) eIF4E binds to the m7GDP of the mRNA cap to allow the translation initiation eIF4E tridimensional structures that interact with cap analogs were identified, allowing to identify the interaction site (Gross et al., 2003; Niedzwiecka et al., 2002; Tomoo et al., 2003) The cap interaction happens in a hydrophobic pocket eIF4E and Cancer A MATVEPETTPTPNPPTTEEEKTESNQEVANPEH YIKHPLQNRWALWFFKNDKSKTWQANLRLISK FDTVEDFWALYNHIQLSSNLMPGCDYSLFKDGI EPMWEDEKNKRGGRWLITLNKQQRRSDLDRF WLETLLCLIGESFDDYSDDVCGAVVNVRAKGDK IAIWTTECENREAVTHIGRVYKERLGLPPKIVIGY QSHADTATKSGST TKNRFVV B N-term human elF4E 4E-BP1 C-term cap-binding pocket Trp 102 Convex side N-term dorsal surface Trp 56 m GpppA C-term Concave side Figure (A) Human eIF4E's primary structure (B) eIF4E's structure Crystal structure of the human protein eIF4E (blue; dark gray in the print version) linked to the mRNA m7GDP cap (light pink; light gray in the print version) and to its ligand 4E-BP1 (green; gray in the print version) (http://atlasgeneticsoncology.org) The eIF4E interaction with the cap occurs on the concave side and requires two highly conserved tryptophan residues (Trp) The interaction between eIF4E and its ligands 4E-BPs, eIF4G, and PML occurs on the convex side on eIF4E’s concave side, due to the interaction with two highly conserved tryptophan residues (56 and 102 in mice) (Fig 1B) This interaction is stabilized by three hydrogen bonds The interaction with partner proteins involved in translation regulation, such as eIF4G or 4E binding proteins (4E-BP), takes place in a hydrophobic region on the convex side, and it involves two conserved tryptophan residues (43 and 73 in mice) (Fig 1B) These proteins interact with eIF4E through a bonding pattern, which consensus sequence is: Y(X) 4LΦ, with X being any amino acid and Φ being a hydrophobic residue The eIF4G or the 4E-BPs’ binding to eIF4E causes conformational changes which increases eIF4E’s affinity to the cap (Niedzwiecka et al., 2002; von Der Haar, Ball, & McCarthy, 2000) The PML protein (promyelocytic leukemia protein) and the viral Sara Karaki et al protein Z (VPZ) represent a second class of eIF4E regulators that intervene in the mRNA nuclear export function These proteins bind to eIF4E’s convex side using their RING domain, which, in contrast to the bond to eIF4G and 4E-BP, decreases the affinity of eIF4E to the cap (Cohen et al., 2001; Kentsis et al., 2001; Volpon et al., 2010) Structural studies show that eIF4E has different conformations and different ligand binding affinities depending on whether it is binding to the cap or not (Niedzwiecka et al., 2002; Niedzwiecka, Darzynkiewicz, & Stolarski, 2004; Volpon et al., 2006; Tomoo et al., 2002) 2.2 eIF4E's Expression and Regulation 2.2.1 Expression Cell and tissue growth depend on protein synthesis eIF4E’s expression is significantly higher in human malignant tissues than in normal tissues For cells to be viable, it is important for protein translation to be closely regulated to prevent malignant transformation and cancer development The translation control is rather at initiation, even though there are controls during elongation phase eIF4E’s activity is controlled by several mechanisms described below (Van Der Kelen et al., 2009) Although eIF4E is well studied for its role in the translation initiation and for its involvement in tumorigenesis, little is known about its expression regulation Surprisingly, eIF4E’s overexpression does not lead to a global increase in the proteins’ translation, but it leads to a selective increase in the translation of mRNAs that have a structure called “sensible elements to eIF4E” and that are involved in tumorigenesis 2.2.2 Regulation Studies show that the eIF4E inhibition can lead to HeLa cancer cell death and its absence is lethal for Saccharomyces cerevisiae When overexpressed, eIF4E can act like an oncogene, by promoting malignant transformation and lymphomagenesis in rodent cells An overproduction of eIF4E causes uncontrollable cell growth or oncogenesis, which indicates its importance in protein synthesis (Andrieu et al., 2010) Given the important function of this protein, it is not surprising to find its activity highly regulated 2.2.3 Transcription Levels Serum, growth factors, and the immunologic activation of T lymphocyte lead to an increase in the gene transcription (Schmidt, 2004) There are also eIF4E and Cancer consensus binding sites to transcription factors (such as c-Myc and hnRNPK) that are involved in the control of the gene transcription in response to stimuli (Lynch et al., 2005) For example, 4E-BP1 has at least seven phosphorylation sites among which four are known to be regulated by signaling pathways such as mTOR (Gingras, Raught, & Sonenberg, 2001; Heesom et al., 2001; Wang et al., 2005) When c-Myc is overexpressed, due to growth factors, eIF4E’s expression rises 2.2.4 Protein Level 2.2.4.1 Phosphorylation In mammals, eIF4E is phosphorylated at the 209th serine residue located in a C-terminal motif which is conserved in all species except for plants and S cerevisiae The Mnk1 and Mnk2 kinases (MAPK-integrating kinases) (Ueda et al., 2004) bind to the C-terminal end of eIF4G, to be close to eIF4E to phosphorylate it These kinases are themselves activated by phosphorylation realized by the Erk kinase (extracellular signal-regulated kinase) and