Protein flexibility in the light of structural alphabets

Frontiers in Molecular Biosciences

Volumn 2, Issue MAY, 2015, Pages

  Craveur, Pierrick ^a,b,c   Joseph, Agnel P ^d   Esque, Jeremy ^e   Narwani, Tarun J ^a,b,c   Noël, Floriane ^a,b,c   Shinada, Nicolas ^a,b,c   Goguet, Matthieu ^a,b,c   Leonard, Sylvain ^a,b,c   Poulain, Pierre ^a,b,c,f   Bertrand, Olivier ^a,b,c   Faure, Guilhem ^g   Rebehmed, Joseph ^h   Ghozlane, Amine ⁱ   Swapna, Lakshmipuram S ^j,k   Bhaskara, Ramachandra M ^j,l   Barnoud, Jonathan ^a,b,c,m   Téletchéa, Stéphane ^a,b,c,n   Jallu, Vincent ^c   Cerny, Jiri ^o   Schneider, Bohdan ^o   Etchebest, Catherine ^a,b,c   Srinivasan, Narayanaswamy ^j   Gelly, Jean Christophe ^a,b,c   de Brevern, Alexandre G ^a,b,c   more..

^a INSERM   (France)

^b hôpital Robert Debré et Institut national de la transfusion sanguine   (France)

^c INSTITUT NATIONAL DE LA TRANSFUSION SANGUINE   (France)

^d RUTHERFORD APPLETON LABORATORY   (United Kingdom)

^e UNIVERSITÉ DE STRASBOURG   (France)

^f Ets Poulain   (Congo)

^g NATIONAL INSTITUTES OF HEALTH   (United States)

^h SORBONNE UNIVERSITÉ   (France)

ⁱ University of Paris Saclay   (France)

^j INDIAN INSTITUTE OF SCIENCE   (India)

^k HOSPITAL FOR SICK CHILDREN   (Canada)

^l MAX PLANCK INSTITUTE OF BIOPHYSICS   (Germany)

^m UNIVERSITÉ DE LYON   (France)

ⁿ UNIVERSITÉ DE NANTES   (France)

^o INSTITUTE OF BIOTECHNOLOGY   (Czech Republic)

more..

Author keywords

Allostery; Disorder; Protein complexes; Protein folding; Protein structures; Protein DNA interactions; Secondary structure; Structural alphabet

Indexed keywords

EID: 84958849980     PISSN: None     EISSN: 2296889X     Source Type: Journal    
DOI: 10.3389/fmolb.2015.00020     Document Type: Review

References (148)

