Connecting the Sequence-Space of Bacterial Signaling Proteins to Phenotypes Using Coevolutionary Landscapes
暂无分享,去创建一个
F. Morcos | J. Onuchic | H. Levine | R. R. Cheng | O. Nordesjö | R. L. Hayes | H. Levine | S. Flores | Olle Nordesjö
[1] J. Bloom. Identification of positive selection in genes is greatly improved by using experimentally informed site-specific models , 2016, Biology Direct.
[2] Y. Benenson,et al. Synthetic biology of cell signaling , 2016, Natural Computing.
[3] F. Morcos,et al. Sequence co-evolutionary information is a natural partner to minimally-frustrated models of biomolecular dynamics , 2016, F1000Research.
[4] Claus O. Wilke,et al. Causes of evolutionary rate variation among protein sites , 2016, Nature Reviews Genetics.
[5] Saurav Mallik,et al. Predicting protein folding rate change upon point mutation using residue‐level coevolutionary information , 2016, Proteins.
[6] Mohit Raghunathan,et al. Constructing sequence‐dependent protein models using coevolutionary information , 2016, Protein science : a publication of the Protein Society.
[7] Andrea Pagnani,et al. Inter-Protein Sequence Co-Evolution Predicts Known Physical Interactions in Bacterial Ribosomes and the Trp Operon , 2015, PloS one.
[8] A. Tek,et al. MMB-GUI: a fast morphing method demonstrates a possible ribosomal tRNA translocation trajectory , 2015, Nucleic acids research.
[9] Peter G Wolynes,et al. Evolution, energy landscapes and the paradoxes of protein folding. , 2015, Biochimie.
[10] A. Valencia,et al. From residue coevolution to protein conformational ensembles and functional dynamics , 2015, Proceedings of the National Academy of Sciences.
[11] Thomas A. Hopf,et al. Quantification of the effect of mutations using a global probability model of natural sequence variation , 2015, 1510.04612.
[12] M. Weigt,et al. Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1 , 2015, bioRxiv.
[13] M. Laub,et al. Evolving New Protein-Protein Interaction Specificity through Promiscuous Intermediates , 2015, Cell.
[14] Ricardo N Dos Santos,et al. Dimeric interactions and complex formation using direct coevolutionary couplings , 2015, Scientific Reports.
[15] Daniel F. A. R. Dourado,et al. Structural and Functional Impact of Parkinson Disease‐Associated Mutations in the E3 Ubiquitin Ligase Parkin , 2015, Human mutation.
[16] G Tiana,et al. A many-body term improves the accuracy of effective potentials based on protein coevolutionary data. , 2015, The Journal of chemical physics.
[17] Simone Marsili,et al. Large-Scale Conformational Transitions and Dimerization Are Encoded in the Amino-Acid Sequences of Hsp70 Chaperones , 2015, PLoS Comput. Biol..
[18] Michael T. Laub,et al. Pervasive degeneracy and epistasis in a protein-protein interface , 2015, Science.
[19] Stephanie J. Spielman,et al. The relationship between dN/dS and scaled selection coefficients. , 2015, Molecular biology and evolution.
[20] H. Chan,et al. Biophysics of protein evolution and evolutionary protein biophysics , 2014, Journal of The Royal Society Interface.
[21] Samuel Flores,et al. Phosphorylation by PINK1 Releases the UBL Domain and Initializes the Conformational Opening of the E3 Ubiquitin Ligase Parkin , 2014, PLoS Comput. Biol..
[22] Jeffrey J. Tabor,et al. Refactoring and optimization of light-switchable Escherichia coli two-component systems. , 2014, ACS synthetic biology.
[23] Daniel F. A. R. Dourado,et al. A multiscale approach to predicting affinity changes in protein–protein interfaces , 2014, Proteins.
[24] Peter G Wolynes,et al. Coevolutionary information, protein folding landscapes, and the thermodynamics of natural selection , 2014, Proceedings of the National Academy of Sciences.
[25] Thierry Mora,et al. Capturing coevolutionary signals inrepeat proteins , 2014, BMC Bioinformatics.