by the p38 MAP kinase (Fig 2) (Scheper et al., 2001) Growth factors, phorbol esters, and insulin can activate the Mnk kinases via the Erk pathway (Tschopp et al., 2000) Cytokines and some stress conditions can activate the p38 MAP kinase pathway Phosphorylation can also be regulated during viral infection For example, during an adenovirus infection, eIF4E is dephosphorylated because the 100K viral protein binds to eIF4G and moves the Mnk kinases from the eIF4F complex The same phenomenon was observed during an influenza virus infection (Cuesta, Xi, & Schneider, 2000) However, a coronavirus infection activates Mnk1 and increases eIF4E’s phosphorylation via the p38 MaP kinase pathway (Banerjee et al., 2002) Although eIF4E’s phosphorylation mechanism is known, the consequences of this phosphorylation on translation initiation are still unclear and depend on the cellular context (Scheper & Proud, 2002) By a modulation of the Mnk–eIF4G interaction, eIF4E’s phosphorylation is controlled: eIF4G binding is controlled by MAPK-mediated phosphorylation of the Mnk1 active site Furthermore in the absence of MAPK signaling, eIF4E phosphorylation is prevented by the C-terminal domain of Mnk1 that restricts its interaction with eIF4G (Shveygert et al., 2010) 2.2.5 4E-BP The protein family 4E-BP regulates eIF4E capacity to form the cap-binding complex (eIF4F) Currently, three 4E-BPs are known in mammals: 4E-BP1, 4E-BP2, and 4E-BP3 Their interaction strength is regulated by Sara Karaki et al Serum, growth factors, lymphocyte T activation Transcription factors (cMyc, hrRNPK), Stimulis eIF4e transcription eIF4e overexpression translation of mRNA having « sensible to eIF4e elements » Tumorigenesis Figure eIF4E's expression regulation and its implication in tumorigenesis Serum, growth factors, and T-lymphocyte immunologic activation lead to an increase of eIF4E's transcription There are also consensus binding sites to transcription factors (such as c-Myc and hnRNPK) that are involved in the control of the gene transcription in response to stimuli When c-Myc is overexpressed, eIF4E's expression rises eIF4E's overexpression leads to a selective increase in the translation of mRNAs that have a structure called “sensible to eIF4E elements” and that are involved in tumorigenesis phosphorylation The 4E-BPs are phosphorylated in response to growth factors, amino acids, or hormones such as insulin which activates the mTOR pathway (molecular target of rapamycin) (Fig 3) (Gingras et al., 2001; Gingras, Raught, & Sonenberg, 2004; Kimball, 2001) For example, 4E-BP1 has at least seven phosphorylation sites, among which four are known to be regulated by signaling pathways such as mTOR (Gingras et al., 2001; Heesom et al., 2001; Wang et al., 2005) In contrast, hypoxia induces a phosphorylation decrease in 4E-BP1 (Shenberger et al., 2005) When 4E-BPs are hypophosphorylated, they can sequestrate eIF4E and 398 Vieta, E., 100–101, 114–117 Viger, R.S., 109–110 Viiri, K., 126 Vijayalakshmi, R., 254 Villa, L.L., 239–240 Villarreal, D.O., 267t, 278 Villatoro-Herna´ndez, J., 267t Vink, S.R., 29–32, 36–37, 39–41, 50–51 Vinter, V.G., 180t Virolainen, N., 150–151 Viscidi, R.P., 251–252 Visser, D.W., 216t, 218 Vitelli, V., 73 Vloon, A.P., 267t Vodyanoy, V., 158, 162t Voegel, J.C., 180t Vogler, W.R., 33, 55 Vogt, P., 80 Voiculescu, I., 169t, 178–179, 179t Voleti, B., 100, 107–110, 115t Volpon, L., 2–4 von Bohlen und Halbach, O., 99–100 von Buchwald, C., 239t von Der Haar, T., 2–4 von Hase, J., 78 Von Mering, C., 326 Von Zglinicki, T., 75 Vonka, V., 281–282 Voo, Z., 158 Voronin, A.P., 68–90, 84f, 86–88f V€ or€ os, J., 151–152, 156 Vu, T.H., 179t, 185–186 Vukelja, S.J., 30–31 W Wacholder, S., 267t Wada, K., 162t, 179t Wada, Y., 53–54, 54f Wadler, S., 267t, 279 Wadstr€ om, T., 162t, 183 Wagner, D., 325326 Wagner, K.R., 78 Waheed, M.T., 267t, 274 Waăhlisch, D., 157, 162t Waisertreiger, I.S., 78 Wakabayashi, Y., 100, 106–107, 115t Wakida, S., 155–156, 169t, 186, 189 Walczak, M., 267t, 276 Author Index Walker, S.L., 157, 162t, 182–183 Wallace, K.J., 108–109 Wallace, T.L., 106 Walsh, D., 176 Walsh, D.M., 110–111 Walter, J., 78 Walterscheid, J.P., 32–33 Walzi, E., 285t Wan, B., 82–83 Wan, J., 162t Wan, Y., 127 Wanderley, M.S., 235 Wandl, S., 285t Wanekaya, A.K., 189 Wang, A.S., 78 Wang, B., 216t, 224 Wang, C., 235 Wang, D.B., 162t, 187, 266–273, 285t Wang, E., 256 Wang, G., 285t Wang, H., 83 Wang, H.H., 216t, 218 Wang, H.T., 216t, 223 Wang, J., 151, 156, 160–161, 162t, 172, 182–183, 326–327 Wang, J.F., 168 Wang, J.K., 127 Wang, J.W., 235, 247t, 250–251, 267t, 278, 285t Wang, J.Z., 330–331 Wang, K., 168, 251, 262 Wang, K.F., 158–159, 184 Wang, L., 53, 162t, 168 Wang, L.Q., 30–31 Wang, M., 216t, 224 Wang, M.C., 284, 285t Wang, Q., 275 Wang, R., 14–15, 160–161, 162t, 182–183 Wang, S., 169t, 179t, 184–185 Wang, S.H., 177, 180t Wang, T.L., 279 Wang, T.S., 253 Wang, W., 169t, 256 Wang, X., 4–7, 30–32, 281–282 Wang, X.G., 285t Wang, X.W., 168 Wang, Y., 162t, 169t, 177–178, 179t, 182–183, 266–273, 285t Author Index Wang, Z., 158–159, 184, 188, 254, 267t, 276, 285t Wang, Z.Y., 30–31 Wang, Z.Z., 266–273 Wangchareansak, T., 160–161, 162t Wangmaung, N., 162t, 172–173 Wanner, G., 78 Wanram, S., 162t, 174–175, 174t Ward, M., 156 Ward, V., 267t Warda, A.K., 216t, 218 Warner, I.M., 187 Wasanapiarnpong, T., 224 Wasserman, G.M., 