Free Access
| Issue |
Biologie Aujourd'hui
Volume 211, Number 3, 2017
|
|
|---|---|---|
| Page(s) | 239 - 244 | |
| Section | La biologie computationnelle parle à la biologie expérimentale | |
| DOI | https://doi.org/10.1051/jbio/2017030 | |
| Published online | 7 février 2018 | |
- Berman, H.M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N., Bourne, P.E. (2000). The Protein Data Bank. Nucleic Acids Res, 28, 235-242. [CrossRef] [PubMed] [Google Scholar]
- Biasini, M., Bienert, S., Waterhouse, A., Arnold, K., Studer, G., Schmidt, T., Kiefer, F., Gallo Cassarino, T., Bertoni, M., Bordoli, L., Schwede, T. (2014). SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucleic Acids Res, 42, W1, W252-W258. [Google Scholar]
- Bitbol, A.F., Dwyer, R.S., Colwell, L.J., Wingreen, N.S. (2016). Inferring interaction partners from protein sequences. Proc Nat Acad Sci USA, 113, 12180-12185. [CrossRef] [Google Scholar]
- Couce, A., Caudwell, L.V., Feinauer, C., Hindré, T., Feugeas, J.P., Weigt, M., Lenski, R.E., Schneider, D., Tenaillon, O. (2017). Mutator genomes decay, despite sustained fitness gains, in a long-term experiment with bacteria. Proc Nat Acad Sci USA, 114, E9026-E9035. [CrossRef] [Google Scholar]
- Dago, A.E., Schug, A., Procaccini, A., Hoch, J.A., Weigt, M., Szurmant, H. (2012). Structural basis of histidine kinase autophosphorylation deduced by integrating genomics, molecular dynamics, and mutagenesis. Proc Nat Acad Sci USA, 109, E1733-E1742. [CrossRef] [Google Scholar]
- De Juan, D., Pazos, F., Valencia A. (2013). Emerging methods in protein co-evolution. Nat Rev Genetics, 14, 249-261. [CrossRef] [Google Scholar]
- Durbin, R., Eddy, S.R., Krogh, A., Mitchison, G., Biological sequence analysis: probabilistic models of proteins and nucleic acids, Cambridge University Press, 1998. [Google Scholar]
- Eddy, S. R. (1998). Profile hidden Markov models. Bioinformatics, 14, 755-763. [CrossRef] [PubMed] [Google Scholar]
- Edgar, R.C., Batzoglou, S. (2006). Multiple sequence alignment. Curr Opin Struct Biol, 16, 368-373. [CrossRef] [PubMed] [Google Scholar]
- Ekeberg, M., Lövkvist, C., Lan, Y., Weigt, M., Aurell, E. (2013). Improved contact prediction in proteins: using pseudolikelihoods to infer Potts models. Phys Review, 87, 012707. [CrossRef] [Google Scholar]
- Feinauer, C., Szurmant, H., Weigt, M., Pagnani, A. (2016). Inter-protein sequence co-evolution predicts known physical interactions in bacterial ribosomes and the Trp operon. PLoS One, 11, e0149166. [CrossRef] [PubMed] [Google Scholar]
- Feinauer, C., Weigt, M. (2017). Context-aware prediction of pathogenicity of missense mutations involved in human disease. arXiv preprint arXiv:1701.07246 [Google Scholar]
- Figliuzzi, M., Jacquier, H., Schug, A., Tenaillon, O., Weigt, M. (2015). Coevolutionary landscape inference and the context-dependence of mutations in beta-lactamase TEM-1. Mol Biol Evol, 33, 268-280. [CrossRef] [PubMed] [Google Scholar]
- Finn, R.D., Bateman, A., Clements, J., Coggill, P., Eberhardt, R.Y., Eddy, S.R., Heger, A., Hetherington, K., Holm, L., Mistry, J., Sonnhammer, E.L., Tate, J., Punta, M. (2014). Pfam: the protein families database. Nucleic Acids Res, 42, D222-230. [CrossRef] [PubMed] [Google Scholar]
- Göbel, U., Sander, C., Schneider, R., Valencia, A. (1994). Correlated mutations and residue contacts in proteins. Proteins, 18, 309-317. [CrossRef] [PubMed] [Google Scholar]
- Gueudré, T., Baldassi, C., Zamparo, M., Weigt, M., Pagnani, A. (2016). Simultaneous identification of specifically interacting paralogs and interprotein contacts by direct coupling analysis. Proc Nat Acad Sci USA, 113, 12186-12191. [CrossRef] [Google Scholar]
- Haldane, A., Flynn, W.F., He, P., Vijayan, R.S., Levy, R.M. (2016). Structural propensities of kinase family proteins from a Potts model of residue co-variation. Protein Sci, 25, 1378-1384. [CrossRef] [PubMed] [Google Scholar]
- Hopf, T.A., Colwell, L.J., Sheridan, R., Rost, B., Sander, C., Marks, D.S. (2012). Three-dimensional structures of membrane proteins from genomic sequencing. Cell, 149, 1607-1621. [CrossRef] [PubMed] [Google Scholar]
- Hopf, T.A., Schärfe, C.P., Rodrigues, J.P., Green, A.G., Kohlbacher, O., Sander, C., Bonvin, A.M., Marks, D.S. (2014). Sequence co-evolution gives 3D contacts and structures of protein complexes. Elife, 3, e03430. [CrossRef] [Google Scholar]
- Hopf, T.A., Ingraham, J.B., Poelwijk, F.J., Schärfe, C.P., Springer, M., Sander, C., Marks, D.S. (2017). Mutation effects predicted from sequence co-variation. Nat Biotechnol, 35, 128-135. [CrossRef] [PubMed] [Google Scholar]
