Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Meet Me Halfway: When Genomics Meets Structural Bioinformatics

Abstract

The DNA sequencing technology developed by Frederick Sanger in the 1970s established genomics as the basis of comparative genetics. The recent invention of next-generation sequencing (NGS) platform has added a new dimension to genome research by generating ultra-fast and high-throughput sequencing data in an unprecedented manner. The advent of NGS technology also provides the opportunity to study genetic diseases where sequence variants or mutations are sought to establish a causal relationship with disease phenotypes. However, it is not a trivial task to seek genetic variants responsible for genetic diseases and even harder for complex diseases such as diabetes and cancers. In such polygenic diseases, multiple genes and alleles, which can exist in healthy individuals, come together to contribute to common disease phenotypes in a complex manner. Hence, it is desirable to have an approach that integrates omics data with both knowledge of protein structure and function and an understanding of networks/pathways, i.e. functional genomics and systems biology; in this way, genotype–phenotype relationships can be better understood. In this review, we bring this ‘bottom-up’ approach alongside the current NGS-driven genetic study of genetic variations and disease aetiology. We describe experimental and computational techniques for assessing genetic variants and their deleterious effects on protein structure and function.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Notes

  1. 1.

    http://www.genome.gov/gwastudies/.

  2. 2.

    http://www.wtccc.org.uk/.

  3. 3.

    http://www.genome.gov/10005107.

  4. 4.

    http://www.1000genomes.org.

  5. 5.

    http://www-cryst.bioc.cam.ac.uk/∼sdm/sdm.php.

  6. 6.

    http://www.bongo.cl.cam.ac.uk/Bongo/.

  7. 7.

    http://www-cryst.bioc.cam.ac.uk/samul (or http://samul.org, alternatively).

  8. 8.

    http://www.dasregistry.org/.

References

  1. 1.

    Metzker, M. L. (2010). Sequencing technologies—The next generation. Nature Reviews. Genetics, 11(1), 31–46.

  2. 2.

    Wheeler, D. A., Srinivasan, M., Egholm, M., Shen, Y., Chen, L., McGuire, A., et al. (2008). The complete genome of an individual by massively parallel DNA sequencing. Nature, 452(7189), 872–876.

  3. 3.

    Sherry, S. T., Ward, M. H., Kholodov, M., Baker, J., Phan, L., Smigielski, E. M., et al. (2001). dbSNP: The NCBI database of genetic variation. Nucleic Acids Research, 29(1), 308–311.

  4. 4.

    Hamosh, A., Scott, A. F., Amberger, J., Bocchini, C., Valle, D., & McKusick, V. A. (2002). Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Research, 30(1), 52–55.

  5. 5.

    Hamosh, A., Scott, A. F., Amberger, J. S., Bocchini, C. A., & McKusick, V. A. (2005). Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Research, 33, D514–517.

  6. 6.

    Schork, N. J., Fallin, D., & Lanchbury, J. S. (2000). Single nucleotide polymorphisms and the future of genetic epidemiology. Clinical Genetics, 58(4), 250–264.

  7. 7.

    Kruglyak, L., & Nickerson, D. A. (2001). Variation is the spice of life. Nature Genetics, 27(3), 234–236.

  8. 8.

    Stephens, J. C., Schneider, J. A., Tanguay, D. A., Choi, J., Acharya, T., Stanley, S. E., et al. (2001). Haplotype variation and linkage disequilibrium in 313 human genes. Science, 293(5529), 489–493.

  9. 9.

    Chakravarti, A. (1998). It’s raining SNPs, hallelujah? Nature Genetics, 19(3), 216–217.

  10. 10.

    Collins, F. S., Brooks, L. D., & Chakravarti, A. (1998). A DNA polymorphism discovery resource for research on human genetic variation. Genome Research, 8(12), 1229–1231.

  11. 11.

    Emahazion, T., Feuk, L., Jobs, M., Sawyer, S. L., Fredman, D., St Clair, D., et al. (2001). SNP association studies in Alzheimer’s disease highlight problems for complex disease analysis. Trends in Genetics, 17(7), 407–413.

  12. 12.

    Pirmohamed, M. (2006). Genetic factors in the predisposition to drug-induced hypersensitivity reactions. The AAPS Journal, 8(1), E20–26.

  13. 13.

    Lohmueller, K. E., Pearce, C. L., Pike, M., Lander, E. S., & Hirschhorn, J. N. (2003). Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nature Genetics, 33(2), 177–182.

  14. 14.

    Risch, N., & Merikangas, K. (1996). The future of genetic studies of complex human diseases. Science, 273(5281), 1516–1517.

  15. 15.

    Kruglyak, L. (1999). Prospects for whole-genome linkage disequilibrium mapping of common disease genes. Nature Genetics, 22(2), 139–144.

  16. 16.

    Tsigelny, I. F., Kotlovyi, V., & Wasserman, L. (2004). SNP analysis combined with protein structure prediction defines structure–functional relationships in cancer related cytochrome P450 estrogen metabolism. Current Medicinal Chemistry, 11(5), 525–538.

  17. 17.

    Botstein, D., & Risch, N. (2003). Discovering genotypes underlying human phenotypes: past successes for Mendelian disease, future approaches for complex disease. Nature Genetics, 33(Suppl), 228–237.

  18. 18.

    Lander, E. S. (1996). The new genomics: Global views of biology. Science, 274(5287), 536–539.

  19. 19.

    Stenson, P. D., Ball, E. V., Mort, M., Phillips, A. D., Shiel, J. A., Thomas, N. S., et al. (2003). Human Gene Mutation Database (HGMD): 2003 update. Human Mutation, 21(6), 577–581.

  20. 20.

    Wang, Z., & Moult, J. (2001). SNPs, protein structure, and disease. Human Mutation, 17(4), 263–270.

  21. 21.

    Yue, P., Li, Z., & Moult, J. (2005). Loss of protein structure stability as a major causative factor in monogenic disease. Journal of Molecular Biology, 353(2), 459–473.

  22. 22.

    Burke, D. F., Worth, C. L., Priego, E. M., Cheng, T., Smink, L. J., Todd, J. A., et al. (2007). Genome bioinformatic analysis of nonsynonymous SNPs. BMC Bioinformatics, 8, 301.

  23. 23.

    Worth, C. L., Bickerton, G. R., Schreyer, A., Forman, J. R., Cheng, T. M., Lee, S., et al. (2007). A structural bioinformatics approach to the analysis of nonsynonymous single nucleotide polymorphisms (nsSNPs) and their relation to disease. Journal of Bioinformatics and Computational Biology, 5(6), 1297–1318.

  24. 24.

    Mardis, E. R. (2008). Next-generation DNA sequencing methods. Annual Review of Genomics and Human Genetics, 9, 387–402.

  25. 25.

    Morozova, O., Hirst, M., & Marra, M. A. (2009). Applications of new sequencing technologies for transcriptome analysis. Annual Review of Genomics and Human Genetics, 10, 135–151.

  26. 26.

    McCarthy, M. I., Abecasis, G. R., Cardon, L. R., Goldstein, D. B., Little, J., Ioannidis, J. P., et al. (2008). Genome-wide association studies for complex traits: Consensus, uncertainty and challenges. Nature Reviews. Genetics, 9(5), 356–369.