1. Allen, S. J., Crown, S. E., and Handel, T. M. (2007). Chemokine: receptor structure, interactions, and antagonism. Annu. Rev. Immunol. 25, 787-820. doi: 10.1146/annurev.immunol.24.021605.090529
2. Batchelor, J. D., Malpede, B. M., Omattage, N. S., DeKoster, G. T., Henzler-Wildman, K. A., and Tolia, N. H. (2014). Red blood cell invasion by Plasmodium vivax: structural basis for DBP engagement of DARC. PLoS Pathog. 10:e1003869. doi: 10.1371/journal.ppat.1003869
3. Benros, C., de Brevern, A. G., Etchebest, C., and Hazout, S. (2006). Assessing a novel approach for predicting local 3D protein structures from sequence. Proteins 62, 865-880. doi: 10.1002/prot.20815
4. Benros, C., de Brevern, A. G., and Hazout, S. (2009). Analyzing the sequence-structure relationship of a library of local structural prototypes. J. Theor. Biol. 256, 215-226. doi: 10.1016/j.jtbi.2008.08.032
5. Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H., et al. (2000). The Protein Data Bank. Nucleic Acids Res. 28, 235-242. doi: 10.1093/nar/28.1.235
6. Bernstein, F. C., Koetzle, T. F., Williams, G. J., Meyer, E. F. Jr., Brice, M. D., Rodgers, J. R., et al. (1977). The Protein Data Bank: a computer-based archival file for macromolecular structures. J. Mol. Biol. 112, 535-542. doi: 10.1016/S0022-2836(77)80200-3
7. Bhaskara, R. M., de Brevern, A. G., and Srinivasan, N. (2013). Understanding the role of domain-domain linkers in the spatial orientation of domains in multi-domain proteins. J. Biomol. Struct. Dyn. 31, 1467-1480. doi: 10.1080/07391102.2012.743438
8. Biswas, S., Guharoy, M., and Chakrabarti, P. (2009). Dissection, residue conservation, and structural classification of protein-DNA interfaces. Proteins 74, 643-654. doi: 10.1002/prot.22180
9. Bornot, A., Etchebest, C., and de Brevern, A. G. (2009). A new prediction strategy for long local protein structures using an original description. Proteins 76, 570-587. doi: 10.1002/prot.22370
10. Budowski-Tal, I., Nov, Y., and Kolodny, R. (2010). FragBag, an accurate representation of protein structure, retrieves structural neighbors from the entire PDB quickly and accurately. Proc. Natl. Acad. Sci. U.S.A. 107, 3481-3486. doi: 10.1073/pnas.0914097107
11. Buehler, M. J., and Yung, Y. C. (2009). Deformation and failure of protein materials in physiologically extreme conditions and disease. Nat. Mater. 8, 175-188. doi: 10.1038/nmat2387
12. Camproux, A. C., Gautier, R., and Tuffery, P. (2004). A hidden markov model derived structural alphabet for proteins. J. Mol. Biol. 339, 591-605. doi: 10.1016/j.jmb.2004.04.005
13. Camproux, A. C., Tuffery, P., Chevrolat, J. P., Boisvieux, J. F., and Hazout, S. (1999). Hidden Markov model approach for identifying the modular framework of the protein backbone. Protein Eng. 12, 1063-1073. doi: 10.1093/protein/12.12.1063
14. Cech, P., Kukal, J., Cerny, J., Schneider, B., and Svozil, D. (2013). Automatic workflow for the classification of local DNA conformations. BMC Bioinformatics 14, 205. doi: 10.1186/1471-2105-14-205
15. Chavent, M., Levy, B., Krone, M., Bidmon, K., Nomine, J. P., Ertl, T., et al. (2011). GPU-powered tools boost molecular visualization. Brief. Bioinformatics 12, 689-701. doi: 10.1093/bib/bbq089
16. Cilia, E., Pancsa, R., Tompa, P., Lenaerts, T., and Vranken, W. F. (2013). From protein sequence to dynamics and disorder with DynaMine. Nat. Commun. 4, 2741. doi: 10.1038/ncomms3741
17. Cilia, E., Pancsa, R., Tompa, P., Lenaerts, T., and Vranken, W. F. (2014). The DynaMine webserver: predicting protein dynamics from sequence. Nucleic Acids Res. 42, W264-W270. doi: 10.1093/nar/gku270
18. Compton, A., and Haber, J. M. (1960). The duffy blood group system in transfusion reactions: a reviw of the literature and report of four cases. Blood 15, 186-191
19. Corey, R. B., and Pauling, L. (1953). Fundamental dimensions of polypeptide chains. Proc. R. Soc. Lond. B Biol. Sci. 141, 10-20. doi: 10.1098/rspb.1953.0011
20. Craveur, P., Rebehmed, J., and de Brevern, A. G. (2014). PTM-SD: a database of structurally resolved and annotated posttranslational modifications in proteins. Database 2014:bau041. doi: 10.1093/database/bau041
21. Crooks, G. E., Hon, G., Chandonia, J. M., and Brenner, S. E. (2004). WebLogo: a sequence logo generator. Genome Res. 14, 1188-1190. doi: 10.1101/gr.849004