[26] José N. Onuchic,et al. Toward rationally redesigning bacterial two-component signaling systems using coevolutionary information , 2014, Proceedings of the National Academy of Sciences.
[27] Pedro M. Alzari,et al. Segmental Helical Motions and Dynamical Asymmetry Modulate Histidine Kinase Autophosphorylation , 2014, PLoS biology.
[28] Peter G Wolynes,et al. Frustration in biomolecules , 2013, Quarterly Reviews of Biophysics.
[29] Terence Hwa,et al. Coevolutionary signals across protein lineages help capture multiple protein conformations , 2013, Proceedings of the National Academy of Sciences.
[30] Soon Ho Hong,et al. Engineered fumarate sensing Escherichia coli based on novel chimeric two-component system. , 2013, Journal of biotechnology.
[31] E. Birney,et al. Pfam: the protein families database , 2013, Nucleic Acids Res..
[32] Samuel Coulbourn Flores,et al. Fast fitting to low resolution density maps: elucidating large-scale motions of the ribosome , 2013, Nucleic acids research.
[33] K. Dill,et al. Principles of maximum entropy and maximum caliber in statistical physics , 2013 .
[34] Guido Tiana,et al. The network of stabilizing contacts in proteins studied by coevolutionary data. , 2013, The Journal of chemical physics.
[35] Michael T. Laub,et al. Determinants of specificity in two-component signal transduction. , 2013, Current opinion in microbiology.
[36] A. Valencia,et al. Emerging methods in protein co-evolution , 2013, Nature Reviews Genetics.
[37] Andrew L. Ferguson,et al. Translating HIV sequences into quantitative fitness landscapes predicts viral vulnerabilities for rational immunogen design. , 2013, Immunity.
[38] E. Aurell,et al. Improved contact prediction in proteins: using pseudolikelihoods to infer Potts models. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.
[39] Thomas A. Hopf,et al. Protein structure prediction from sequence variation , 2012, Nature Biotechnology.
[40] Adam P. Arkin,et al. Engineering robust control of two-component system phosphotransfer using modular scaffolds , 2012, Proceedings of the National Academy of Sciences.
[41] Michael T Laub,et al. Evolution of two-component signal transduction systems. , 2012, Annual review of microbiology.
[42] F. Morcos,et al. Genomics-aided structure prediction , 2012, Proceedings of the National Academy of Sciences.
[43] Martin Weigt,et al. Structural basis of histidine kinase autophosphorylation deduced by integrating genomics, molecular dynamics, and mutagenesis , 2012, Proceedings of the National Academy of Sciences.
[44] Richard A. Goldstein,et al. Estimating the Distribution of Selection Coefficients from Phylogenetic Data Using Sitewise Mutation-Selection Models , 2012, Genetics.
[45] C. Sander,et al. Direct-coupling analysis of residue coevolution captures native contacts across many protein families , 2011, Proceedings of the National Academy of Sciences.
[46] Russ B. Altman,et al. Fast Flexible Modeling of RNA Structure Using Internal Coordinates , 2011, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[47] Robert D. Finn,et al. HMMER web server: interactive sequence similarity searching , 2011, Nucleic Acids Res..
[48] B. Lunt,et al. Dissecting the Specificity of Protein-Protein Interaction in Bacterial Two-Component Signaling: Orphans and Crosstalks , 2011, PloS one.
[49] Robert D. Finn,et al. Representative Proteomes: A Stable, Scalable and Unbiased Proteome Set for Sequence Analysis and Functional Annotation , 2011, PloS one.
[50] Christopher A. Voigt,et al. Multichromatic control of gene expression in Escherichia coli. , 2011, Journal of molecular biology.
[51] Russ B. Altman,et al. Pacific Symposium on Biocomputing 15:216-227(2010) PREDICTING RNA STRUCTURE BY MULTIPLE TEMPLATE HOMOLOGY MODELING , 2022 .
[52] V. Rubio,et al. The mechanism of signal transduction by two-component systems. , 2010, Current opinion in structural biology.
[53] Jeffrey M. Skerker,et al. Systematic Dissection and Trajectory-Scanning Mutagenesis of the Molecular Interface That Ensures Specificity of Two-Component Signaling Pathways , 2010, PLoS genetics.