166 Wasson, C.W., 256 Watanuki, T., 100, 106–107, 115t Watson, C.M., 71 Watson, M., 235 Waudby, C.A., 180t Way, A.S., 169t Weaver, D.R., 110 Weaver, R.H., 324 Webb, E.C., 324–325 Webster, M.J., 107–108 Weckman, N.E., 159 Weghofer, M., 267t Wei, H.P., 162t, 187, 216t, 224 Wei, J., 107–108 Wei, J.J., 30–31 Wei, M., 251, 262 Wei, S., 41–43 Wei, X., 285t Weickert, C.S., 108–109 Weidler, C., 30–31 Weinberger, K., 162t Weiner, D.B., 267t, 278 Weintraub, E., 160 Weiss, C., 285t Weiss-Steider, B., 267t, 285t Welch, M.E., 162t Welchner, E., 285t Welland, M.E., 180t Welters, M.J., 267t Weltzien, H.U., 29 Wen, H.W., 184–185 Wen, Q., 180t Wen, Y., 162t, 170–171 Wendel, H.G., 14–15 399 Weng, T.C., 177, 180t Weng, Z., 251, 262 Wensheng, L., 267t Wenzel, J., 37–39 Wesierska-Gadek, J., 285t West, S.C., 70–71 Westman, B., 19 Westmoreland, D., 267t, 276–277 Westphal, O., 29, 32–33 Wever, P.C., 214–215, 216t, 218 Wheeler, C.M., 265, 267t Whelan, S., 139 White, E.A., 254, 260 White, P.W., 267t, 276–277, 285t White, W.I., 274 Whittle, N.R., 267t, 280 Whyte, W.A., 126 Wiecek, A., 45 Wiedemann, I., 159 Wieder, T., 55 Wielinga, P.R., 181 Wiens, M.E., 261–262 Wiesner, B., 37–39 Wiggins, C.H., 334 Wijesinghe, C.A., 169t Wilczynski, S., 267t Wilkinson, G.W., 267t, 276–277 Will, H., 252 Willeke, K., 177 Willett, C.G., 239t Williams, C., 261 Williams, C.L., 53 Willis, A.E., 9, 19–20 Willner, I., 162t, 168, 169t, 171, 178, 185 Wilson, D.B., 109–110 Wilson, G.S., 151–152 Wilson, I.C., 101 Wilson, L., 103–104 Wilson, M., 267t Wilson, S.S., 261–262 Winkler, M., 260 Winnett, M.T., 267t, 279 Winnubst, L., 216t, 223 Winters, U., 267t, 280, 285t Wirtanen, G., 162t, 183–184 Wischnewski, H., 73 Wise, M.C., 267t, 278 Witos, J., 176, 180t 400 Wittkop, T., 325 Wolf, G., 157, 162t Wolf, H., 155–156, 162t Wolf, P., 32–33 Wolff, A., 109–110 Wong, D.T., 156–157, 162t Wong, E.H., 101 Wong, P.K., 155–156 Wong, S.M., 162t Wong, S.T., 28 Wong, Y.Y., 162t Wongphaet, N., 224 Wood, A.M., 89 Wood, G.C., 214 Wood, L.M., 267t, 278 Wood, N.H., 235 Wood, R., 29 Workman, P., 32–33, 49–50 Wortley, P.M., 160 Wright, D.W., 160–161, 162t Wright, T.C., 277–278 Wright, W.E., 68–69 Wrobel, A., 101 Wu, A., 267t, 278, 284, 285t Wu, B.H., 267t, 279 Wu, B.M., 156–157, 162t Wu, H.B., 267t, 279 Wu, J., 82–83, 162t, 256 Wu, J.C., 174–175, 174t Wu, J.Y., 73–74 Wu, L., 76, 169t Wu, M., 326 Wu, N., 126–146 Wu, Q., 158–159, 184 Wu, R., 162t, 167 Wu, T.C., 266–273, 267t, 276, 278–279, 281–282, 284, 285t Wu, T.Z., 162t, 172 Wu, T.-Z., 162t, 172 Wu, V.C., 162t, 182–183 Wu, X.Y., 30–31 Wurst, W., 109–110 Wyatt, H.D.M., 70–71 Wyler, M., 261 Wysocki, J., 264–265, 267t X Xi, Q., Xia, J., 162t, 172 Author Index Xia, N., 262 Xia, Y., 157, 162t, 179t, 267t, 273–274, 283 Xiang, Q., 167, 326 Xiao, L.D., 216t, 219–220 Xiaohua, W., 156 Xie, X., 254, 267t, 276, 285t Xiong, F., 151 Xiong, Y., 72 Xu, B., 326–327 Xu, C.F., 127, 142 Xu, D., 266–273 Xu, J., 167 Xu, K., 179t Xu, L., 169t Xu, X., 267t, 275 Xu, Y., 162t, 267t, 273–275 Xuan, Y., 215, 216t Xue, B., 258, 260–261 Xue, Z.L., 169t, 179t Xukui, L., 267t Y Yadav, A., 274, 283–284, 285t Yadav, I.S., 274, 283–284, 285t Yaginuma, Y., 259 Yagur-Kroll, S., 216t, 223 Yakovleva, M.E., 162t, 183 Yalamanchili, S., 162t Yamanaka, H., 151–152 Yamasaki, A., 169t Yamayoshi, A., 285t Yamazaki, S., 110 Yan, H., 158, 174t, 176, 180t Yan, J., 254, 267t, 278, 284 Yan, Q., 258 Yan, S., 169t Yan, S.C., 30–31 Yan, X., 266–273, 325–326 Yan, Y., 19, 267t Yanagida, M., 80–81 Yanatatsaneejit, P., 259 Yanez, G., 83 Yang, B., 267t Yang, C., 159 Yang, C.L., 266–273 Yang, D., 72 Yang, H.G., 262, 267t, 285t Yang, H.H., 162t, 170–172 Yang, H.-H., 162t, 172 401 Author Index Yang, J., 126–146 Yang, J.J., 177, 180t Yang, K.L., 169t Yang, L., 162t, 182–183 Yang, M., 162t, 171 Yang, P., 172–174, 174t Yang, R.F., 162t, 187, 251–252 Yang, S.X., 14–15 Yang, X., 162t, 183, 266–274, 267t, 283 Yang, Y., 82–83, 258, 326 Yang, Y.K., 184–185 Yang, Y.L., 30–31, 162t, 172 Yang, Z., 30–31, 134, 136–139, 145, 326–327 Yano, K., 169t Yao, C., 30–31, 162t, 167, 172 Yao, C.Y., 162t, 189 Yao, J., 178, 179t Yao, L., 54f Yao, S., 157, 162t Yao, W., 168, 169t Yao, Y., 267t, 273–274, 283 Yardley, V., 36–37 Yasuda, M., 216t, 224 Yasui, H., 30–31 Yasuike, M., 216t, 218 Yatham, L.N., 100–101, 114–117 Yau Li, S.F., 179t Ye, G.W., 285t Ye, M., 260 Ye, P.D., 215, 216t Ye, R., 162t, 182–183 Ye, S., 169t Ye, W.W., 216t, 219–220 Yeatermeyer, J., 267t, 276 Yeo-Teh, N.S., 258 Yi, S., 262, 267t, 285t Yi, W.J., 216t, 220 Yim, E.K., 285t Yin, J., 82–83 Yin, R., 267t, 283 Ying, Y., 162t, 182–183 Yiu, S.M., 326 Yoakim, C., 267t, 276–277, 285t Yokoyama, T., 216t, 224 Yola, M.L., 184–185 Yong, L., 169t, 179t Yoo, J., 285t Yoon, J.H., 169t Yoon, J.K., 276 Yoshida, M., 329 Yoshida, T., 127 Yoshimoto, M., 169t, 186, 259 Yoshinari, M., 159 Yosifov, D.Y., 36–37 You, J., 254, 284 Young, L.T., 102, 110 Young, V., 267t Yrazu, F., 216t, 223 Yu, H., 262, 329 Yu, J., 266–273 Yu, J.S., 162t, 172 Yu, K., 19–20 Yu, K.A., 285t Yuan, L., 277–278 Yue, P., 30–31 Yue, P.L., 216t, 224 Yue, Y., 256 Yugawa, T., 253 Yuqing, M., 156 Yusibov, V., 263 Yutzy, W.H., 251–252 Z Zaharieva, M.M., 36–37, 46–47, 53 Zahedifard, F., 267t Zahin, M., 267t Zajecka, J.M., 101 Zalensky, A.O., 80–81 Zˇaln_eravicˇius, R., 216t, 220 Zamaleeva, A.I., 180t Zaman, M., 267t, 273–274, 283 Zanolini, A., 267t, 