  27. 27.

    Weir, B. S. (2008). Linkage disequilibrium and association mapping. Annual Review of Genomics and Human Genetics, 9, 129–142.

  28. 28.

    Hakonarson, H., Grant, S. F., Bradfield, J. P., Marchand, L., Kim, C. E., Glessner, J. T., et al. (2007). A genome-wide association study identifies KIAA0350 as a type 1 diabetes gene. Nature, 448(7153), 591–594.

  29. 29.

    Todd, J. A., Walker, N. M., Cooper, J. D., Smyth, D. J., Downes, K., Plagnol, V., et al. (2007). Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes. Nature Genetics, 39(7), 857–864.

  30. 30.

    Sladek, R., Rocheleau, G., Rung, J., Dina, C., Shen, L., Serre, D., et al. (2007). A genome-wide association study identifies novel risk loci for type 2 diabetes. Nature, 445(7130), 881–885.

  31. 31.

    Zeggini, E., Weedon, M. N., Lindgren, C. M., Frayling, T. M., Elliott, K. S., Lango, H., et al. (2007). Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science, 316(5829), 1336–1341.

  32. 32.

    Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., et al. (2007). Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants. Nature Genetics, 39(11), 1329–1337.

  33. 33.

    Consortium WTCC. (2007). Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, 447(7145), 661–678.

  34. 34.

    Dalgliesh, G. L., Furge, K., Greenman, C., Chen, L., Bignell, G., Butler, A., et al. (2010). Systematic sequencing of renal carcinoma reveals inactivation of histone modifying genes. Nature, 463(7279), 360–363.

  35. 35.

    Greenman, C., Stephens, P., Smith, R., Dalgliesh, G. L., Hunter, C., Bignell, G., et al. (2007). Patterns of somatic mutation in human cancer genomes. Nature, 446(7132), 153–158.

  36. 36.

    Pleasance, E. D., Cheetham, R. K., Stephens, P. J., McBride, D. J., Humphray, S. J., Greenman, C. D., et al. (2010). A comprehensive catalogue of somatic mutations from a human cancer genome. Nature, 463(7278), 191–196.

  37. 37.

    Wood, L. D., Parsons, D. W., Jones, S., Lin, J., Sjoblom, T., Leary, R. J., et al. (2007). The genomic landscapes of human breast and colorectal cancers. Science, 318(5853), 1108–1113.

  38. 38.

    Hulbert, E. M., Smink, L. J., Adlem, E. C., Allen, J. E., Burdick, D. B., Burren, O. S., et al. (2007). T1DBase: Integration and presentation of complex data for type 1 diabetes research. Nucleic Acids Research, 35, D742–746.

  39. 39.

    Forbes, S. A., Bhamra, G., Bamford, S., Dawson, E., Kok, C., Clements, J., Menzies, A., Teague, J. W., Futreal, P. A., & Stratton, M. R. (2008). The Catalogue of Somatic Mutations in Cancer (COSMIC). Current Protococls in Human Genetics, Chapter 10:Unit 10.11.

  40. 40.

    Church, D. M., Lappalainen, I., Sneddon, T. P., Hinton, J., Maguire, M., Lopez, J., et al. (2010). Public data archives for genomic structural variation. Nature Genetics, 42(10), 813–814.

  41. 41.

    Yip, Y. L., Scheib, H., Diemand, A. V., Gattiker, A., Famiglietti, L. M., Gasteiger, E., et al. (2004). The Swiss-Prot variant page and the ModSNP database: A resource for sequence and structure information on human protein variants. Human Mutation, 23(5), 464–470.

  42. 42.

    Mottaz, A., David, F. P., Veuthey, A. L., & Yip, Y. L. (2010). Easy retrieval of single amino-acid polymorphisms and phenotype information using SwissVar. Bioinformatics, 26(6), 851–852.

  43. 43.

    Cargill, M., Altshuler, D., Ireland, J., Sklar, P., Ardlie, K., Patil, N., et al. (1999). Characterization of single-nucleotide polymorphisms in coding regions of human genes. Nature Genetics, 22(3), 231–238.

  44. 44.

    Sunyaev, S., Hanke, J., Aydin, A., Wirkner, U., Zastrow, I., Reich, J., et al. (1999). Prediction of nonsynonymous single nucleotide polymorphisms in human disease-associated genes. Journal of Molecular Medicine, 77(11), 754–760.

  45. 45.

    Botstein, D., White, R. L., Skolnick, M., & Davis, R. W. (1980). Construction of a genetic linkage map in man using restriction fragment length polymorphisms. American Journal of Human Genetics, 32(3), 314–331.

  46. 46.

    Solomon, E., & Bodmer, W. F. (1979). Evolution of sickle variant gene. Lancet, 1(8122), 923.

  47. 47.

    Kan, Y. W., & Dozy, A. M. (1978). Polymorphism of DNA sequence adjacent to human beta-globin structural gene: Relationship to sickle mutation. Proceedings of the National Academy of Sciences of the United States of America, 75(11), 5631–5635.

  48. 48.

    Feder, J. N., Gnirke, A., Thomas, W., Tsuchihashi, Z., Ruddy, D. A., Basava, A., et al. (1996). A novel MHC class I-like gene is mutated in patients with hereditary haemochromatosis. Nature Genetics, 13(4), 399–408.

  49. 49.

    Enattah, N. S., Sahi, T., Savilahti, E., Terwilliger, J. D., Peltonen, L., & Jarvela, I. (2002). Identification of a variant associated with adult-type hypolactasia. Nature Genetics, 30(2), 233–237.

  50. 50.

    Kruglyak, L. (2008). The road to genome-wide association studies. Nat Rev Genet, 9, 314–318.

  51. 51.

    Sunyaev, S., Ramensky, V., & Bork, P. (2000). Towards a structural basis of human non-synonymous single nucleotide polymorphisms. Trends in Genetics, 16(5), 198–200.

  52. 52.

    Ferrer-Costa, C., Orozco, M., & de la Cruz, X. (2002). Characterization of disease-associated single amino acid polymorphisms in terms of sequence and structure properties. Journal of Molecular Biology, 315(4), 771–786.

  53. 53.

    Ng, P. C., & Henikoff, S. (2001). Predicting deleterious amino acid substitutions. Genome Research, 11(5), 863–874.

  54. 54.

    Steward, R. E., MacArthur, M. W., Laskowski, R. A., & Thornton, J. M. (2003). Molecular basis of inherited diseases: A structural perspective. Trends in Genetics, 19(9), 505–513.

  55. 55.

    Worth CL, Burke DF, Blundell TL (2007) Estimating the effects of single nucleotide polymorphisms on protein structure: How good are we at identifying likely disease associated mutations? Proceedings of Molecular Interactions—Bringing Chemistry to Life, pp. 11–26.

  56. 56.

    Gong, S., Worth, C. L., Bickerton, G. R., Lee, S., Tanramluk, D., & Blundell, T. L. (2009). Structural and functional restraints in the evolution of protein families and superfamilies. Biochemical Society Transactions, 37(Pt 4), 727–733.

  57. 57.

