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Bibliography Bibliography [1] Noam Agmon. Tetrahedral displacement: The molecular mechanism behind the Debye relax- ation in water. Journal of Physical Chemistry, 100(1):1072–1080, 1996. [2] M. P. Allen and D. J. Tildesley. Computer Simulation of Liquids. Oxford Science Publications, Clarendon Press, Oxford, 1989. [3] Patrick Aloy and Robert B. Russell. Interrogating protein interaction networks through struc- tural biology. Proceedings of the National Academy of Sciences, USA, 99:5896–5901, 2002. [4] Claus A.F. Andersen, Arthur G. Palmer, Sren Brunak, and Burkhard Rost. Continuum secondary structure captures protein flexibility. Structure, 10:175–184, 2002. [5] D. E. ANDERSON, J. H. HURLEY, H. NICHOLSON, W. A. BAASE, and B. W. MATTHEWS. Hydrophobic core repacking and aromatic-aromatic interaction in the ther- mostable mutant of T4 lysozyme Ser 117 Phe. Protein Science, 2(8):1285–1290, 1993. → [6] G. Apic, J. Gough, and S. A. Teichmann. An insight into domain combinations. Bioinfor- matics, 17 (Suppl.1):S83–89, 2001. [7] Isaiah T. Arkin, Huafeng Xu, Morten O. Jensen, Eyal Arbely, Estelle R. Bennett, Kevin J. Bowers, Edmond Chow, Ron O. Dror, Michael P. Eastwood, Ravenna Flitman-Tene, Brent A. Gregersen, John L. Klepeis, Istvan Kolossvary, Yibing Shan, and David E. Shaw. Mechanism of Na+/H+ antiporting. Science, 317(5839):799–803, 2007. [8] R. Aurora and G. D. Rose. Helix capping. Protein Science, 7(1):21–38, 1998. [9] Kellar Autumn, Metin Sitti, Yiching A. Liang, Anne M. Peattie, Wendy R. Hansen, Simon Sponberg, Thomas W. Kenny, Ronald Fearing, Jacob N. Israelachvili, and Robert J. Full. Evidence for van der Waals adhesion in gecko setae. Proceedings of the National Academy of Sciences, USA, 99(19):12252–12256, 2002. [10] Franc Avbelj and Robert L. Baldwin. Role of backbone solvation and electrostatics in gen- erating preferred peptide backbone conformations: distributions of phi. Proceedings of the National Academy of Sciences, USA, 100(10):5742–5747, 2003. Draft: February 12, 2008, do not distribute 219 BIBLIOGRAPHY BIBLIOGRAPHY [11] Franc Avbelj and Robert L. Baldwin. Origin of the neighboring residue effect on peptide back- bone conformation. Proceedings of the National Academy of Sciences, USA, 101(30):10967– 10972, 2004. [12] Franc Avbelj, P. Luo, and Robert L. Baldwin. Energetics of the interaction between water and the helical peptide group and its role in determining helix propensities. Proceedings of the National Academy of Sciences, USA, 97:10786–10791, 2000. [13] R. Azriel and E. Gazit. Analysis of the minimal amyloid-forming fragment of the islet amyloid polypeptide. An experimental support for the key role of the phenylalanine residue in amyloid formation. Journal of Biological Chemistry, 276(36):34156–34161, Sep 2001. [14] Ranjit Prasad Bahadur, Pinak Chakrabarti, Francis Rodier, and Jo¨ol Janin. Dissecting sub- unit interfaces in homodimeric proteins. Proteins: Str. Func. Gen., 53:708–719, 2003. [15] Ranjit Prasad Bahadur, Pinak Chakrabarti, Francis Rodier, and Jo¨ol Janin. A dissection of specific and non-specific protein-protein interfaces. Journal of Molecular Biology, 336:943–955, 2004. [16] E. N. Baker and R. E. Hubbard. Hydrogen bonding in globular proteins. Progress in Bio- physics and Molecular Biology, 44:97–179, 1984. [17] Robert L. Baldwin. Protein folding: Making a network of hydrophobic clusters. Science, 