281–282 Zanoni, M.V.B., 151–152 Zanotto, C., 276 Zaragosi, L.E., 72 Zarbl, H., 285t Zarnitsyn, V., 267t, 274–275 Zavala-Flores, L.M., 267t Zayats, M., 162t, 171 Zeephongsekul, P., 162t, 171–172 Zeisig, R., 37–41 Zeller, W.J., 37–39 Zeng, K., 157, 162t Zeng, Q., 284, 285t Zeng, X., 155–156, 158, 169t, 174t, 176, 180t, 188 Zenin, V.V., 79–81 402 Zentgraf, H., 267t, 278 Zerp, S.F., 29–32, 53 Zhai, F., 285t Zhai, S., 30–31 Zhan, Y., 53 Zhang, B., 180t, 256 Zhang, C., 53–54 Zhang, H., 162t, 169t, 267t Zhang, H.L., 254, 267t, 276, 285t Zhang, H.T., 105–106 Zhang, J., 136–139, 145, 157, 162t, 169t, 174, 177, 179t, 258, 285t Zhang, K., 325–326 Zhang, L., 256 Zhang, Q., 216t, 224 Zhang, S., 172–174, 174t, 216t, 224 Zhang, S.W., 285t Zhang, T., 254, 267t, 276, 285t Zhang, W., 178, 179t, 216t, 224, 251, 260, 262 Zhang, X., 162t, 187, 251, 262 Zhang, Y., 53, 127, 162t, 169t, 170–171, 179t, 184–185, 216t, 219–220, 258, 326–327 Zhao, J., 100, 104–105, 115t, 127 Zhao, K.N., 256 Zhao, L., 256 Zhao, M., 180t Zhao, Q., 262 Zhao, R., 169t, 179t Zhao, W., 285t Zhao, X., 285t Zhao, X.S., 216t, 223 Zheng, D., 169t Zheng, H., 109 Zheng, J., 266–273, 285t Zheng, Q., 167 Zheng, Y., 41–43, 285t Zhong, G., 329 Zhong, H.-J., 70f Zhong, Z., 81–82 Zhou, H., 285t Zhou, J., 285t, 326 Zhou, L., 71, 178, 179t Author Index Zhou, Q., 187 Zhou, T., 173–174, 174t Zhou, X., 162t, 168 Zhou, X.C., 169t, 186 Zhou, X.J., 325–326 Zhou, X.L., 108–109 Zhou, Y., 109 Zhou, Z.R., 83 Zhu, D., 260 Zhu, D.R., 162t Zhu, H., 126–146 Zhu, J., 31–32 Zhu, L., 30–31 Zhu, Q., 162t Zhu, T., 162t, 167 Zhu, W., 222–223 Zhu, X.-D., 74–76, 89 Zhu, Y., 167 Zhuang, X., 73–74 Zhurov, V.G., 79–80 Zille, A., 216t, 224 Zillmann, U., 36–37 Zimmer, R., 326 Zimmer, S.G., 11–16 Zimmerman, G.A., 32–33 Zimmerman, G.R., 162t Ziouziou, H., 2–21 Zisman, E., 162t, 168 Zitka, O., 160, 162t Ziv, E., 334 Ziya Oztuărk, Z., 179t Zosso, N., 266–273, 267t Zou, C., 285t Zu, Y., 156 Zubair, A., 267t, 276 Zueger, C., 188 Zumbach, K., 281–282 Zunhammer, A., 78–79 Zuo, G.M., 162t, 187 zur Hausen, H., 233, 239–240, 285t Zwang, T.J., 173–174 Zwerger, M., 78 Zwerschke, W., 260 Zwietering, M.H., 214–215, 216t SUBJECT INDEX Note: Page numbers followed by “f ” indicate figures and “t ” indicate tables A Acquired immunodeficiency syndrome (AIDS), 168–171 Adjuvanted vaccines of HPV, 274 Agrobacterium tumefaciens, 274 AIDS See Acquired immunodeficiency syndrome (AIDS) AKT-mTOR Ras/Raf, activation of, 53–55, 54f ALDH9A1, 104–105 Alkylphosphocholines (APCs), 36–37, 41–43 Alkylphospholipids (APLs), 29–30, 32–33 anticancer mechanisms of, 40–41 on cell cycle and mitosis, 49–50 chemical structures, 34f in lipid rafts, 47–49 mechanisms of, 46f signal transduction pathways, 52, 52f ALPs See Antitumor lipids (ALPs) Alternative telomere lengthening (ALT) pathway, 71 AMPs See Antimicrobial peptides (AMPs) Antenatal depression, 98 Antidepressant treatments, 100–102 Antimicrobial peptides (AMPs), 158–159, 221 Anti-MTBP AB, 85–87, 87f Antisense oligonucleotides (ASOs), 17–18 Antitumor lipids (ALPs) APLs effect on cell cycle and mitosis, 49–50 biological processes and targets affected by, 48f, 49 clinical trials, 37–40 development of, 29 and electroporation, 32 interference with phospholipid metabolism, 50–51 Kaplan–Meier survival curves, 39–40 in leukemic cells, 41–49 lipid rafts, membrane localization, 40–41 and mTOR inhibitors, 30–31 and radiation, 31–32 signaling molecules, 42f in solid tumor cells, 41–49 structure of, 32–37 therapeutic effect, 37–40 APLs See Alkylphospholipids (APLs) Aptamers, 156, 180–181 Area under curve (AUC), 340 for SHOPIN, 344–346, 344t ASOs See Antisense oligonucleotides (ASOs) Association-based approach, 325–326 Atherosclerosis, 176 ATM kinase pathway, 74–75, 75f ATR kinase pathway, 75–76 Attachment plaques, 87 AUC See Area under curve (AUC) Avian influenza virus (AIV) H5N1, 160–161 B Bacillus sp B anthracis, 187 B cereus, 183–184 B subtilis, 215 B thuringiensis, 187 Bacterial-based vaccines prophylactic HPV vaccines, 266–273 therapeutic HPV vaccines, 275–276 Bacteria, quartz-crystal microbalance and, 156–159 Batch CD-Search program, 145 Bcl-2, 41–43 Bcl-XL, 41–43 BGLL algorithm, 338–339 Biochemical oxygen demand (BOD) biosensor, 220 Biohazards, 187–188 Biosensors See also Sensors electrochemical, 151–152 optical, 151 probing/reacting, 152 quartz-crystal microbalance, 151–152, 154f 403 404 Bioterrorism, 187–188 Bipolar depression, 98 BOD biosensor See Biochemical oxygen demand (BOD) biosensor Branch-site models, 136–139 Breakbone fever See Dengue fever Breast cancer eIF4E, 14–16 MDR in, 37–40 quartz-crystal microbalance, 174 treatment, 32 Butterworth–van-Dyke (BVD) model, 155 C Calorimetric sensors, 152 cAMP response element binding protein (CREB), 102, 106, 257 Campylobacter jejuni (C jejuni), 183 Cancers eIF4E in, 14–20 QCM for detection of, 173–175, 174t Cap-binding complex (CBC), eIF4E, 11–13 CaP-dependent translation initiation, eIF4E, 9–10 CaP-independent translation initiation, eIF4E, 10 CAPS, 140, 146 Capsomers-based vaccines prophylactic HPV vaccines, 274 therapeutic HPV vaccines, 283 Carrageenan (CG)-based vaccine, 274 Caveolins, 41–43 Cell cycle arrest, in G2/M phase, 32, 55 Cell-mediated immunity (CMI), 264 Centromere protein C (CENP-C), 259 Cervarix, 265 CG-based vaccine See Carrageenan (CG)-based vaccine Charged-coupled device (CCD), porous aluminum, 215f Chemotherapeutic agents, 28 Chlamydia trachomatis (C trachomatis), 168 Chromatin organization, telomeres in, 77–81 Chromosomal ends, telomeres protecting, 70–71 Chromosomal rearrangements, in Drosophila, 68 Subject Index Chromosome territory (CT), 77–81 Chronic degenerative diseases, 175–177, 180t Circadian genes, depression and, 110–111 Clostridium perfringens, 184 Cluster extraction, 335–337 Cluster functional enrichment, 337–338 Clustering-based approach, 325–326 CMI See Cell-mediated immunity (CMI) Concanavalin A (Con A), 158 Conserved Domain Database (CDD), 128, 131–134, 145 Content-based weights, 332 Convergent evolution, 139 Corticotrophin-releasing hormone (CRH) family, 112 CPEB protein, 8–9 CREB See cAMP response element binding protein (CREB) C-strand of telomere, 68–69 Cyclic adenosine monophosphate (cAMP), 102 Cyclothymic disorder, 98 D DBD domain See DNA-binding dimerization (DBD) domain DDR See DNA-damage response (DDR) Death-inducing signaling complex (DISC), 41–43 Death receptors (DRs), 30–31 Delayed Explosion Model, 143 Dendritic cell-based vaccines, 281–283 Dengue fever, 172 Depression amine hypothesis of, 100–101 antidepressant treatments, 100–102 circadian genes, 110–111 definition, 98 etiology of, 99–100 GABA receptors, 102 general practitioners, 113–114 intracellular signaling pathways, 105–106 and neurotransmitter systems, 103–105 neurotrophic factors, 106–107 pathophysiology of, 99–100, 103 profiling expression pattern, 113–117 significant alteration in, 115t 405 Subject Index synapse-related genes, 107–108 transcription factors and, 108–110 types of, 98–99 Diabetes, 176 Dissipation factor of QCM, 155 DNA-based vaccines, 277–279 DNA-binding dimerization (DBD) domain, 253 DNA-damage response (DDR), 252 Dopamine (D3) receptor, 101 Dopamine reuptake inhibition, 101 Double-strand breaks (DSBs), 70 Drosophila chromosomal rearrangements in, 68 PRC2 proteins, 126 Dysthymic disorder, 99 E Ebola virus, 172 4E-BP regulation of eIF4E, 5–7 Edelfosine, 32–33, 35, 35t apoptotic and cytostatic effect, 49–50 cell uptake of, 43–45, 44f Edge-based approaches, 330 EdgeCluster algorithm, 338–339 EDS See Episodic diversifying selection (EDS) Eed See Extra sexcombs (Eed) eIF4E See Eukaryotic translation initiation factor 4E (eIF4E) Electrochemical biosensors, 151–152 Electrochemical impedance spectroscopy (EIS) immunosensor, 222 Electrochemical QCM (EQCM), 156, 158 Electroporation, ALPs, 32 Endoplasmic reticulum (ER), 47–49, 47f Enhancer of zeste (Ezh1) frameshift mutations in, 130–131 homologous sequences, 129f, 135f NMD transcripts, 130–131, 134–136 Enhancer of zeste (Ezh2) coevolution, 141f homologous sequences, 129f, 135f and lncRNAs, 127 ncRNA binding in, 142 NMD transcripts, 130–131 phylogenetic trees, 136f Environmental monitoring porous aluminum, 224 quartz-crystal microbalance, 186–187 Episodic diversifying selection (EDS), 137t Epitope imprinting technique, 170–171 EQCM See Electrochemical QCM (EQCM) Erucylphosphocholine (ErPC), 31–32, 36–37 Erufosine, 36–37 Escherichia coli food-borne pathogens, 182–183 porous aluminum, 219–221 quartz-crystal microbalance, 158–159 Eukaryotic translation initiation factor 4E (eIF4E), antisense oligonucleotides, 17–18 and eIF4G, 18–19 expression, and Hsp27, 20 inhibitors, 17f, 18–19 m7GDP structure, 2–4, 9–10 mRNA cap analogs, 19 mRNA translation initiation, 9–10 in N-terminal end, 2–4 nuclear export, 11–13, 12f protein level, regulation of, sensitive to, 11–13 siRNAs, 17–18 structure, 2–4, 3f therapeutic target in cancer, 14–20 transcription levels, 4–5 upstream pathway inhibitors, 19–20 Extra sexcombs (Eed) coevolution, 141f mammalian-specific insertion in, 128 placentals-specific insertion in, 129f Ezh1 See Enhancer of zeste (Ezh1) F False-negative (FN) event, 339–340, 341t, 345t Fas-associated death domain-containing protein (FADD), 41–43 FC algorithm, 338–339 Field-effect transistors (FETs), 151–152 Flotillin, 41–43 FN event See False-negative (FN) event 406 Food-borne pathogens, 182–184 Food hygiene, 181 allergens, 184–185 food-borne pathogens, 182–184 genetically modified organisms, 185–186 micronutrients, 185 mycotoxins, 184 pesticides, 185 porous aluminum, 222 Food safety hazards, 181–182 FOXD3, 109 Francisella tularensis (F tularensis), 188 Freundlich–Langmuir isotherm model, 219 G GABAA receptor beta (GABRB2), 104–105 GABA receptors, 102 GAGs See Glycosaminoglycans (GAGs) Gardasil, 265 Gardasil 9, 266 GATA1, 108–110 Gene ontology (GO), 324–325 Genetically modified organisms (GMOs), 185–186 GENEWISE, 144–145 Genome, human papillomaviruses, 239–240 Glial cell line-derived neurotrophic factor (GDNF), 106–107 Global optimization-based approach, 325–326 Glutamate–ammonia ligase (GLUL), 104–105 Gly/Arg-rich (GAR) domain, 83 Glycosaminoglycans (GAGs), 260–261 GMOs See Genetically modified organisms (GMOs) G-quadruplexes, 69, 70f G-rich strand of telomere, 68–69 GTF file of human genome, 144–145 H Hayflick limit, 68, 70–71 Heparan sulfate proteoglycans (HSPGs), 260–261 Hepatitis B virus (HBV) diagnosis, 166–167 quartz-crystal microbalance, 166–168 Subject Index Herpes simplex virus (HSV), 171 HIV infection See Human immunodeficiency virus (HIV) infection Homeland security, 188 Homodimerization domain, 82 Homology-directed repair (HDR), 76 Hormone changes, 99–100 HPVs See Human