[54] Russ B Altman,et al. Turning limited experimental information into 3D models of RNA. , 2010, RNA.
[55] Hendrik Szurmant,et al. Interaction fidelity in two-component signaling. , 2010, Current opinion in microbiology.
[56] R. Bourret,et al. Two-component signal transduction. , 2010, Current opinion in microbiology.
[57] Terence Hwa,et al. High-resolution protein complexes from integrating genomic information with molecular simulation , 2009, Proceedings of the National Academy of Sciences.
[58] Alberto Marina,et al. Structural Insight into Partner Specificity and Phosphoryl Transfer in Two-Component Signal Transduction , 2009, Cell.
[59] V. Pande,et al. On the application of statistical physics to evolutionary biology. , 2009, Journal of theoretical biology.
[60] T. Hwa,et al. Identification of direct residue contacts in protein–protein interaction by message passing , 2009, Proceedings of the National Academy of Sciences.
[61] Michael T. Laub,et al. Rewiring the Specificity of Two-Component Signal Transduction Systems , 2008, Cell.
[62] E. van Nimwegen,et al. Accurate Prediction of Protein–protein Interactions from Sequence Alignments Using a Bayesian Method , 2022 .
[63] M. Laub,et al. Specificity in two-component signal transduction pathways. , 2007, Annual review of genetics.
[64] Michael T Laub,et al. Two-Component Signal Transduction Pathways Regulating Growth and Cell Cycle Progression in a Bacterium: A System-Level Analysis , 2005, PLoS biology.
[65] R. Utsumi,et al. Functional Characterization in Vitro of All Two-component Signal Transduction Systems from Escherichia coli* , 2005, Journal of Biological Chemistry.
[66] Wendell A. Lim,et al. Optimization of specificity in a cellular protein interaction network by negative selection , 2003, Nature.
[67] M. Inouye,et al. Cysteine-Scanning Analysis of the Dimerization Domain of EnvZ, an Osmosensing Histidine Kinase , 2003, Journal of bacteriology.
[68] Eugene I Shakhnovich,et al. Amino acids determining enzyme-substrate specificity in prokaryotic and eukaryotic protein kinases , 2003, Proceedings of the National Academy of Sciences of the United States of America.
[69] L. Serrano,et al. Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations. , 2002, Journal of molecular biology.
[70] J. Hoch,et al. Two-component and phosphorelay signal transduction. , 2000, Current opinion in microbiology.
[71] A. Halpern,et al. Evolutionary distances for protein-coding sequences: modeling site-specific residue frequencies. , 1998, Molecular biology and evolution.
[72] V S Pande,et al. Statistical mechanics of simple models of protein folding and design. , 1997, Biophysical journal.
[73] J. Hoch,et al. Molecular recognition in signal transduction: the interaction surfaces of the Spo0F response regulator with its cognate phosphorelay proteins revealed by alanine scanning mutagenesis. , 1997, Journal of molecular biology.
[74] J. Onuchic,et al. Funnels, pathways, and the energy landscape of protein folding: A synthesis , 1994, Proteins.
[75] C. Sander,et al. Correlated mutations and residue contacts in proteins , 1994, Proteins.
[76] C. Sander,et al. Can three-dimensional contacts in protein structures be predicted by analysis of correlated mutations? , 1994, Protein engineering.
[77] E. Neher. How frequent are correlated changes in families of protein sequences? , 1994, Proceedings of the National Academy of Sciences of the United States of America.
[78] J. Onuchic,et al. Protein folding funnels: a kinetic approach to the sequence-structure relationship. , 1992, Proceedings of the National Academy of Sciences of the United States of America.
[79] P. Wolynes,et al. Spin glasses and the statistical mechanics of protein folding. , 1987, Proceedings of the National Academy of Sciences of the United States of America.
[80] Vijay S. Pande,et al. Heteropolymer freezing and design: Towards physical models of protein folding , 2000 .
[81] J. Onuchic,et al. Theory of protein folding: the energy landscape perspective. , 1997, Annual review of physical chemistry.
[82] C. Sander,et al. Correlated Mutations and Residue Contacts , 1994 .