295:1657–1658, 2002. [18] A. Barabasi and R. Albert. Emergence of scaling in random networks. Science, 286:509–512, 1999. [19] Arieh Y. Ben-Naim. Hydrophobic Interactions. Springer, 1980. [20] Marco Bittelli, Markus Flury, and Kurt Roth. Use of dielectric spectroscopy to estimate ice content in frozen porous media. WATER RESOURCES RESEARCH, 40:W04212, 2004. [21] A. A. Bogan and K. S. Thorn. Anatomy of hot spots in protein interfaces. Journal of Molecular Biology, 280:1–9, 1998. [22] A. A. Bogan and K. S. J. Thorn. Anatomy of hot spots in protein interfaces. Journal of Molecular Biology, 280:1–9, 1998. [23] A. Bondi. van der Waals volumes and radii. Journal of Physical Chemistry, 68(3):441–451, 1964. [24] Clay Bracken, Lilia M. Iakoucheva, Pedro R. Romero, and A. Keith Dunker. Combining prediction, computation and experiment for the characterization of protein disorder. Curr Opin Struct Biol, 14(5):570–576, 2004. Draft: February 12, 2008, do not distribute 220 BIBLIOGRAPHY BIBLIOGRAPHY [25] Bobby-Joe Breitkreutz, Chris Stark, Teresa Reguly, Lorrie Boucher, Ashton Breitkreutz, Michael Livstone, Rose Oughtred, Daniel H. Lackner, Jrg Bhl, Valerie Wood, Kara Dolinsk, and Mike Tyers. The BioGRID Interaction Database: 2008 update. Nucl. Acids Res., 36(database issue):D637–640, 2008. [26] E Breslow, V Mombouyran, R Deeb, C Zheng, JP Rose, BC Wang, and RH Haschemeyer. Structural basis of neurophysin hormone specificity: Geometry, polarity, and polarizability in aromatic ring interactions. Protein Science, 8(4):820–831, 1999. [27] Dawn J. Brooks, Jacques R. Fresco, Arthur M. Lesk, and Mona Singh. Evolution of amino acid frequencies in proteins over deep time: Inferred order of introduction of amino acids into the genetic code. Molecular Biology and Evolution, 19:1645–1655, 2002. [28] William Fuller Brown, Jr. Dielectrics. In Handbuch der Physik, volume 14, pages 1–154. Springer, 1956. [29] R. G. Bryant. The dynamics of water-protein interactions. Annu. Rev. Biophys. Biomol. Struct., 25:29–53, 1996. [30] Christian J. Burnham and Sotiris S. Xantheas. Development of transferable interaction models for water. iii. reparametrization of an all-atom polarizable rigid model (ttm2–r) from first principles. Journal of Chemical Physics, 116(4):1500–1510, 2002. [31] Daniel R. Caffrey, Shyamal Somaroo, Jason D. Hughes, Julian Mintseris, and Enoch S. Huang. Are protein-protein interfaces more conserved in sequence than the rest of the protein surface? Protein Science, 13(1):190–202, 2004. [32] Eric Canc`es, Claude Le Bris, and Yvon Maday. M`ethodes math`ematiques en chimie quantique. Springer, 2006. [33] Eric Canc`es, M. Defranceschi, W. Kutzelnigg, Claude Le Bris, and Yvon Maday. Compu- tational quantum chemistry: a primer. In Ph. Ciarlet and C. Le Bris, editors, Handbook of numerical analysis. Volume X: special volume: computational chemistry, pages 3–270. Else- vier, 2003. [34] E. Candes and L. Demanet. The curvelet representation of wave propagators is optimally sparse. Comm. Pure Appl. Math., 58(11):1472–1528, 2005. [35] Pinak Chakrabarti and Jo¨ol Janin. Dissecting protein-protein recognition sites. Proteins: Str. Func. Gen., 47:334–343, 2002. [36] Dmitry A. Cherepanov. Force oscillations and dielectric overscreening of interfacial water. Phys. Rev. Lett., 93:266104, 2004. [37] T. Clackson and J. A. Wells. A hot spot of binding energy in a hormone-receptor interface. Science, 267:383–386, 1995. Draft: February 12, 