- Jones, D.T., Buchan, D.W., Cozzetto, D., Pontil, M. (2012) PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments. Bioinformatics, 28, 184-190. [CrossRef] [PubMed] [Google Scholar]
- Jones, D.T., Singh, T., Kosciolek, T., Tetchner, S. (2015). MetaPSICOV: combining coevolution methods for accurate prediction of contacts and long range hydrogen bonding in proteins. Bioinformatics, 31, 999-1006. [CrossRef] [PubMed] [Google Scholar]
- Kamisetty, H., Ovchinnikov, S., Baker, D. (2013). Assessing the utility of coevolution-based residue–residue contact predictions in a sequence-and structure-rich era. Proc Nat Acad Sci USA, 110, 15674-15679. [CrossRef] [Google Scholar]
- Mann, J.K., Barton, J.P., Ferguson, A.L., Omarjee, S., Walker, B.D., Chakraborty, A., Ndung'u, T. (2014). The fitness landscape of HIV-1 gag: advanced modeling approaches and validation of model predictions by in vitro testing. PLoS Comput Biol, 10, e1003776. [CrossRef] [Google Scholar]
- Marks, D.S., Colwell, L.J., Sheridan, R., Hopf, T.A., Pagnani, A., Zecchina, R., Sander, C. (2011). Protein 3D structure computed from evolutionary sequence variation. PLoS One, 6, e28766. [CrossRef] [PubMed] [Google Scholar]
- Morcos, F., Pagnani, A., Lunt, B., Bertolino, A., Marks, D.S., Sander, C., Zecchina, R., Onuchic, J.N., Hwa, T., Weigt, M. (2011). Direct-coupling analysis of residue coevolution captures native contacts across many protein families. Proc Nat Acad Sci USA, 108, E1293-E1301. [CrossRef] [Google Scholar]
- Morcos, F., Schafer, N.P., Cheng, R.R., Onuchic, J.N., Wolynes, P.G. (2014). Coevolutionary information, protein folding landscapes, and the thermodynamics of natural selection. Proc Nat Acad Sci USA, 111, 12408-12413. [CrossRef] [Google Scholar]
- Neher, E. (1994). How frequent are correlated changes in families of protein sequences? Proc Nat Acad Sci USA, 91, 98-102. [CrossRef] [Google Scholar]
- Nugent, T., Jones, D.T. (2012). Accurate de novo structure prediction of large transmembrane protein domains using fragment-assembly and correlated mutation analysis. Proc Nat Acad Sci USA, 109, E1540-E1547. [CrossRef] [Google Scholar]
- Ovchinnikov, S., Kamisetty, H., Baker, D. (2014). Robust and accurate prediction of residue–residue interactions across protein interfaces using evolutionary information. Elife, 3, e02030. [CrossRef] [PubMed] [Google Scholar]
- Ovchinnikov, S., Park, H., Varghese, N., Huang, P.S., Pavlopoulos, G.A., Kim, D.E., Kamisetty, H., Kyrpides, N.C., Baker, D. (2017). Protein structure determination using metagenome sequence data. Science, 355, 294-298. [CrossRef] [PubMed] [Google Scholar]
- Schug, A., Weigt, M., Onuchic, J.N., Hwa, T., Szurmant, H. (2009). High-resolution protein complexes from integrating genomic information with molecular simulation. Proc Nat Acad Sci USA, 106, 22124-22129. [CrossRef] [Google Scholar]
- Socolich, M., Lockless, S.W., Russ, W.P., Lee, H., Gardner, K.H., Ranganathan, R. (2005). Evolutionary information for specifying a protein fold. Nature, 437, 512-518. [CrossRef] [PubMed] [Google Scholar]
- Söding, J. (2004). Protein homology detection by HMM-HMM comparison. Bioinformatics, 21, 951-960. [CrossRef] [PubMed] [Google Scholar]
- Sułkowska, J.I., Morcos, F., Weigt, M., Hwa, T., Onuchic, J.N. (2012). Genomics-aided structure prediction. Proc Nat Acad Sci USA, 109, 10340-10345. [CrossRef] [Google Scholar]
- Sutto, L., Marsili, S., Valencia, A., Gervasio, F.L. (2015). From residue coevolution to protein conformational ensembles and functional dynamics. Proc Nat Acad Sci USA, 112, 13567-13572. [CrossRef] [Google Scholar]
- Uguzzoni, G., John Lovis, S., Oteri, F., Schug, A., Szurmant, H., Weigt, M. (2017). Large-scale identification of coevolution signals across homo-oligomeric protein interfaces by direct coupling analysis. Proc Nat Acad Sci USA, 114, E2662-E2671. [CrossRef] [Google Scholar]
- UniProt Consortium. UniProt: a hub for protein information. (2015). Nucleic Acids Res, 43, D204–212. [Google Scholar]
- Wang, S., Sun, S., Li, Z., Zhang, R., Xu, J. (2017). Accurate de novo prediction of protein contact map by ultra-deep learning model. PLoS Comput Biol, 13, e1005324. [CrossRef] [Google Scholar]
- Webb B., Sali A. Protein Structure Modeling with MODELLER, in: Kihara D. (ed.), Protein Structure Prediction. Methods in Molecular Biology (Methods and Protocols), vol 1137, Humana Press, New York, 2014. [Google Scholar]
- Weigt, M., White, R.A., Szurmant, H., Hoch, J.A., Hwa, T. (2009). Identification of direct residue contacts in protein-protein interaction by message passing. Proc Nat Acad Sci USA, 106, 67-72. [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.