    Kimura, M. (1983). The neutral theory of evolution. Cambridge: Cambridge University Press.

  58. 58.

    Ohta, T. (1973). Slightly deleterious mutant substitutions in evolution. Nature, 246(5428), 96–98.

  59. 59.

    Worth, C. L., Gong, S., & Blundell, T. L. (2009). Structural and functional constraints in the evolution of protein families. Nature Reviews. Molecular Cell Biology, 10(10), 709–720.

  60. 60.

    Gusella, J. F., Wexler, N. S., Conneally, P. M., Naylor, S. L., Anderson, M. A., Tanzi, R. E., et al. (1983). A polymorphic DNA marker genetically linked to Huntington’s disease. Nature, 306(5940), 234–238.

  61. 61.

    Kerem, B., Rommens, J. M., Buchanan, J. A., Markiewicz, D., Cox, T. K., Chakravarti, A., et al. (1989). Identification of the cystic fibrosis gene: Genetic analysis. Science, 245(4922), 1073–1080.

  62. 62.

    Riordan, J. R., Rommens, J. M., Kerem, B., Alon, N., Rozmahel, R., Grzelczak, Z., et al. (1989). Identification of the cystic fibrosis gene: Cloning and characterization of complementary DNA. Science, 245(4922), 1066–1073.

  63. 63.

    Frazer, K. A., Murray, S. S., Schork, N. J., & Topol, E. J. (2009). Human genetic variation and its contribution to complex traits. Nature Reviews. Genetics, 10(4), 241–251.

  64. 64.

    Durbin, R. M., Abecasis, G. R., Altshuler, D. L., Auton, A., Brooks, L. D., Durbin, R. M., et al. (2010). A map of human genome variation from population-scale sequencing. Nature, 467(7319), 1061–1073.

  65. 65.

    Matthews, B. W. (1993). Structural and genetic analysis of protein stability. Annual Review of Biochemistry, 62, 139–160.

  66. 66.

    Pakula, A. A., & Sauer, R. T. (1989). Genetic analysis of protein stability and function. Annual Review of Genetics, 23, 289–310.

  67. 67.

    Ruotolo, B. T., Benesch, J. L., Sandercock, A. M., Hyung, S. J., & Robinson, C. V. (2008). Ion mobility–mass spectrometry analysis of large protein complexes. Nature Protocols, 3(7), 1139–1152.

  68. 68.

    McLaughlin, S. H., & Jackson, S. E. (2002). Folding and stability of the ligand-binding domain of the glucocorticoid receptor. Protein Science, 11(8), 1926–1936.

  69. 69.

    Perrett, S., Freeman, S. J., Butler, P. J., & Fersht, A. R. (1999). Equilibrium folding properties of the yeast prion protein determinant Ure2. Journal of Molecular Biology, 290(1), 331–345.

  70. 70.

    Jackson, S. E., el Masry, N., & Fersht, A. R. (1993). Structure of the hydrophobic core in the transition state for folding of chymotrypsin inhibitor 2: A critical test of the protein engineering method of analysis. Biochemistry, 32(42), 11270–11278.

  71. 71.

    Main, E. R., Fulton, K. F., & Jackson, S. E. (1998). Context-dependent nature of destabilizing mutations on the stability of FKBP12. Biochemistry, 37(17), 6145–6153.

  72. 72.

    Wray, J. W., Baase, W. A., Lindstrom, J. D., Weaver, L. H., Poteete, A. R., & Matthews, B. W. (1999). Structural analysis of a non-contiguous second-site revertant in T4 lysozyme shows that increasing the rigidity of a protein can enhance its stability. Journal of Molecular Biology, 292(5), 1111–1120.

  73. 73.

    Itzhaki, L. S., Evans, P. A., Dobson, C. M., & Radford, S. E. (1994). Tertiary interactions in the folding pathway of hen lysozyme: Kinetic studies using fluorescent probes. Biochemistry, 33(17), 5212–5220.

  74. 74.

    Mallam, A. L., & Jackson, S. E. (2007). A comparison of the folding of two knotted proteins: YbeA and YibK. Journal of Molecular Biology, 366(2), 650–665.

  75. 75.

    Clarke, J., Hounslow, A. M., & Fersht, A. R. (1995). Disulfide mutants of barnase. II: Changes in structure and local stability identified by hydrogen exchange. Journal of Molecular Biology, 253(3), 505–513.

  76. 76.

    Clifford, S. C., Cockman, M. E., Smallwood, A. C., Mole, D. R., Woodward, E. R., Maxwell, P. H., et al. (2001). Contrasting effects on HIF-1alpha regulation by disease-causing pVHL mutations correlate with patterns of tumourigenesis in von Hippel–Lindau disease. Human Molecular Genetics, 10(10), 1029–1038.

  77. 77.

    Tanoue, T., Adachi, M., Moriguchi, T., & Nishida, E. (2000). A conserved docking motif in MAP kinases common to substrates, activators and regulators. Nature Cell Biology, 2(2), 110–116.

  78. 78.

    Takayama, N., Kizaki, M., Hida, T., Kinjo, K., & Ikeda, Y. (2001). Novel mutation in the PML/RARalpha chimeric gene exhibits dramatically decreased ligand-binding activity and confers acquired resistance to retinoic acid in acute promyelocytic leukemia. Experimental Hematology, 29(7), 864–872.

  79. 79.

    Jackson, S. E., & Fersht, A. R. (1994). Contribution of residues in the reactive site loop of chymotrypsin inhibitor two to protein stability and activity. Biochemistry, 33(46), 13880–13887.

  80. 80.

    Poliakov, E., Gentleman, S., Cunningham, F. X., Jr., Miller-Ihli, N. J., & Redmond, T. M. (2005). Key role of conserved histidines in recombinant mouse beta-carotene 15,15′-monooxygenase-1 activity. The Journal of Biological Chemistry, 280(32), 29217–29223.

  81. 81.

    Alber, T., Sun, D. P., Nye, J. A., Muchmore, D. C., & Matthews, B. W. (1987). Temperature-sensitive mutations of bacteriophage T4 lysozyme occur at sites with low mobility and low solvent accessibility in the folded protein. Biochemistry, 26(13), 3754–3758.

  82. 82.

    Clarke, J., Henrick, K., & Fersht, A. R. (1995). Disulfide mutants of barnase. I: Changes in stability and structure assessed by biophysical methods and X-ray crystallography. Journal of Molecular Biology, 253(3), 493–504.

  83. 83.

    Matthews, B. W., Nicholson, H., & Becktel, W. J. (1987). Enhanced protein thermostability from site-directed mutations that decrease the entropy of unfolding. Proceedings of the National Academy of Sciences of the United States of America, 84(19), 6663–6667.

  84. 84.

    Pace, C. N., Horn, G., Hebert, E. J., Bechert, J., Shaw, K., Urbanikova, L., et al. (2001). Tyrosine hydrogen bonds make a large contribution to protein stability. Journal of Molecular Biology, 312(2), 393–404.

  85. 85.

    Stollar, E. J., Mayor, U., Lovell, S. C., Federici, L., Freund, S. M., Fersht, A. R., et al. (2003). Crystal structures of engrailed homeodomain mutants: Implications for stability and dynamics. The Journal of Biological Chemistry, 278(44), 43699–43708.