2008, do not distribute 221 BIBLIOGRAPHY BIBLIOGRAPHY [38] C. COLOVOS and T. O. YEATES. Verification of protein structures: Patterns of nonbonded atomic interactions. Protein Sci, 2(9):1511–1519, 1993. [39] David B. Cook, editor. Handbook of Computational Quantum Chemistry. Oxford Univ. Press, 1998. [40] Christopher J. Cramer. Essentials of Computational Chemistry. Wiley, second edition, 2004. [41] Thomas E. Creighton. Proteins: Structures and molecular properties. W. H. Freeman, 1993. [42] Peter B. Crowley and Adel Golovin. Cation-π interactions in protein-protein interfaces. PRO- TEINS: Structure, Function, and Bioinformatics, 59:231–239, 2005. [43] Alfonso De Simone, Guy G. Dodson, Chandra S. Verma, Adriana Zagari, and Franca Fra- ternali. Prion and water: Tight and dynamical hydration sites have a key role in structural stability. Proceedings of the National Academy of Sciences, USA, 102:7535–7540, 2005. [44] P. Debye. Polar molecules. Dover, New York, 1945. [45] W. L. DeLano, M. H. Ultsch, A. M. de Vos, and J. A. Wells. Convergent solutions to binding at a protein-protein interface. Science, 287:1279–1283, 2000. [46] A. H. DePace, A. Santoso, P. Hillner, and J. S. Weissman. A critical role for amino- terminal glutamine/asparagine repeats in the formation and propagation of a yeast prion. Cell, 93(7):1241–1252, Jun 1998. [47] Florin Despa, Ariel Fern´andez, and R. Stephen Berry. Dielectric modulation of biological water. Phys. Rev. Lett., 93:269901, 2004. [48] Florin Despa, Ariel Fern´andez, and R. Stephen Berry. The origin of long range attraction between hydrophobes in water. Biophysical Journal, 92:373–378, 2007. [49] Christopher M. Dobson. Protein folding and misfolding. Nature, 426:884–890, 2003. [50] Dennis A. Dougherty. Cation-pi interactions in chemistry and biology: a new view of benzene, Phe, Tyr, and Trp. Science, 271(5246):163–168, 1996. [51] John Doyle. Beyond the sperical cow. Nature, 411:151–152, May 2001. [52] Xiaoqun Joyce Duan, Ioannis Xenarios, and David Eisenberg. Describing biological protein interactions in terms of protein states and state transitions. Mol. Cell. Proteomics, 1:104–116, 2002. [53] Johannes J. Duistermaat. Fourier Integral Operators. Springer, Berlin, 1996. [54] A. Elgsaeter, B. T. Stokke, A. Mikkelsen, and D. Branton. The molecular basis of erythrocyte shape. Science, 234:1217–1223, 1986. Draft: February 12, 2008, do not distribute 222 BIBLIOGRAPHY BIBLIOGRAPHY [55] M. Fandrich, M. A. Fletcher, and C. M. Dobson. Amyloid fibrils from muscle myoglobin. Nature, 410(6825):165–166, Mar 2001. [56] Marcus Fandrich and Christopher M. Dobson. The behaviour of polyamino acids reveals an inverse side chain effect in amyloid structure formation. EMBO J., 21(21):5682–5690, 2002. [57] Ariel Fern´andez. Cooperative walks in a cubic lattice: Protein folding as a many-body prob- lem. J. Chem. Phys., 115:7293–7297, 2001. [58] Ariel Fern´andez. Intramolecular modulation of electric fields in folding proteins. Phys. Lett. A, 299:217–220, 2002. [59] Ariel Fern´andez. Buffering the entropic cost of hydrophobic collapse in folding proteins. Journal of Chemical Physics, 121:11501–11502, 2004. [60] Ariel Fern´andez. Keeping dry and crossing membranes. Nature Biotechnology, 22:1081–1084, 2004. [61] Ariel Fern´andez. Direct nanoscale dehydration of hydrogen bonds. Journal of Physics D: Applied Physics, 38:2928–2932, 2005.
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