papillomaviruses (HPVs) Hsp27–eIF4E interaction, 20 HSPGs See Heparan sulfate proteoglycans (HSPGs) HSV See Herpes simplex virus (HSV) 5-HT transporter, 101–102 Human immunodeficiency virus (HIV) infection, 168–171 Human leukemic cells, 31–32, 41–45, 53 Human papillomaviruses (HPVs), 233 alpha-HPV, 233 anogenital diseases, 235, 236t beta-HPV, 233 classification, 233–234t combinational therapy, 284–292, 285t detection technology, 235, 238t emerging drugs against, 285t E1 protein, 252–253 E2 protein, 253–255 E3 protein, 255 E4 protein, 255–256 E5 protein, 256–257 E6 protein, 257–258 E7 protein, 258–260 E8 protein, 260 functional characterizations of, 245t genome, 239–240 life cycle, 260–262 L1 protein, 250 L2 protein, 250–252 in non-anogenital cancers, 239t nucleic acid-based vaccines, 267t papillomavirus cladogram, 234f plant-based vaccines, 263, 267t prophylactic vaccines, 264–275 protein data bank, 241t proteins interaction, 247t proteome, 240–249 recombinant-based vaccines, 263–264 risks of, 233, 234t socioeconomic burden, 235 407 Subject Index therapeutic vaccines, 264, 275–284 upstream regulatory region, 239–240 vector-based vaccines, 267t virus-like particles based vaccines, 251, 262–263, 267t whole cell-based vaccines, 267t Hybrid weights, 333 Hypothalamic–pituitary–adrenal (HPA) axis, 111–112 I IgG anti-nucleoprotein, 160 Ilmofosine, 35, 36t Influenza virus, 160–165 Information content (IC), 330–331 Insect-based vaccines of HPV, 273 Intracellular signaling pathways, depression, 105–106 Ion-selective FETs (ISFETs), 151–152 J Jaccard metric, 340–343 JTT models, 139 Jumonji, ARID domain-containing protein (Jarid2) homologous sequences, 128 human sequence, 130f positive selections, 136–137, 138f L Label-free devices, 155–156, 158 Lactobacillus rhamnosus, 221–222 Lactococcus lactis (L lactis), 266–273, 275–276 Lamina-associated domains (LADs), 78 L2-based vaccines of HPV, 275 Leishmania chagasi, 180–181 Leukemic cells, ALPs in, 41–49 Lipid rafts APLs in, 47–49 membrane localization, 40–41 Listeria monocytogenes, 184, 276 Litoria fallax, 159 L1/L2 chimeras, 275 LncRNAs, 127 Low-dose perifosine, 30–31 L1 protein of HPV, 250 L2 protein of HPV, 250–252 2-Lysophosphatidylcholine (LPC), 29 M Major depressive disorder (MDD), 98 in adrenoceptor density, 101 dorsolateral prefrontal cortex, 107–108 dysregulated in, 108–109 expression biomarkers for, 103–104 glutamatergic transmission in, 104 locus coeruleus in, 103 neurotrophic factors, 107 pathophysiology, 110 prevalence of, 99 risk for, 99–100 Malaria, 172–173 Mammalian target of rapamycin (mTOR) pathway, 112 Mammals, PRC2 genes insertions in, 128–131, 129–130f Manic depression See Bipolar depression MDD See Major depressive disorder (MDD) MEGA 6.0, 146 Melancholia, 98 Membrane telomere-binding protein (MTBP) localization of, 86–87, 88f prometaphase, 87–89 with telomeric DNA, 83 Methicillin-sensitive S aureus (MSSA), 158 7-methylguanosine (m7GDP) structure, 2–4, 9–10 Metric space transformation, 334–335 Microbiology, 214–218 Micronutrients, 185 Miltefosine, 36–39 Mitogen-activated protein kinase p38 (p38-MAPK), 102 Modified vaccinia virus Ankara (MVA), 277 Most informative common ancestor (MICA), 331 mRNA cap analogs, eIF4E, 19 mRNA translation initiation, eIF4E, 7f, 9–10 CaP-dependent translation initiation, 9–10 CaP-independent translation initiation, 10 MTBP See Membrane telomere-binding protein (MTBP) mTOR pathway See Mammalian target of rapamycin (mTOR) pathway 408 Multidrug resistance (MDR) mechanisms, 28 Multiple myeloma (MM) cells, 30–31, 37–39 Mycobacterium tuberculosis (M tuberculosis) porous aluminum, 218 quartz-crystal microbalance, 173 Mycotoxins, 184 Myeloid-derived suppressor cells (MDSCs), 284 N Nanobiomaterials-based sensors, 150–151 Nanomedicine, 152 Nanosensors of QCM, 151–152 Nanotechnologies-based vaccines prophylactic HPV vaccines, 275 therapeutic HPV vaccines, 283 ncRNAs See Noncoding RNAs (ncRNAs) NE See Nuclear envelope (NE) Neighborhood-based approach, 325–326 Neisseria meningitidis, 171 Neurotransmitter systems, 103–105 Neurotrophic factors of depression, 106–107 N-methyl-D-aspartate (NMDA), protein level, 104 Node-based approaches, 330 Noncoding RNAs (ncRNAs), 126 Nonhomologous end-joining (NHEJ) in chromosome fusions, 76 repression of, 75f Nonsense-mediated decay (NMD) transcripts, 134–136 Norepinephrine, 101 Normalized Jaccard Index, 332 Nosocomial infections, 157 NR2A/B proteins, 104–105 Nuclear envelope (NE), 80–81, 85–90 Nuclear export, eIF4E, 11–13, 12f Nuclear lamina, 81 Nucleic acid-based vaccines, 267t O Occupational hygiene, 177 ODPC, 46–47, 46f Optical biosensors, 151 Osteoarthritis, 177 Subject Index P Papillomavirus cladogram, 234f See also Human papillomaviruses (HPVs) Pathogen detection, porous aluminum, 219–220 Peptide-based vaccines of HPV, 280–281 Perifosine, 31–32, 36–39 Pesticides, 185 Phosphodiesterase type 4A (PDE4A) in depression, 105–106 Phosphoinositide-dependent kinase (PDK1), 53–54 Phospholipid metabolism, 50–51 Phosphorylation, eIF4E mechanism, Piezoelectric mass-sensing devices, 151 PINs See Protein interaction networks (PINs) Plant-based vaccines human papillomaviruses, 263, 267t prophylactic HPV vaccines, 274 Plasmodium sp P falciparum, 172–173 P vivax, 172–173 Platelet-activating factor (PAF), 32–33, 33f PML protein See Promyelocytic leukemia (PML) protein Poly-A tail, eIF4E, 8–9 Polycomb repressive complexes (PRC2) ab initio, 131–134, 132t align sequences and estimate sequence features, 145 clade-specific features, 127, 129–130f, 132t coevolution between genes, 141f, 146 components, 126 distances between human and other species, 135f domains in, 127 episodic diversifying selection, 137t Ezh2, 127 functional domains, 140–142, 145 interaction domains, 139–140 JTT models, 139 in multiple species, 144–145 and NMD transcripts, 134–136 phylogenetic trees, 136f, 146 positive selection sites, 138f, 143 protein-protein interactions, 143–144 409 Subject Index Rbbp7, 127 sequence distances, computing, 146 signals distribution in lineages and sites, 136–139 signal selection, 136–139, 145 in situ, 131–134, 132t Suz12, 127 in vertebrates and mammals, 128–131, 129–130f WAG models, 139 Polycomb responsive element (PRE), 126 Porous aluminum, 214 antimicrobial properties, 220–221 charged-coupled device acquired image, 215f E coli, 219–221 EIS immunosensor, 222 environmental monitoring, 224 food production and manipulation, 221–222 food safety assurance, 222 for microbiology, 214–218 for pathogen detection, 219–220 in public health, 216t S aureus, 219–221 in vitro tests, 220 water safety assurance, 222–224 Postnatal depression, 98 Postsynaptic density protein-95 (PSD-95), 104–105 PRC2 See Polycomb repressive complexes (PRC2) ProCervix, 280 PROCOMOSS, 326–327 Profiling expression pattern of depression, 113–117 Promyelocytic leukemia (PML) protein, 2–4, 11–13 Prophylactic HPV vaccines, 264 adjuvanted vaccines, 274 bacterial-based vaccines, 266–273 capsomers-based vaccines, 274 Cervarix, 265 Gardasil, 265 Gardasil 9, 266 insect-based vaccines, 273 L2-based vaccines, 275 L1/L2 chimeras, 275 nanotechnologies-based vaccines, 275 plant-based vaccines, 274 pseudovirions-based vaccines, 274–275 virus-based vaccines, 273 yeast-based vaccines, 273–274 Prostate cancer, eIF4E, 14–15, 17–18 Protection of telomeres (POT1), 71, 74 Protein-based vaccines of HPV, 279–280 Protein data bank (PDB) of HPV, 241t Protein interaction networks (PINs) challenges, 324 content-based weights, 332 degree distribution, 329f function prediction, 325–326 graph augmentation, 330–334 hybrid weights, 333 proteins context in, 325–326 query protein and, 346 semantic similarity measures, 330–332 structure-based weights, 333 topology-based weights, 326–327 weighting strategies for, 332–334 Protein kinase C (PKC) activation, 53–55 Protein level, eIF4E, 5–7 4E-BP regulation, 5–7 phosphorylation, poly-A tail, 8–9 ubiquitination, 8, 14–15 Protein–protein interaction (PPI), 325–326, 328–329 Proteome of HPV, 240–249 Pseudomonas aeruginosa (P aeruginosa), 157, 159 Pseudovirions-based vaccines of HPV, 274–275 Psychotic depression, 98 Public health porous aluminum in, 216t, 221–224 QCM in, 160–172, 167t, 175–179, 179–180t, 181–188 Q Quartz-crystal microbalance (QCM) See also Quartz-crystal microbalance with dissipation (QCM-D) AIV H5N1 detection, 160–161 aptamers, 156, 180–181 bacteria, 156–159 biohazards, 187–188 410 Quartz-crystal microbalance (QCM) (Continued ) biosensors, 151–152 bioterrorism, 187–188 Butterworth–van-Dyke model, 155 for cancer detection, 173–175, 174t chemical compounds detection, 169t chronic degenerative diseases, 175–177, 180t definition, 153–154 dissipation factor, 155 electrochemical, 156, 158 environmental monitoring, 186–187 food hygiene, 181–186 with gold electrodes, 153f homeland security, 188 influenza virus, 160–165 invasive diseases, 171–172 microorganisms detection, 162t nanosensors, 151–152 nosocomial infections, 157 occupational hygiene, 177 pictorial representation, 154f in public health, 167t respiratory viruses, 160–165 Sauerbrey’s equation, 154–155 SELEX technology, 156 sensitivity factor, 154–155 sexually transmitted diseases, 166–171 tropical neglected diseases, 172–173 types of sensors, 155–156 Veterinary Public Health, 179–181 water safety, 177–179, 179t Quartz-crystal microbalance with dissipation (QCM-D), 170–171, 175, 176–177, 178–179 See also Quartzcrystal microbalance (QCM) biofilm formation, 157 Cryptosporidium parvum, 178 Escherichia coli, 158–159 monitoring drug resistance, 158–159 R Radiation, ALPs and, 31–32 Rana temporaria oocytes, 85–86 Random effects branch-site model, 136–137 Random Walks with Restarts (RWR), 334 Rap1, 71 Subject Index Rbbp4 homologous sequences, 129f, 135f NMD transcripts, 130–131 phylogenetic trees, 136f and WD40 domains, 127 Rbbp7 pregnancy-induced ncRNA, 127 and WD40 domains, 127 Receiver operating characteristic (ROC) curve, 340 Recombinant-based vaccines of HPV, 263–264 Recombinant measles virus (rMV), 273 Recombination-dependent replication (RDR), 252 Resnik metric, 331, 340–344 Respiratory viruses, 160–165 Restart probability, 334–335 Rolling circle amplification (RCA), 168 S Saccharomyces cerevisiae (S cerevisiae) eIF4E, PPI, 328–329 yeast-based vaccines, 273–274 SAD See Seasonal affective disorder (SAD) Salmonella food-borne pathogens, 182 S typhimurium, 182 SAPK/JNK pathway See Stress-activated protein kinase or c-Jun N-terminal kinase (SAPK/JNK) pathway Sauerbrey’s equation, quartz-crystal microbalance, 154–155 Seasonal affective disorder (SAD), 99 Self-assembling monolayer (SAM), QCM, 160–161 Semantic homogeneity optimization in protein interaction networks (SHOPIN), 327 AUC