  86. 86.

    Ekblad, C. M., Wilkinson, H. R., Schymkowitz, J. W., Rousseau, F., Freund, S. M., & Itzhaki, L. S. (2002). Characterisation of the BRCT domains of the breast cancer susceptibility gene product BRCA1. Journal of Molecular Biology, 320(3), 431–442.

  87. 87.

    Tang, K. S., Guralnick, B. J., Wang, W. K., Fersht, A. R., & Itzhaki, L. S. (1999). Stability and folding of the tumour suppressor protein p16. Journal of Molecular Biology, 285(4), 1869–1886.

  88. 88.

    Bullock, A. N., Henckel, J., DeDecker, B. S., Johnson, C. M., Nikolova, P. V., Proctor, M. R., et al. (1997). Thermodynamic stability of wild-type and mutant p53 core domain. Proceedings of the National Academy of Sciences of the United States of America, 94(26), 14338–14342.

  89. 89.

    Friedler, A., Veprintsev, D. B., Hansson, L. O., & Fersht, A. R. (2003). Kinetic instability of p53 core domain mutants: Implications for rescue by small molecules. The Journal of Biological Chemistry, 278(26), 24108–24112.

  90. 90.

    Nikolova, P. V., Henckel, J., Lane, D. P., & Fersht, A. R. (1998). Semirational design of active tumor suppressor p53 DNA binding domain with enhanced stability. Proceedings of the National Academy of Sciences of the United States of America, 95(25), 14675–14680.

  91. 91.

    Joerger, A. C., Allen, M. D., & Fersht, A. R. (2004). Crystal structure of a superstable mutant of human p53 core domain. Insights into the mechanism of rescuing oncogenic mutations. The Journal of Biological Chemistry, 279(2), 1291–1296.

  92. 92.

    Joerger, A. C., Ang, H. C., Veprintsev, D. B., Blair, C. M., & Fersht, A. R. (2005). Structures of p53 cancer mutants and mechanism of rescue by second-site suppressor mutations. The Journal of Biological Chemistry, 280(16), 16030–16037.

  93. 93.

    Ang, H. C., Joerger, A. C., Mayer, S., & Fersht, A. R. (2006). Effects of common cancer mutations on stability and DNA binding of full-length p53 compared with isolated core domains. The Journal of Biological Chemistry, 281(31), 21934–21941.

  94. 94.

    Cheon, D. J., & Orsulic, S. (2011). Mouse models of cancer. Annu Rev Pathol, 6, 95–119.

  95. 95.

    Jucker, M. (2010). The benefits and limitations of animal models for translational research in neurodegenerative diseases. Natural Medicines, 16(11), 1210–1214.

  96. 96.

    Scheikl, T., Pignolet, B., Mars, L. T., & Liblau, R. S. (2010). Transgenic mouse models of multiple sclerosis. Cellular and Molecular Life Sciences, 67(23), 4011–4034.

  97. 97.

    Venter, J. C., Adams, M. D., Myers, E. W., Li, P. W., Mural, R. J., Sutton, G. G., et al. (2001). The sequence of the human genome. Science, 291(5507), 1304–1351.

  98. 98.

    Frazer, K. A., Ballinger, D. G., Cox, D. R., Hinds, D. A., Stuve, L. L., Gibbs, R. A., et al. (2007). A second generation human haplotype map of over 3.1 million SNPs. Nature, 449(7164), 851–861.

  99. 99.

    Lee, D., Redfern, O., & Orengo, C. (2007). Predicting protein function from sequence and structure. Nature Reviews. Molecular Cell Biology, 8(12), 995–1005.

  100. 100.

    Mooney, S. (2005). Bioinformatics approaches and resources for single nucleotide polymorphism functional analysis. Briefings in Bioinformatics, 6(1), 44–56.

  101. 101.

    Ng, P. C., & Henikoff, S. (2006). Predicting the effects of amino acid substitutions on protein function. Annual Review of Genomics and Human Genetics, 7, 61–80.

  102. 102.

    Topham, C. M., Srinivasan, N., & Blundell, T. L. (1997). Prediction of the stability of protein mutants based on structural environment-dependent amino acid substitution and propensity tables. Protein Engineering, 10(1), 7–21.

  103. 103.

    Guerois, R., Nielsen, J. E., & Serrano, L. (2002). Predicting changes in the stability of proteins and protein complexes: A study of more than 1000 mutations. Journal of Molecular Biology, 320(2), 369–387.

  104. 104.

    Capriotti, E., Fariselli, P., & Casadio, R. (2004). A neural-network-based method for predicting protein stability changes upon single point mutations. Bioinformatics, 20(1), i63–i68.

  105. 105.

    Capriotti, E., Fariselli, P., Calabrese, R., & Casadio, R. (2005). Predicting protein stability changes from sequences using support vector machines. Bioinformatics, 21(2), 54–58.

  106. 106.

    Capriotti, E., Fariselli, P., & Casadio, R. (2005). I-Mutant2.0: Predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Research, 33, W306–310.

  107. 107.

    Cheng, J., Randall, A., & Baldi, P. (2006). Prediction of protein stability changes for single-site mutations using support vector machines. Proteins, 62(4), 1125–1132.

  108. 108.

    Parthiban, V., Gromiha, M. M., & Schomburg, D. (2006). CUPSAT: Prediction of protein stability upon point mutations. Nucleic Acids Research, 34, W239–242.

  109. 109.

    Yin, S., Ding, F., & Dokholyan, N. V. (2007). Modeling backbone flexibility improves protein stability estimation. Structure, 15(12), 1567–1576.

  110. 110.

    Fernandez-Escamilla, A. M., Rousseau, F., Schymkowitz, J., & Serrano, L. (2004). Prediction of sequence-dependent and mutational effects on the aggregation of peptides and proteins. Nature Biotechnology, 22(10), 1302–1306.

  111. 111.

    Conchillo-Sole, O., de Groot, N. S., Aviles, F. X., Vendrell, J., Daura, X., & Ventura, S. (2007). AGGRESCAN: A server for the prediction and evaluation of “hot spots” of aggregation in polypeptides. BMC Bioinformatics, 8, 65.

  112. 112.

    Trovato, A., Seno, F., & Tosatto, S. C. (2007). The PASTA server for protein aggregation prediction. Protein Engineering, Design & Selection, 20(10), 521–523.

  113. 113.

    Morgan, D. H., Kristensen, D. M., Mittelman, D., & Lichtarge, O. (2006). ET viewer: An application for predicting and visualizing functional sites in protein structures. Bioinformatics, 22(16), 2049–2050.

  114. 114.

    Joachimiak, M. P., & Cohen, F. E. (2002). JEvTrace: Refinement and variations of the evolutionary trace in JAVA. Genome Biology, 3(12), RESEARCH0077.

  115. 115.

    La, D., & Livesay, D. R. (2005). MINER: Software for phylogenetic motif identification. Nucleic Acids Research, 33, W267–270.

  116. 116.