22. Cutbush, M., and Mollison, P. L. (1950). The Duffy blood group system. Heredity (Edinb.) 4, 383-389. doi: 10.1038/hdy.1950.31
23. Cutts, J. C., Powell, R., Agius, P. A., Beeson, J. G., Simpson, J. A., and Fowkes, F. J. (2014). Immunological markers of Plasmodium vivax exposure and immunity: a systematic review and meta-analysis. BMC Med. 12:150. doi: 10.1186/s12916-014-0150-1
24. de Brevern, A. G., Autin, L., Colin, Y., Bertrand, O., and Etchebest, C. (2009). In silico studies on DARC. Infect. Disord. Drug Targets 9, 289-303. doi: 10.2174/1871526510909030289
25. de Brevern, A. G., Benros, C., Gautier, R., Valadie, H., Hazout, S., and Etchebest, C. (2004). Local backbone structure prediction of proteins. In Silico Biol. 4, 381-386
26. de Brevern, A. G., Bornot, A., Craveur, P., Etchebest, C., and Gelly, J. C. (2012). PredyFlexy: flexibility and local structure prediction from sequence. Nucleic Acids Res. 40, W317-W322. doi: 10.1093/nar/gks482
27. de Brevern, A. G., Etchebest, C., and Hazout, S. (2000). Bayesian probabilistic approach for predicting backbone structures in terms of protein blocks. Proteins 41, 271-287. doi: 10.1002/1097-0134(20001115)41:3<271::AID-PROT10>3.0.CO;2-Z
28. de Brevern, A. G., and Hazout, S. (2003). 'Hybrid protein model' for optimally defining 3D protein structure fragments. Bioinformatics 19, 345-353. doi: 10.1093/bioinformatics/btf859
29. de Brevern, A. G., Wong, H., Tournamille, C., Colin, Y., Le Van Kim, C., and Etchebest, C. (2005). A structural model of a seven-transmembrane helix receptor: the Duffy antigen/receptor for chemokine (DARC). Biochim. Biophys. Acta 1724, 288-306. doi: 10.1016/j.bbagen.2005.05.016
30. Delano, W. L. (2013). The PyMOL Molecular Graphics System on World Wide Web. Available online at: http://www.pymol.org
31. Dosztanyi, Z., Csizmok, V., Tompa, P., and Simon, I. (2005). IUPred: web server for the prediction of intrinsically unstructured regions of proteins based on estimated energy content. Bioinformatics 21, 3433-3434. doi: 10.1093/bioinformatics/bti541
32. Dudev, M., and Lim, C. (2007). Discovering structural motifs using a structural alphabet: application to magnesium-binding sites. BMC Bioinformatics 8:106. doi: 10.1186/1471-2105-8-106
33. Dunker, A. K. (2007). Another window into disordered protein function. Structure 15, 1026-1028. doi: 10.1016/j.str.2007.08.001
34. Dunker, A. K., Lawson, J. D., Brown, C. J., Williams, R. M., Romero, P., Oh, J. S., et al. (2001). Intrinsically disordered protein. J. Mol. Graph. Model. 19, 26-59. doi: 10.1016/S1093-3263(00)00138-8
35. Dunker, A. K., and Obradovic, Z. (2001). The protein trinity-linking function and disorder. Nat. Biotechnol. 19, 805-806. doi: 10.1038/nbt0901-805
36. Dunker, A. K., Obradovic, Z., Romero, P., Garner, E. C., and Brown, C. J. (2000). Intrinsic protein disorder in complete genomes. Genome Inform. Ser. Workshop Genome Inform. 11, 161-171
37. Eisenberg, D. (2003). The discovery of the alpha-helix and beta-sheet, the principal structural features of proteins. Proc. Natl. Acad. Sci. U.S.A. 100, 11207-11210. doi: 10.1073/pnas.2034522100
38. Espinoza, J. P., Caradeux, J., Norwitz, E. R., and Illanes, S. E. (2013). Fetal and neonatal alloimmune thrombocytopenia. Rev. Obstet. Gynecol. 6, e15-21. doi: 10.1097/AOG.0b013e31823403f4
39. Etchebest, C., Benros, C., Hazout, S., and de Brevern, A. G. (2005). A structural alphabet for local protein structures: improved prediction methods. Proteins 59, 810-827. doi: 10.1002/prot.20458
40. Eyal, E., Lum, G., and Bahar, I. (2015). The anisotropic network model web server at 2015 (ANM 2.0). Bioinformatics 31, 1487-1489. doi: 10.1093/bioinformatics/btu847
41. Ferrada, E., and Melo, F. (2009). Effective knowledge-based potentials. Protein Sci. 18, 1469-1485. doi: 10.1002/pro.166
42. Fetrow, J. S., Palumbo, M. J., and Berg, G. (1997). Patterns, structures, and amino acid frequencies in structural building blocks, a protein secondary structure classification scheme. Proteins 27, 249-271
43. Fong, J. H., and Panchenko, A. R. (2010). Intrinsic disorder and protein multibinding in domain, terminal, and linker regions. Mol. Biosyst. 6, 1821-1828. doi: 10.1039/c005144f
44. Fornili, A., Pandini, A., Lu, H. C., and Fraternali, F. (2013). Specialized dynamical properties of promiscuous residues revealed by simulated conformational ensembles. J. Chem. Theory Comput. 9, 5127-5147. doi: 10.1021/ct400486p