value for, 344–346, 344t BGLL, 338–339 cluster extraction, 335–337 cluster functional enrichment, 337–338 computational protein function prediction, 328f false-negative event, 339–340, 345t FC algorithms, 338–339 411 Subject Index leave-one-out method, 339 materials and methods, 327–338 metric space transformation, 334–335 noisy prediction problem in, 344–346 performance of, 342f PIN graph augmentation, 330–334 PPI data, 328–329 semantic similarity measures, 330–332 stationary vector, 334–335 true-positive events, 339–340 values for sensitivity, 341t, 345t weighting strategies for, 332–334 Sensitivity factor of QCM, 154–155 Sensors See also Biosensors biological component, 152 calorimetric, 152 thermometric, 152 Sexually transmitted diseases (STDs) Chlamydia trachomatis, 168 herpes simplex virus, 171 HIV/AIDS, 168–171 viral hepatitis, 166–168 SGN-00101, 279 Shelterin abundance and stoichiometry, 72 cis-acting mechanism, 74 components, 71–73 end-protection problem, 74 functions, 73–76 human, 72f structure, 72f subcomplexes, 71–72 on telomeric DNA, 72f t-loop formation, 73–74 t-loop HR control by, 77f Shigella, 266–273 SHOPIN See Semantic homogeneity optimization in protein interaction networks (SHOPIN) siRNAs, 17–18 SLC1A2/3, 103–104 SLPs See Synthetic long peptides (SLPs) Solid tumor cells, ALPs in, 41–49 Spodoptera frugiperda (Sf9), 273 Staphylococcus sp S aureus, 158–159, 219–221 S epidermidis, 157 S mutans, 156–157 STDs See Sexually transmitted diseases (STDs) Streptococcus pneumoniae, 172 Stress-activated protein kinase or c-Jun N-terminal kinase (SAPK/JNK) pathway, 53–55 Stresscopin, 112 Stress-inducible controlled expression (SICE) approach, 275–276 Structure-based weights, 333 Suppressor of zeste 12 (Suz12) coevolution, 141f human sequence, 130f PRC2 interacting through, 126 vertebrate-specific insertion, 129f Suprachiasmatic nucleus (SCN), 110 Synapse-related genes, depression, 107–108 Synthetic long peptides (SLPs), 280 Systematic evolution of ligands by exponential enrichment (SELEX) technology, 156 T TA-CIN, 276–277, 280 Tandem repeats (TRs), 78–80 TBLASTN software, 131–134, 144–145 Telomere repeat-containing RNA (TERRA), 73 Telomeres in chromatin organization, 77–81 DNA, 80–81 G-quadruplexes, 69, 70f G-rich strand, 68–69 Hayflick limit, 68 higher-order chromatin arrangements, 79 Hoogsteen hydrogen bonding, 70f length regulation, 74 mammalian, 69f protecting chromosomal ends, 70–71 RNA, 70–71 of somatic cells, 70 Telomeric repeat-binding factors and (TRF1/2), 71 activation, 75 amino acid sequence, 84f ATM kinase pathway, 74 colocalization, 89 deletion/inhibition, 75 412 Telomeric repeat-binding factors and (TRF1/2) (Continued ) interacting partners, 72 localization of, 88f nonshelterin factors, 72–73 N-terminal domain, 82 nuclear envelope and, 85–90 protein composition, 86f structure of, 81–84, 82f T-loop formation, 73–74 TERRA See Telomere repeat-containing RNA (TERRA) Tetrahymena thermophila, 68 TG4011 vaccine, 277 Therapeutic antigen-HPV (TA-HPV), 276–277 Therapeutic HPV vaccines, 264 bacterial vector-based vaccines, 275–276 bioinformatics studies, 283–284 capsomers-based vaccines, 283 DC-based vaccines, 281–283 DNA-based vaccines, 277–279 nanotechnologies-based vaccines, 283 peptide-based vaccines, 280–281 protein-based vaccines, 279–280 viral vector-based vaccines, 276–277 Thermometric sensors, 152 TimeBGLL algorithm, 338–339 TIN2, 71 T-loop HR, 76, 77f TNF receptor signaling and interferon, 113 TPP1, 71 Transcription factors of depression, 108–110 TRF1/2 See Telomeric repeat-binding factors and (TRF1/2) TRF homology (TRFH) dimerization, 82–83 TriVax, 280 True-positive (TP) events, 339–340 T-SCEs, 76 TTAGGG repeats of mammalian chromosome, 71 sequences, 69f single-stranded telomeric repeats, 74 Tuberculosis, 173 Subject Index U Ubiquitination of eIF4E, 8, 14–15 V 9-valent HPV VLP-based (9vHPV) vaccine, 266 Vector-based vaccines of HPV, 267t Vertebrates, PRC2 genes insertions in, 128–131, 129–130f Veterinary Public Health, 179–181 VGX-3100, 279 Vibrio harveyi, 180 Viral hepatitis, 166–168 Viral protein Z (VPZ), 11–13 Virus-based vaccines prophylactic HPV vaccines, 273 therapeutic HPV vaccines, 276–277 Virus-like particles (VLP) technology human papillomaviruses, 251, 262–263, 267t prophylactic HPV vaccines, 264–266 VPZ See Viral protein Z (VPZ) W WAG models, 139 Waldenstrom’s macroglobulinemia (WM), 37–39 Wang’s metric, 331, 340–343 Water safety assurance porous aluminum, 222–224 quartz-crystal microbalance, 177–179, 179t West Nile virus, 219 Whole cell-based vaccines of HPV, 267t X Xenopus laevis, 8–9 Xist, 127 Y Yeast-based vaccines of HPV, 273–274 Z ZYC101, 277–278 ... Cook, 2001), the PRH protein (proline-rich homeodomain protein) (Topisirovic et al., 2003a), the eIF4E and Cancer 13 homeodomain proteins, the Z protein, and the PML protein which is the most... structure and functions It will also expose the use of eIF4E as a therapeutic target in cancer Advances in Protein Chemistry and Structural Biology, Volume 101 ISSN 1876-1623 http://dx.doi.org/10 .1016 /bs.apcsb.2015.09.001... interaction by determining all protein protein interactions and signaling pathways that are blocked In fact, studies have shown that it can induce apoptosis through an eIF4E/eIF4G interaction-independent
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