    Chelliah, V., Blundell, T., & Mizuguchi, K. (2005). Functional restraints on the patterns of amino acid substitutions: Application to sequence–structure homology recognition. Proteins, 61(4), 722–731.

  117. 117.

    Porter, C. T., Bartlett, G. J., & Thornton, J. M. (2004). The Catalytic Site Atlas: A resource of catalytic sites and residues identified in enzymes using structural data. Nucleic Acids Research, 32, D129–133.

  118. 118.

    Ivanisenko, V. A., Pintus, S. S., Grigorovich, D. A., & Kolchanov, N. A. (2004). PDBSiteScan: A program for searching for active, binding and posttranslational modification sites in the 3D structures of proteins. Nucleic Acids Research, 32, W549–554.

  119. 119.

    Golovin, A., Dimitropoulos, D., Oldfield, T., Rachedi, A., & Henrick, K. (2005). MSDsite: A database search and retrieval system for the analysis and viewing of bound ligands and active sites. Proteins, 58(1), 190–199.

  120. 120.

    Rohl, C. A., Strauss, C. E., Misura, K. M., & Baker, D. (2004). Protein structure prediction using Rosetta. Methods Enzymol, 383, 66–93.

  121. 121.

    Ng, P. C., & Henikoff, S. (2002). Accounting for human polymorphisms predicted to affect protein function. Genome Research, 12(3), 436–446.

  122. 122.

    Sunyaev, S., Ramensky, V., Koch, I., Lathe, W., 3rd, Kondrashov, A. S., & Bork, P. (2001). Prediction of deleterious human alleles. Human Molecular Genetics, 10(6), 591–597.

  123. 123.

    Bao, L., Zhou, M., & Cui, Y. (2005). nsSNPAnalyzer: Identifying disease-associated nonsynonymous single nucleotide polymorphisms. Nucleic Acids Research, 33, W480–482.

  124. 124.

    Bromberg, Y., & Rost, B. (2007). SNAP: Predict effect of non-synonymous polymorphisms on function. Nucleic Acids Research, 35(11), 3823–3835.

  125. 125.

    Capriotti, E., Calabrese, R., & Casadio, R. (2006). Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary information. Bioinformatics, 22(22), 2729–2734.

  126. 126.

    Blundell, T. L., Cooper, J., Donnelly, D., Driessen, H., Edwards, Y., Eisenmenger, F., et al. (1991). Patterns of sequence variation in families of homologous proteins. In H. Jornvall, J. O. Hoog, & A. M. Gustavsson (Eds.), Methods in proteins sequence analysis (pp. 373–385). Basel: Birkhauser Verlag AG.

  127. 127.

    Overington, J., Johnson, M. S., Sali, A., & Blundell, T. L. (1990). Tertiary structural constraints on protein evolutionary diversity: Templates, key residues and structure prediction. Proc Biol Sci, 241(1301), 132–145.

  128. 128.

    Ferguson, B. J., Alexander, C., Rossi, S. W., Liiv, I., Rebane, A., Worth, C. L., et al. (2008). AIRE’s CARD revealed, a new structure for central tolerance provokes transcriptional plasticity. The Journal of Biological Chemistry, 283(3), 1723–1731.

  129. 129.

    Velho, S., Oliveira, C., Paredes, J., Sousa, S., Leite, M., Matos, P., et al. (2010). Mixed lineage kinase three gene mutations in mismatch repair deficient gastrointestinal tumours. Human Molecular Genetics, 19(4), 697–706.

  130. 130.

    Nagpal, K., Plantinga, T. S., Wong, J., Monks, B. G., Gay, N. J., Netea, M. G., et al. (2009). A TIR domain variant of MyD88 adapter-like (Mal)/TIRAP results in loss of MyD88 binding and reduced TLR2/TLR4 signaling. The Journal of Biological Chemistry, 284(38), 25742–25748.

  131. 131.

    Rowling, P. J., Cook, R., & Itzhaki, L. S. (2010). Toward classification of BRCA1 missense variants using a biophysical approach. The Journal of Biological Chemistry, 285(26), 20080–20087.

  132. 132.

    Chelliah, V., Chen, L., Blundell, T. L., & Lovell, S. C. (2004). Distinguishing structural and functional restraints in evolution in order to identify interaction sites. Journal of Molecular Biology, 342(5), 1487–1504.

  133. 133.

    Lee, S., & Blundell, T. L. (2009). BIPA: A database for protein–nucleic acid interaction in 3D structures. Bioinformatics, 25(12), 1559–1560.

  134. 134.

    Schreyer, A., & Blundell, T. L. (2009). A protein–ligand interaction database for drug discovery. Chemical Biology & Drug Design, 73, 157–167.

  135. 135.

    Forman, J. R., Worth, C. L., Bickerton, G. R., Eisen, T. G., & Blundell, T. L. (2009). Structural bioinformatics mutation analysis reveals genotype–phenotype correlations in von Hippel–Lindau disease and suggests molecular mechanisms of tumorigenesis. Proteins, 77(1), 84–96.

  136. 136.

    Cangul, H., Morgan, N. V., Forman, J. R., Saglam, H., Aycan, Z., Yakut, T., et al. (2010). Novel TSHR mutations in consanguineous families with congenital nongoitrous hypothyroidism. Clin Endocrinol (Oxf), 73(5), 671–677.

  137. 137.

    Ricketts, C. J., Forman, J. R., Rattenberry, E., Bradshaw, N., Lalloo, F., Izatt, L., et al. (2010). Tumor risks and genotype–phenotype–proteotype analysis in 358 patients with germline mutations in SDHB and SDHD. Human Mutation, 31(1), 41–51.

  138. 138.

    Cheng, T. M., Lu, Y. E., Vendruscolo, M., Lio, P., & Blundell, T. L. (2008). Prediction by graph theoretic measures of structural effects in proteins arising from non-synonymous single nucleotide polymorphisms. PLoS Computational Biology, 4(7), e1000135.

  139. 139.

    Thomas, P. D., Campbell, M. J., Kejariwal, A., Mi, H., Karlak, B., Daverman, R., et al. (2003). PANTHER: A library of protein families and subfamilies indexed by function. Genome Research, 13(9), 2129–2141.

  140. 140.

    Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., et al. (2010). A method and server for predicting damaging missense mutations. Nat Methods, 7(4), 248–249.

  141. 141.

    Bickerton, G. R. (2009). Molecular characterization and evolutionary plasticity of protein–protein interfaces. Cambridge: Emmanuel College, University of Cambridge.

  142. 142.

    Lee, S., Brown, A., Pitt, W. R., Perez Higueruelo, A., Gong, S., Bickerton, G. R., et al. (2009). Structural interactomics: Informatics approaches to aid the interpretation of genetic variation and the development of novel therapeutics. Molecular Biosystems, 5, 1456–1472.

  143. 143.

    Mizuguchi, K., Deane, C. M., Blundell, T. L., Johnson, M. S., & Overington, J. P. (1998). JOY: Protein sequence–structure representation and analysis. Bioinformatics, 14(7), 617–623.

  144. 144.

    Jmol: An open-source Java viewer for chemical structures in 3D. http://www.jmol.org/.

  145. 145.