45. Galzitskaya, O. V., Garbuzynskiy, S. O., and Lobanov, M. Y. (2006). FoldUnfold: web server for the prediction of disordered regions in protein chain. Bioinformatics 22, 2948-2949. doi: 10.1093/bioinformatics/btl504
46. Garvie, C. W., and Phillips, S. E. (2000). Direct and indirect readout in mutant Met repressor-operator complexes. Structure 8, 905-914. doi: 10.1016/S0969-2126(00)00182-9
47. Gelly, J. C., Joseph, A. P., Srinivasan, N., and de Brevern, A. G. (2011). iPBA: a tool for protein structure comparison using sequence alignment strategies. Nucleic Acids Res. 39, W18-W23. doi: 10.1093/nar/gkr333
48. George, J. N., Caen, J. P., and Nurden, A. T. (1990). Glanzmann's thrombasthenia: the spectrum of clinical disease. Blood 75, 1383-1395
49. Goh, C. S., Milburn, D., and Gerstein, M. (2004). Conformational changes associated with protein-protein interactions. Curr. Opin. Struct. Biol. 14, 104-109. doi: 10.1016/j.sbi.2004.01.005
50. Grunberg, R., Leckner, J., and Nilges, M. (2004). Complementarity of structure ensembles in protein-protein binding. Structure 12, 2125-2136. doi: 10.1016/j.str.2004.09.014
51. Gu, Y., Rosenblatt, J., and Morgan, D. O. (1992). Cell cycle regulation of CDK2 activity by phosphorylation of Thr160 and Tyr15. EMBO J. 11, 3995-4005
52. Guerra, C. A., Snow, R. W., and Hay, S. I. (2006). Mapping the global extent of malaria in 2005. Trends Parasitol. 22, 353-358. doi: 10.1016/j.pt.2006.06.006
53. Hirose, S., Yokota, K., Kuroda, Y., Wako, H., Endo, S., Kanai, S., et al. (2010). Prediction of protein motions from amino acid sequence and its application to protein-protein interaction. BMC Struct. Biol. 10:20. doi: 10.1186/1472-6807-10-20
54. Hirst, J. D., Glowacki, D. R., and Baaden, M. (2014). Molecular simulations and visualization: introduction and overview. Faraday Discuss. 169, 9-22. doi: 10.1039/C4FD90024C
55. Horne, K., and Woolley, I. J. (2009). Shedding light on DARC: the role of the Duffy antigen/receptor for chemokines in inflammation, infection and malignancy. Inflamm. Res. 58, 431-435. doi: 10.1007/s00011-009-0023-9
56. Huntington, J. A., Read, R. J., and Carrell, R. W. (2000). Structure of a serpin-protease complex shows inhibition by deformation. Nature 407, 923-926. doi: 10.1038/35038119
57. Hwang, H., Vreven, T., Whitfield, T. W., Wiehe, K., and Weng, Z. (2011). A machine learning approach for the prediction of protein surface loop flexibility. Proteins 79, 2467-2474. doi: 10.1002/prot.23070
58. Hynes, R. O. (2002). Integrins: bidirectional, allosteric signaling machines. Cell 110, 673-687. doi: 10.1016/S0092-8674(02)00971-6
59. Ihaka, R., and Gentleman, R. (1996). R: a language for data analysis and graphics. J. Comput. Graph. Stat. 5, 299-314. doi: 10.2307/1390807
60. Ishida, T., and Kinoshita, K. (2007). PrDOS: prediction of disordered protein regions from amino acid sequence. Nucleic Acids Res. 35, W460-W464. doi: 10.1093/nar/gkm363
61. Jallu, V., Bertrand, G., Bianchi, F., Chenet, C., Poulain, P., and Kaplan, C. (2013). The alphaIIb p. Leu841Met (Cab3(a+)) polymorphism results in a new human platelet alloantigen involved in neonatal alloimmune thrombocytopenia. Transfusion 53, 554-563. doi: 10.1111/j.1537-2995.2012.03762.x
62. Jallu, V., Dusseaux, M., Panzer, S., Torchet, M. F., Hezard, N., Goudemand, J., et al. (2010). AlphaIIbbeta3 integrin: new allelic variants in Glanzmann thrombasthenia, effects on ITGA2B and ITGB3 mRNA splicing, expression, and structure-function. Hum. Mutat. 31, 237-246. doi: 10.1002/humu.21179
63. Jallu, V., Poulain, P., Fuchs, P. F., Kaplan, C., and de Brevern, A. G. (2012). Modeling and molecular dynamics of HPA-1a and-1b polymorphisms: effects on the structure of the beta3 subunit of the alphaIIbbeta3 integrin. PLoS ONE 7:e47304. doi: 10.1371/journal.pone.0047304
64. Jallu, V., Poulain, P., Fuchs, P. F., Kaplan, C., and de Brevern, A. G. (2014). Modeling and molecular dynamics simulations of the V33 variant of the integrin subunit beta3: structural comparison with the L33 (HPA-1a) and P33 (HPA-1b) variants. Biochimie 105, 84-90. doi: 10.1016/j.biochi.2014.06.017
65. Janin, J., Bahadur, R. P., and Chakrabarti, P. (2008). Protein-protein interaction and quaternary structure. Q. Rev. Biophys. 41, 133-180. doi: 10.1017/S0033583508004708
66. Jin, Y., and Dunbrack, R. L. Jr. (2005). Assessment of disorder predictions in CASP6. Proteins 61(Suppl. 7), 167-175. doi: 10.1002/prot.20734