    Hubbard, T. J., Aken, B. L., Ayling, S., Ballester, B., Beal, K., Bragin, E., et al. (2009). Ensembl 2009. Nucleic Acids Research, 37, D690–697.

  146. 146.

    Yip, Y. L., Famiglietti, M., Gos, A., Duek, P. D., David, F. P., Gateau, A., et al. (2008). Annotating single amino acid polymorphisms in the UniProt/Swiss-Prot knowledgebase. Human Mutation, 29(3), 361–366.

  147. 147.

    Gong, S., & Blundell, T. L. (2008). Discarding functional residues from the substitution table improves predictions of active sites within three-dimensional structures. PLoS Computational Biology, 4(10), e1000179.

  148. 148.

    Stein, L. D., Mungall, C., Shu, S., Caudy, M., Mangone, M., Day, A., et al. (2002). The generic genome browser: A building block for a model organism system database. Genome Research, 12(10), 1599–1610.

  149. 149.

    Kent, W. J., Sugnet, C. W., Furey, T. S., Roskin, K. M., Pringle, T. H., Zahler, A. M., et al. (2002). The human genome browser at UCSC. Genome Research, 12(6), 996–1006.

  150. 150.

    Harris, T. W., Antoshechkin, I., Bieri, T., Blasiar, D., Chan, J., Chen, W. J., et al. (2010). WormBase: A comprehensive resource for nematode research. Nucleic Acids Research, 38, D463–467.

  151. 151.

    Prlic, A., Down, T. A., Kulesha, E., Finn, R. D., Kahari, A., & Hubbard, T. J. (2007). Integrating sequence and structural biology with DAS. BMC Bioinformatics, 8, 333.

  152. 152.

    Sanger, F., & Tuppy, H. (1951). The amino-acid sequence in the phenylalanyl chain of insulin. 2. The investigation of peptides from enzymic hydrolysates. The Biochemical Journal, 49(4), 481–490.

  153. 153.

    Sanger, F., & Tuppy, H. (1951). The amino-acid sequence in the phenylalanyl chain of insulin I. The identification of lower peptides from partial hydrolysates. The Biochemical Journal, 49(4), 463–481.

  154. 154.

    Consortium TU. (2007). The Universal Protein Resource (UniProt). Nucleic Acids Research, 35, D193–197.

  155. 155.

    Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T. N., Weissig, H., et al. (2000). The Protein Data Bank. Nucleic Acids Research, 28(1), 235–242.

  156. 156.

    Laskowski, R. A., & Thornton, J. M. (2008). Understanding the molecular machinery of genetics through 3D structures. Nature Reviews. Genetics, 9(2), 141–151.

  157. 157.

    Sali, A., & Blundell, T. L. (1990). Definition of general topological equivalence in protein structures. A procedure involving comparison of properties and relationships through simulated annealing and dynamic programming. Journal of Molecular Biology, 212(2), 403–428.

  158. 158.

    Sali, A., Overington, J. P., Johnson, M. S., & Blundell, T. L. (1990). From comparisons of protein sequences and structures to protein modelling and design. Trends in Biochemical Sciences, 15(6), 235–240.

  159. 159.

    Moult, J. (2005). A decade of CASP: Progress, bottlenecks and prognosis in protein structure prediction. Current Opinion in Structural Biology, 15(3), 285–289.

  160. 160.

    Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990). Basic local alignment search tool. Journal of Molecular Biology, 215(3), 403–410.

  161. 161.

    Altschul, S. F., Madden, T. L., Schaffer, A. A., Zhang, J., Zhang, Z., Miller, W., et al. (1997). Gapped BLAST and PSI-BLAST: A new generation of protein database search programs. Nucleic Acids Research, 25(17), 3389–3402.

  162. 162.

    Finn, R. D., Tate, J., Mistry, J., Coggill, P. C., Sammut, S. J., Hotz, H. R., et al. (2008). The Pfam protein families database. Nucleic Acids Research, 36, D281–288.

  163. 163.

    Rost, B. (1995). TOPITS: Threading one-dimensional predictions into three-dimensional structures. Proc Int Conf Intell Syst Mol Biol, 3, 314–321.

  164. 164.

    Shi, J., Blundell, T. L., & Mizuguchi, K. (2001). FUGUE: Sequence–structure homology recognition using environment-specific substitution tables and structure-dependent gap penalties. Journal of Molecular Biology, 310(1), 243–257.

  165. 165.

    Furnham, N., de Bakker, P. I., Gore, S., Burke, D. F., & Blundell, T. L. (2008). Comparative modelling by restraint-based conformational sampling. BMC Structural Biology, 8(1), 7.

  166. 166.

    Gore, S. P., Karmali, A. M., & Blundell, T. L. (2007). Rappertk: A versatile engine for discrete restraint-based conformational sampling of macromolecules. BMC Structural Biology, 7, 13.

  167. 167.

    Sali, A., & Blundell, T. L. (1993). Comparative protein modelling by satisfaction of spatial restraints. Journal of Molecular Biology, 234(3), 779–815.

  168. 168.

    Bates, P. A., Kelley, L. A., MacCallum, R. M., & Sternberg, M. J. (2001). Enhancement of protein modeling by human intervention in applying the automatic programs 3D-JIGSAW and 3D-PSSM. Proteins Suppl, 5, 39–46.

  169. 169.

    Montalvao, R. W., Smith, R. E., Lovell, S. C., & Blundell, T. L. (2005). CHORAL: A differential geometry approach to the prediction of the cores of protein structures. Bioinformatics, 21(19), 3719–3725.

  170. 170.

    Peitsch, M. C., Wilkins, M. R., Tonella, L., Sanchez, J. C., Appel, R. D., & Hochstrasser, D. F. (1997). Large-scale protein modelling and integration with the SWISS-PROT and SWISS-2DPAGE databases: The example of Escherichia coli. Electrophoresis, 18(3–4), 498–501.

  171. 171.

    Sutcliffe, M. J., Hayes, F. R., & Blundell, T. L. (1987). Knowledge based modelling of homologous proteins, part II: Rules for the conformations of substituted sidechains. Protein Engineering, 1(5), 385–392.

  172. 172.

    Lovell, S. C., Davis, I. W., Arendall, W. B., 3rd, de Bakker, P. I., Word, J. M., Prisant, M. G., et al. (2003). Structure validation by Calpha geometry: Phi, psi and Cbeta deviation. Proteins, 50(3), 437–450.

  173. 173.

    Sippl, M. J. (1993). Recognition of errors in three-dimensional structures of proteins. Proteins, 17(4), 355–362.

  174. 174.

    Bradley, P., Misura, K. M., & Baker, D. (2005). Toward high-resolution de novo structure prediction for small proteins. Science, 309(5742), 1868–1871.

  175. 175.

    Alimonti, A., Carracedo, A., Clohessy, J. G., Trotman, L. C., Nardella, C., Egia, A., et al. (2010). Subtle variations in Pten dose determine cancer susceptibility. Nature Genetics, 42(5), 454–458.

  176. 176.

    Hindorff, L. A., Sethupathy, P., Junkins, H. A., Ramos, E. M., Mehta, J. P., Collins, F. S., et al. (2009). Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proceedings of the National Academy of Sciences of the United States of America, 106(23), 9362–9367.

  177. 177.

    Chamary, J. V., Parmley, J. L., & Hurst, L. D. (2006). Hearing silence: Non-neutral evolution at synonymous sites in mammals. Nature Rev Genet, 7, 98–108.

  178. 178.

    Clark, T. G., Andrew, T., Cooper, G. M., Margulies, E. H., Mullikin, J. C., & Balding, D. J. (2007). Functional constraint and small insertions and deletions in the ENCODE regions of the human genome. Genome Biology, 8(9), R180.

  179. 179.

    Mills, R. E., Luttig, C. T., Larkins, C. E., Beauchamp, A., Tsui, C., Pittard, W. S., et al. (2006). An initial map of insertion and deletion (INDEL) variation in the human genome. Genome Research, 16(9), 1182–1190.

  180. 180.

    Redon, R., Ishikawa, S., Fitch, K. R., Feuk, L., Perry, G. H., Andrews, T. D., et al. (2006). Global variation in copy number in the human genome. Nature, 444(7118), 444–454.

  181. 181.

    Sebat, J., Lakshmi, B., Troge, J., Alexander, J., Young, J., Lundin, P., et al. (2004). Large-scale copy number polymorphism in the human genome. Science, 305(5683), 525–528.

  182. 182.

    Sudmant, P. H., Kitzman, J. O., Antonacci, F., Alkan, C., Malig, M., Tsalenko, A., et al. (2010). Diversity of human copy number variation and multicopy genes. Science, 330(6004), 641–646.

  183. 183.

    Gemayel, R., Vinces, M. D., Legendre, M., & Verstrepen, K. J. (2010). Variable tandem repeats accelerate evolution of coding and regulatory sequences. Annual Review of Genetics, 44, 445–477.

  184. 184.

    McCarroll, S. A. (2010). Copy number variation and human genome maps. Nature Genetics, 42(5), 365–366.

  185. 185.

    Mullaney, J. M., Mills, R. E., Pittard, W. S., & Devine, S. E. (2010). Small insertions and deletions (INDELs) in human genomes. Human Molecular Genetics, 19(2), R131–136.

  186. 186.

    Soskine, M., & Tawfik, D. S. (2010). Mutational effects and the evolution of new protein functions. Nature Reviews. Genetics, 11(8), 572–582.

  187. 187.

    Stankiewicz, P., & Lupski, J. R. (2010). Structural variation in the human genome and its role in disease. Annual Review of Medicine, 61, 437–455.

  188. 188.

    Wain, L. V., Armour, J. A., & Tobin, M. D. (2009). Genomic copy number variation, human health, and disease. Lancet, 374(9686), 340–350.

  189. 189.

    Goldberg, A. L. (2003). Protein degradation and protection against misfolded or damaged proteins. Nature, 426(6968), 895–899.

  190. 190.

    Ferrer-Costa, C., Orozco, M., & de la Cruz, X. (2007). Characterization of compensated mutations in terms of structural and physico-chemical properties. Journal of Molecular Biology, 365(1), 249–256.

  191. 191.

    Marguerat, S., Wilhelm, B. T., & Bahler, J. (2008). Next-generation sequencing: Applications beyond genomes. Biochemical Society Transactions, 36(Pt 5), 1091–1096.

  192. 192.

    Wang, Z., Gerstein, M., & Snyder, M. (2009). RNA-Seq: A revolutionary tool for transcriptomics. Nature Reviews. Genetics, 10(1), 57–63.

  193. 193.

    Brookes, A. J., Lehvaslaiho, H., Siegfried, M., Boehm, J. G., Yuan, Y. P., Sarkar, C. M., et al. (2000). HGBASE: A database of SNPs and other variations in and around human genes. Nucleic Acids Research, 28(1), 356–360.

  194. 194.

    Fredman, D., Siegfried, M., Yuan, Y. P., Bork, P., Lehvaslaiho, H., & Brookes, A. J. (2002). HGVbase: A human sequence variation database emphasizing data quality and a broad spectrum of data sources. Nucleic Acids Research, 30(1), 387–391.

  195. 195.

    Gromiha, M. M., An, J., Kono, H., Oobatake, M., Uedaira, H., & Sarai, A. (1999). ProTherm: Thermodynamic Database for Proteins and Mutants. Nucleic Acids Research, 27(1), 286–288.

  196. 196.

    Thorn, K. S., & Bogan, A. A. (2001). ASEdb: A database of alanine mutations and their effects on the free energy of binding in protein interactions. Bioinformatics, 17(3), 284–285.

  197. 197.

    Martin, A. C., Facchiano, A. M., Cuff, A. L., Hernandez-Boussard, T., Olivier, M., Hainaut, P., et al. (2002). Integrating mutation data and structural analysis of the TP53 tumor-suppressor protein. Human Mutation, 19(2), 149–164.

  198. 198.

    Kwok, C. J., Martin, A. C., Au, S. W., & Lam, V. M. (2002). G6PDdb, an integrated database of glucose-6-phosphate dehydrogenase (G6PD) mutations. Human Mutation, 19(3), 217–224.

  199. 199.

    Mooney, S. D., & Altman, R. B. (2003). MutDB: Annotating human variation with functionally relevant data. Bioinformatics, 19(14), 1858–1860.

  200. 200.

    Riva, A., & Kohane, I. S. (2002). SNPper: Retrieval and analysis of human SNPs. Bioinformatics, 18(12), 1681–1685.

  201. 201.

    Bamford, S., Dawson, E., Forbes, S., Clements, J., Pettett, R., Dogan, A., et al. (2004). The COSMIC (Catalogue of Somatic Mutations in Cancer) database and website. British Journal of Cancer, 91(2), 355–358.

  202. 202.

    Stitziel, N. O., Binkowski, T. A., Tseng, Y. Y., Kasif, S., & Liang, J. (2004). topoSNP: A topographic database of non-synonymous single nucleotide polymorphisms with and without known disease association. Nucleic Acids Research, 32, D520–522.

  203. 203.

    Karchin, R., Diekhans, M., Kelly, L., Thomas, D. J., Pieper, U., Eswar, N., et al. (2005). LS-SNP: Large-scale annotation of coding non-synonymous SNPs based on multiple information sources. Bioinformatics, 21(12), 2814–2820.

  204. 204.

    Hurst, J. M., McMillan, L. E., Porter, C. T., Allen, J., Fakorede, A., & Martin, A. C. (2009). The SAAPdb web resource: A large-scale structural analysis of mutant proteins. Human Mutation, 30(4), 616–624.

  205. 205.

    Reumers, J., Maurer-Stroh, S., Schymkowitz, J., & Rousseau, F. (2006). SNPeffect v2.0: A new step in investigating the molecular phenotypic effects of human non-synonymous SNPs. Bioinformatics, 22(17), 2183–2185.

  206. 206.

    Reumers, J., Schymkowitz, J., Ferkinghoff-Borg, J., Stricher, F., Serrano, L., & Rousseau, F. (2005). SNPeffect: A database mapping molecular phenotypic effects of human non-synonymous coding SNPs. Nucleic Acids Research, 33, D527–532.

  207. 207.