67. Jones, D. T., and Cozzetto, D. (2015). DISOPRED3: precise disordered region predictions with annotated protein-binding activity. Bioinformatics 31, 857-863. doi: 10.1093/bioinformatics/btu744
68. Jones, S., and Thornton, J. M. (1996). Principles of protein-protein interactions. Proc. Natl. Acad. Sci. U.S.A. 93, 13-20. doi: 10.1073/pnas.93.1.13
69. Joseph, A. P., Agarwal, G., Mahajan, S., Gelly, J. C., Swapna, L. S., Offmann, B., et al. (2010a). A short survey on protein blocks. Biophys. Rev. 2, 137-145. doi: 10.1007/s12551-010-0036-1
70. Joseph, A. P., Bornot, A., and de Brevern, A. G. (2010b). "Local structural alphabet". in Protein Structure Methods and Algorithms, eds H. Rangwala and G. Karypis (Hoboken, NJ: Wiley), 75-106. doi: 10.1002/9780470882207.ch5
71. Joseph, A. P., and de Brevern, A. G. (2014). From local structure to a global framework: recognition of protein folds. J. R. Soc. Interface 11:20131147. doi: 10.1098/rsif.2013.1147
72. Joseph, A. P., Srinivasan, N., and de Brevern, A. G. (2012). Progressive structure-based alignment of homologous proteins: adopting sequence comparison strategies. Biochimie 94, 2025-2034. doi: 10.1016/j.biochi.2012.05.028
73. Kabsch, W., and Sander, C. (1983). Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 22, 2577-2637. doi: 10.1002/bip.360221211
74. Karplus, P., and Schulz, G. (1985). Prediction of chain flexibility in proteins. A tool for the selection of peptide antigens. Naturwissenschaften 72, 212-213. doi: 10.1007/BF01195768
75. Kim, S., Woo, J., Seo, E. J., Yu, M., and Ryu, S. (2001). A 2.1 A resolution structure of an uncleaved alpha(1)-antitrypsin shows variability of the reactive center and other loops. J. Mol. Biol. 306, 109-119. doi: 10.1006/jmbi.2000.4357
76. Kolodny, R., Koehl, P., Guibas, L., and Levitt, M. (2002). Small libraries of protein fragments model native protein structures accurately. J. Mol. Biol. 323, 297-307. doi: 10.1016/S0022-2836(02)00942-7
77. Kuznetsov, I. B. (2008). Ordered conformational change in the protein backbone: prediction of conformationally variable positions from sequence and low-resolution structural data. Proteins 72, 74-87. doi: 10.1002/prot.21899
78. Kuznetsov, I. B., and McDuffie, M. (2008). FlexPred: a web-server for predicting residue positions involved in conformational switches in proteins. Bioinformation 3, 134-136. doi: 10.6026/97320630003134
79. Le, Q., Pollastri, G., and Koehl, P. (2009). Structural alphabets for protein structure classification: a comparison study. J. Mol. Biol. 387, 431-450. doi: 10.1016/j.jmb.2008.12.044
80. Lensink, M. F., and Mendez, R. (2008). Recognition-induced conformational changes in protein-protein docking. Curr. Pharm. Biotechnol. 9, 77-86. doi: 10.2174/138920108783955173
81. Leonard, S., Joseph, A. P., Srinivasan, N., Gelly, J. C., and de Brevern, A. G. (2014). mulPBA: an efficient multiple protein structure alignment method based on a structural alphabet. J. Biomol. Struct. Dyn. 32, 661-668. doi: 10.1080/07391102.2013.787026
82. Lindahl, E., Hess, B., and van der Spoel, D. (2001). GROMACS 3.0: A package for molecular simulation and trajectory analysis. J. Mol. Mod. 7, 306-317. doi: 10.1007/s008940100045
83. Linding, R., Jensen, L. J., Diella, F., Bork, P., Gibson, T. J., and Russell, R. B. (2003). Protein disorder prediction: implications for structural proteomics. Structure 11, 1453-1459. doi: 10.1016/j.str.2003.10.002
84. Liu, X. H., Hadley, T. J., Xu, L., Peiper, S. C., and Ray, P. E. (1999). Up-regulation of Duffy antigen receptor expression in children with renal disease. Kidney Int. 55, 1491-1500. doi: 10.1046/j.1523-1755.1999.00385.x
85. Lobanov, M. Y., Shoemaker, B. A., Garbuzynskiy, S. O., Fong, J. H., Panchenko, A. R., and Galzitskaya, O. V. (2010). ComSin: database of protein structures in bound (complex) and unbound (single) states in relation to their intrinsic disorder. Nucleic Acids Res. 38, D283-D287. doi: 10.1093/nar/gkp963
86. Luo, X., Lv, F., Pan, Y., Kong, X., Li, Y., and Yang, Q. (2011). Structure-based prediction of the mobility and disorder of water molecules at protein-DNA interface. Protein Pept. Lett. 18, 203-209. doi: 10.2174/092986611794475066