    Han, A., Kang, H. J., Cho, Y., Lee, S., Kim, Y. J., & Gong, S. (2006). SNP@Domain: A web resource of single nucleotide polymorphisms (SNPs) within protein domain structures and sequences. Nucleic Acids Research, 34, W642–644.

  208. 208.

    Jegga, A. G., Gowrisankar, S., Chen, J., & Aronow, B. J. (2007). PolyDoms: A whole genome database for the identification of non-synonymous coding SNPs with the potential to impact disease. Nucleic Acids Research, 35, D700–706.

  209. 209.

    Peterson, T. A., Adadey, A., Santana-Cruz, I., Sun, Y., Winder, A., & Kann, M. G. (2010). DMDM: Domain mapping of disease mutations. Bioinformatics, 26(19), 2458–2459.

  210. 210.

    Craddock, N., Hurles, M. E., Cardin, N., Pearson, R. D., Plagnol, V., Robson, S., et al. (2010). Genome-wide association study of CNVs in 16,000 cases of eight common diseases and 3,000 shared controls. Nature, 464(7289), 713–720.

  211. 211.

    Topham, C. M., McLeod, A., Eisenmenger, F., Overington, J. P., Johnson, M. S., & Blundell, T. L. (1993). Fragment ranking in modelling of protein structure. Conformationally constrained environmental amino acid substitution tables. Journal of Molecular Biology, 229(1), 194–220.

  212. 212.

    Dehouck, Y., Grosfils, A., Folch, B., Gilis, D., Bogaerts, P., & Rooman, M. (2009). Fast and accurate predictions of protein stability changes upon mutations using statistical potentials and neural networks: PoPMuSiC-2.0. Bioinformatics, 25, 2537–2543.

  213. 213.

    Gilis, D., & Rooman, M. (2000). PoPMuSiC, an algorithm for predicting protein mutant stability changes: Application to prion proteins. Protein Engineering, 13(12), 849–856.

  214. 214.

    Zhou, H., & Zhou, Y. (2002). Distance-scaled, finite ideal-gas reference state improves structure-derived potentials of mean force for structure selection and stability prediction. Protein Science, 11(11), 2714–2726.

  215. 215.

    Schymkowitz, J., Borg, J., Stricher, F., Nys, R., Rousseau, F., & Serrano, L. (2005). The FoldX web server: An online force field. Nucleic Acids Research, 33, W382–388.

  216. 216.

    Ramensky, V., Bork, P., & Sunyaev, S. (2002). Human non-synonymous SNPs: Server and survey. Nucleic Acids Research, 30(17), 3894–3900.

  217. 217.

    Christen, M., Hunenberger, P. H., Bakowies, D., Baron, R., Burgi, R., Geerke, D. P., et al. (2005). The GROMOS software for biomolecular simulation: GROMOS05. Journal of Computational Chemistry, 26(16), 1719–1751.

  218. 218.

    Ferrer-Costa, C., Gelpi, J. L., Zamakola, L., Parraga, I., de la Cruz, X., & Orozco, M. (2005). PMUT: A web-based tool for the annotation of pathological mutations on proteins. Bioinformatics, 21(14), 3176–3178.

  219. 219.

    Yuan, H. Y., Chiou, J. J., Tseng, W. H., Liu, C. H., Liu, C. K., Lin, Y. J., et al. (2006). FASTSNP: An always up-to-date and extendable service for SNP function analysis and prioritization. Nucleic Acids Research, 34, W635–641.

  220. 220.

    Yue, P., Melamud, E., & Moult, J. (2006). SNPs3D: Candidate gene and SNP selection for association studies. BMC Bioinformatics, 7, 166.

  221. 221.

    Yin, S., Ding, F., & Dokholyan, N. V. (2007). Eris: An automated estimator of protein stability. Nat Methods, 4(6), 466–467.

  222. 222.

    Ye, Z. Q., Zhao, S. Q., Gao, G., Liu, X. Q., Langlois, R. E., Lu, H., et al. (2007). Finding new structural and sequence attributes to predict possible disease association of single amino acid polymorphism (SAP). Bioinformatics, 23(12), 1444–1450.

  223. 223.

    Uzun, A., Leslin, C. M., Abyzov, A., & Ilyin, V. (2007). Structure SNP (StSNP): A web server for mapping and modeling nsSNPs on protein structures with linkage to metabolic pathways. Nucleic Acids Research, 35, W384–392.

  224. 224.

    Li, S., Ma, L., Li, H., Vang, S., Hu, Y., Bolund, L., et al. (2007). Snap: An integrated SNP annotation platform. Nucleic Acids Research, 35, D707–710.

  225. 225.

    Masso, M., & Vaisman, I. I. (2010). AUTO-MUTE: Web-based tools for predicting stability changes in proteins due to single amino acid replacements. Protein Engineering, Design & Selection, 23(8), 683–687.

  226. 226.

    Capriotti, E., Arbiza, L., Casadio, R., Dopazo, J., Dopazo, H., & Marti-Renom, M. A. (2008). Use of estimated evolutionary strength at the codon level improves the prediction of disease-related protein mutations in humans. Human Mutation, 29(1), 198–204.

  227. 227.

    Lee, P. H., & Shatkay, H. (2008). F-SNP: Computationally predicted functional SNPs for disease association studies. Nucleic Acids Research, 36, D820–824.

  228. 228.

    Brooks, B. R., Brooks, C. L., 3rd, Mackerell, A. D., Jr., Nilsson, L., Petrella, R. J., Roux, B., et al. (2009). CHARMM: The biomolecular simulation program. Journal of Computational Chemistry, 30(10), 1545–1614.

  229. 229.

    Kotowski, I. K., Pertsemlidis, A., Luke, A., Cooper, R. S., Vega, G. L., Cohen, J. C., et al. (2006). A spectrum of PCSK9 alleles contributes to plasma levels of low-density lipoprotein cholesterol. American Journal of Human Genetics, 78(3), 410–422.

  230. 230.

    Allard, D., Amsellem, S., Abifadel, M., Trillard, M., Devillers, M., Luc, G., et al. (2005). Novel mutations of the PCSK9 gene cause variable phenotype of autosomal dominant hypercholesterolemia. Human Mutation, 26(5), 497.

  231. 231.

    Murzin, A. G., Brenner, S. E., Hubbard, T., & Chothia, C. (1995). SCOP: A structural classification of proteins database for the investigation of sequences and structures. Journal of Molecular Biology, 247(4), 536–540.

Download references

Acknowledgement

We are grateful to all who are developing and maintaining biological databases, scientists submitting their invaluable data and people who support open-source programmes and operating systems. SG, CLW and TC want to thank the Blundell Group members for their support and collaborations during their stay in Cambridge.

Author information

Correspondence to Sungsam Gong.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Gong, S., Worth, C.L., Cheng, T.M.K. et al. Meet Me Halfway: When Genomics Meets Structural Bioinformatics. J. of Cardiovasc. Trans. Res. 4, 281–303 (2011). https://doi.org/10.1007/s12265-011-9259-1

Download citation

Keywords

  • Next-generation sequencing
  • Genotype–phenotype relationship
  • Single nucleotide polymorphism
  • Computational algorithm
  • Database