87. Mamonova, T. B., Glyakina, A. V., Kurnikova, M. G., and Galzitskaya, O. V. (2010). Flexibility and mobility in mesophilic and thermophilic homologous proteins from molecular dynamics and FoldUnfold method. J. Bioinform. Comput. Biol. 8, 377-394. doi: 10.1142/S0219720010004690
88. Marsh, J. A. (2013). Buried and accessible surface area control intrinsic protein flexibility. J. Mol. Biol. 425, 3250-3263. doi: 10.1016/j.jmb.2013.06.019
89. Matlock, M. K., Holehouse, A. S., and Naegle, K. M. (2015). ProteomeScout: a repository and analysis resource for post-translational modifications and proteins. Nucleic Acids Res. 43, D521-D530. doi: 10.1093/nar/gku1154
90. Meszaros, B., Simon, I., and Dosztanyi, Z. (2011). The expanding view of protein-protein interactions: complexes involving intrinsically disordered proteins. Phys. Biol. 8:035003. doi: 10.1088/1478-3975/8/3/035003
91. Micheletti, C., Seno, F., and Maritan, A. (2000). Recurrent oligomers in proteins: an optimal scheme reconciling accurate and concise backbone representations in automated folding and design studies. Proteins 40, 662-674. doi: 10.1002/1097-0134(20000901)40:4<662::AID-PROT90>3.0.CO;2-F
92. Miller, L. H., Mason, S. J., Clyde, D. F., and McGinniss, M. H. (1976). The resistance factor to Plasmodium vivax in blacks. The Duffy-blood-group genotype, FyFy. N. Engl. J. Med. 295, 302-304. doi: 10.1056/NEJM197608052950602
93. Miller, L. H., Mason, S. J., Dvorak, J. A., McGinniss, M. H., and Rothman, I. K. (1975). Erythrocyte receptors for (Plasmodium knowlesi) malaria: Duffy blood group determinants. Science 189, 561-563. doi: 10.1126/science.1145213
94. Misaghi, S., Galardy, P. J., Meester, W. J., Ovaa, H., Ploegh, H. L., and Gaudet, R. (2005). Structure of the ubiquitin hydrolase UCH-L3 complexed with a suicide substrate. J. Biol. Chem. 280, 1512-1520. doi: 10.1074/jbc. M410770200
95. Nussinov, R., Tsai, C. J., Xin, F., and Radivojac, P. (2012). Allosteric post-translational modification codes. Trends Biochem. Sci. 37, 447-455. doi: 10.1016/j.tibs.2012.07.001
96. Offmann, B., Tyagi, M., and de Brevern, A. G. (2007). Local protein structures. Curr. Bioinform. 3, 165-202. doi: 10.2174/157489307781662105
97. Olsson, S., Vögeli, B., Cavalli, A., Boomsma, W., Ferkinghoff-Borg, J., Lindorff-Larsen, K., et al. (2014). Probabilistic determination of native state ensembles of proteins. J. Chem. Theory Comput. 10, 3484-3491. doi: 10.1021/ct5001236
98. Otterbein, L. R., Cosio, C., Graceffa, P., and Dominguez, R. (2002). Crystal structures of the vitamin D-binding protein and its complex with actin: structural basis of the actin-scavenger system. Proc. Natl. Acad. Sci. U.S.A. 99, 8003-8008. doi: 10.1073/pnas.122126299
99. Palmer, A. G. 3rd. (2001). Nmr probes of molecular dynamics: overview and comparison with other techniques. Annu. Rev. Biophys. Biomol. Struct. 30, 129-155. doi: 10.1146/annurev.biophys.30.1.129
100. Pan, X. Y., and Shen, H. B. (2009). Robust prediction of B-factor profile from sequence using two-stage SVR based on random forest feature selection. Protein Pept. Lett. 16, 1447-1454. doi: 10.2174/092986609789839250
101. Pandini, A., Fornili, A., Fraternali, F., and Kleinjung, J. (2012). Detection of allosteric signal transmission by information-theoretic analysis of protein dynamics. FASEB J. 26, 868-881. doi: 10.1096/fj.11-190868
102. Pandini, A., Fornili, A., Fraternali, F., and Kleinjung, J. (2013). GSATools: analysis of allosteric communication and functional local motions using a structural alphabet. Bioinformatics 29, 2053-2055. doi: 10.1093/bioinformatics/btt326
103. Pandini, A., Fornili, A., and Kleinjung, J. (2010). Structural alphabets derived from attractors in conformational space. BMC Bioinformatics 11:97. doi: 10.1186/1471-2105-11-97
104. Park, B. H., and Levitt, M. (1995). The complexity and accuracy of discrete state models of protein structure. J. Mol. Biol. 249, 493-507. doi: 10.1006/jmbi.1995.0311
105. Powers, R., Clore, G., Garrett, D., and Gronenborn, A. (1993). Relationships between the precision of high-resolution protein NMR structures, solution-order parameters, and crystallographic B factors. J. Magn. Reson. B 101, 325-327. doi: 10.1006/jmrb.1993.1051
106. Python Software Foundation. (2015). Python Language Reference, Version 2.7. Available online at: http://www.python.org
107. Rangwala, H., Kauffman, C., and Karypis, G. (2009). svmPRAT: SVM-based protein residue annotation toolkit. BMC Bioinformatics 10:439. doi: 10.1186/1471-2105-10-439
108. Richardson, J. S. (1981). The anatomy and taxonomy of protein structure. Adv. Protein Chem. 34, 167-339. doi: 10.1016/S0065-3233(08)60520-3
109. Russo, D., Teixeira, J., Kneller, L., Copley, J. R., Ollivier, J., Perticaroli, S., et al. (2011). Vibrational density of states of hydration water at biomolecular sites: hydrophobicity promotes low density amorphous ice behavior. J. Am. Chem. Soc. 133, 4882-4888. doi: 10.1021/ja109610f
110. Salwinski, L., Miller, C. S., Smith, A. J., Pettit, F. K., Bowie, J. U., and Eisenberg, D. (2004). The database of interacting proteins: 2004 update. Nucleic Acids Res. 32, D449-D451. doi: 10.1093/nar/gkh086
111. Schlessinger, A., Punta, M., Yachdav, G., Kajan, L., and Rost, B. (2009). Improved disorder prediction by combination of orthogonal approaches. PLoS ONE 4:e4433. doi: 10.1371/journal.pone.0004433
112. Schlessinger, A., and Rost, B. (2005). Protein flexibility and rigidity predicted from sequence. Proteins 61, 115-126. doi: 10.1002/prot.20587
113. Schlessinger, A., Yachdav, G., and Rost, B. (2006). PROFbval: predict flexible and rigid residues in proteins. Bioinformatics 22, 891-893. doi: 10.1093/bioinformatics/btl032
114. Schneider, B., Gelly, J. C., de Brevern, A. G., and Cerny, J. (2014). Local dynamics of proteins and DNA evaluated from crystallographic B factors. Acta Crystallogr. D Biol. Crystallogr. 70(Pt 9), 2413-2419. doi: 10.1107/S1399004714014631
115. Schuchhardt, J., Schneider, G., Reichelt, J., Schomburg, D., and Wrede, P. (1996). Local structural motifs of protein backbones are classified by self-organizing neural networks. Protein Eng. 9, 833-842. doi: 10.1093/protein/9.10.833
116. Schwede, T., Sali, A., Honig, B., Levitt, M., Berman, H. M., Jones, D., et al. (2009). Outcome of a workshop on applications of protein models in biomedical research. Structure 17, 151-159. doi: 10.1016/j.str.2008.12.014
117. Scott, W. R., and Straus, S. K. (2015). Determining and visualizing flexibility in protein structures. Proteins 83, 820-826. doi: 10.1002/prot.24776
118. Smolarek, D., Bertrand, O., Czerwinski, M., Colin, Y., Etchebest, C., and de Brevern, A. G. (2010). Multiple interests in structural models of DARC transmembrane protein. Transfus. Clin. Biol. 17, 184-196. doi: 10.1016/j.tracli.2010.05.003
119. Suhre, K., and Sanejouand, Y. H. (2004). ElNemo: a normal mode web server for protein movement analysis and the generation of templates for molecular replacement. Nucleic Acids Res. 32, W610-W614. doi: 10.1093/nar/gkh368
120. Sunami, T., and Kono, H. (2013). Local conformational changes in the DNA interfaces of proteins. PLoS ONE 8:e56080. doi: 10.1371/journal.pone.0056080
121. Suresh, V., Ganesan, K., and Parthasarathy, S. (2013). A protein block based fold recognition method for the annotation of twilight zone sequences. Protein Pept. Lett. 20, 249-254. doi: 10.2174/092986613804910617
122. Svozil, D., Kalina, J., Omelka, M., and Schneider, B. (2008). DNA conformations and their sequence preferences. Nucleic Acids Res. 36, 3690-3706. doi: 10.1093/nar/gkn260
123. Swapna, L. S., Mahajan, S., de Brevern, A. G., and Srinivasan, N. (2012). Comparison of tertiary structures of proteins in protein-protein complexes with unbound forms suggests prevalence of allostery in signalling proteins. BMC Struct. Biol. 12:6. doi: 10.1186/1472-6807-12-6
124. Takada, Y., Ye, X., and Simon, S. (2007). The integrins. Genome Biol. 8:215. doi: 10.1186/gb-2007-8-5-215
125. Tanaka, Y., Nureki, O., Kurumizaka, H., Fukai, S., Kawaguchi, S., Ikuta, M., et al. (2001). Crystal structure of the CENP-B protein-DNA complex: the DNA-binding domains of CENP-B induce kinks in the CENP-B box DNA. EMBO J. 20, 6612-6618. doi: 10.1093/emboj/20.23.6612
126. Tiwari, S. P., Fuglebakk, E., Hollup, S. M., Skjaerven, L., Cragnolini, T., Grindhaug, S. H., et al. (2014). WEBnm@ v2.0: Web Server and Services for Comparing Protein Flexibility. BMC Bioinformatics 15:6597. doi: 10.1186/s12859-014-0427-6
127. Tournamille, C., Filipe, A., Badaut, C., Riottot, M. M., Longacre, S., Cartron, J. P., et al. (2005). Fine mapping of the Duffy antigen binding site for the Plasmodium vivax Duffy-binding protein. Mol. Biochem. Parasitol. 144, 100-103. doi: 10.1016/j.molbiopara.2005.04.016
128. Tournamille, C., Filipe, A., Wasniowska, K., Gane, P., Lisowska, E., Cartron, J. P., et al. (2003). Structure-function analysis of the extracellular domains of the Duffy antigen/receptor for chemokines: characterization of antibody and chemokine binding sites. Br. J. Haematol. 122, 1014-1023. doi: 10.1046/j.1365-2141.2003.04533.x
129. Touw, W. G., and Vriend, G. (2014). BDB: databank of PDB files with consistent B-factors. Protein Eng. Des. Sel. 27, 457-462. doi: 10.1093/protein/gzu044
130. Trott, O., Siggers, K., Rost, B., and Palmer, A. G. 3rd. (2008). Protein conformational flexibility prediction using machine learning. J. Magn. Reson. 192, 37-47. doi: 10.1016/j.jmr.2008.01.011
131. Tung, C. H., Huang, J. W., and Yang, J. M. (2007). Kappa-alpha plot derived structural alphabet and BLOSUM-like substitution matrix for fast protein structure database search. Genome Biol. 8:R31. doi: 10.1186/gb-2007-8-3-r31
132. Tung, C. H., and Yang, J. M. (2007). fastSCOP: a fast web server for recognizing protein structural domains and SCOP superfamilies. Nucleic Acids Res. 35, W438-W443. doi: 10.1093/nar/gkm288
133. Tyagi, M., Benros, C., Martin, J., and de Brevern, A. G. (2007). "Description of the local protein structure II. Novel approaches". in Recent Research Developments in Protein Engineering, ed A. G. de Brevern (Trivandrum: Research Signpost), 23-36
134. Uhart, M., and Bustos, D. M. (2014). Protein intrinsic disorder and network connectivity. The case of 14-3-3 proteins. Front. Genet. 5:10. doi: 10.3389/fgene.2014.00010
135. Unger, R., Harel, D., Wherland, S., and Sussman, J. L. (1989). A 3D building blocks approach to analyzing and predicting structure of proteins. Proteins 5, 355-373. doi: 10.1002/prot.340050410
136. Uversky, V. N., Gillespie, J. R., and Fink, A. L. (2000). Why are "natively unfolded" proteins unstructured under physiologic conditions? Proteins 41, 415-427. doi: 10.1002/1097-0134(20001115)41:3<415::AID-PROT130>3.0.CO;2-7
137. Van Der Spoel, D., Lindahl, E., Hess, B., Groenhof, G., Mark, A. E., and Berendsen, H. J. (2005). GROMACS: fast, flexible, and free. J. Comput. Chem. 26, 1701-1718. doi: 10.1002/jcc.20291
138. Vihinen, M., Torkkila, E., and Riikonen, P. (1994). Accuracy of protein flexibility predictions. Proteins 19, 141-149. doi: 10.1002/prot.340190207
139. Wu, C. Y., Chen, Y. C., and Lim, C. (2010). A structural-alphabet-based strategy for finding structural motifs across protein families. Nucleic Acids Res. 38:e150. doi: 10.1093/nar/gkq478
140. Xiao, T., Takagi, J., Coller, B. S., Wang, J. H., and Springer, T. A. (2004). Structural basis for allostery in integrins and binding to fibrinogen-mimetic therapeutics. Nature 432, 59-67. doi: 10.1038/nature02976
141. Xin, F., and Radivojac, P. (2012). Post-translational modifications induce significant yet not extreme changes to protein structure. Bioinformatics 28, 2905-2913. doi: 10.1093/bioinformatics/bts541
142. Xue, B., and Uversky, V. N. (2014). Intrinsic disorder in proteins involved in the innate antiviral immunity: another flexible side of a molecular arms race. J. Mol. Biol. 426, 1322-1350. doi: 10.1016/j.jmb.2013.10.030
143. Yang, J. M., and Tung, C. H. (2006). Protein structure database search and evolutionary classification. Nucleic Acids Res. 34, 3646-3659. doi: 10.1093/nar/gkl395
144. Zhang, H., and Kurgan, L. (2014). Improved prediction of residue flexibility by embedding optimized amino acid grouping into RSA-based linear models. Amino Acids 46, 2665-2680. doi: 10.1007/s00726-014-1817-9
145. Zhang, T., Faraggi, E., and Zhou, Y. (2010). Fluctuations of backbone torsion angles obtained from NMR-determined structures and their prediction. Proteins 78, 3353-3362. doi: 10.1002/prot.22842
146. Zhang, Y., Stec, B., and Godzik, A. (2007). Between order and disorder in protein structures: analysis of "dual personality" fragments in proteins. Structure 15, 1141-1147. doi: 10.1016/j.str.2007.07.012
147. Zhu, J., Luo, B. H., Xiao, T., Zhang, C., Nishida, N., and Springer, T. A. (2008). Structure of a complete integrin ectodomain in a physiologic resting state and activation and deactivation by applied forces. Mol. Cell 32, 849-861. doi: 10.1016/j.molcel.2008.11.018
148. Zimmermann, O., and Hansmann, U. H. (2008). LOCUSTRA: accurate prediction of local protein structure using a two-layer support vector machine approach. J. Chem. Inf. Model. 48, 1903-1908. doi: 10.1021/ci800178a