Structural basis of histidine kinase autophosphorylation deduced by integrating genomics, molecular dynamics, and mutagenesis

By A. E. Dago, Alexander Schug, Andrea Procaccini, J. Hoch, Martin Weigt, H. Szurmant. 2012

143 citations recorded by the source corpus.

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In Genetics

In Molecular Biology

Citations in the corpus

Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1 (2015, methodology): “In this paper we propose a variant of DCA which assigns to each mutant sequence a statistical score, which in a next step In technical terms, a mutational landscape is given as a genotype-to-phenotype mapping.”
Robust and accurate prediction of residue–residue interactions across protein interfaces using evolutionary information (2014, background): “…); the application of global statistical models to coevolution-based contact prediction across interfaces has been limited to the case of the histidine-kinase/response-regulator two component system ( Burger and van Nimwegen, 2008 ; Weigt et al., 2009 ; Schug et al., 2009 ; Dago et al., 2012 ).”
Coevolutionary signals across protein lineages help capture multiple protein conformations (2013, background): “Integrating the DCA-predicted contacts into coarse-grained physical models of proteins such as structure-based models (SBMs) (15 – 19) led to predictions on protein – protein interactions (20 – 22) as well as tools to aid the prediction of native structures (19, 23 – 25).”
Origins of coevolution between residues distant in protein 3D structures (2017, unknown): “There has been considerable recent success in using direct couplings to infer residue–residue contacts for protein structure prediction (6–9), protein–protein complex prediction (10–12), identification of specific interaction partners among two sets of paralogous proteins (13), resolution of ambigui”
Large-scale identification of coevolution signals across homo-oligomeric protein interfaces by direct coupling analysis (2017, background): “Such information has proven useful in the prediction of tertiary protein structures (10-13), conformational transitions (14-16), and similarly RNA structures (17, 18).”
Connecting the Sequence-Space of Bacterial Signaling Proteins to Phenotypes Using Coevolutionary Landscapes (2016, methodology): “…residue pairs have been used as docking constraints in a molecular dynamics simulation to predict the HK/RR signaling complex (Schug et al. 2009), the autophosphorylation structure of a HK (Dago et al. 2012), and the homodimeric form (transcription factor) of the RR (dos Santos et al. 2015).”
From Principal Component to Direct Coupling Analysis of Coevolution in Proteins: Low-Eigenvalue Modes are Needed for Structure Prediction (2012, unknown): “In [36] it was used to rationally design mutagenesis experiments to repair a non-functional hybrid protein, and thus to confirm the predicted structure.”
Emerging methods in protein co-evolution (2013, methodology): “Direct coupling analysis (DCA) 15–17, 38 and Alternatively, Burger and van Nimwegen’s 41 method uses a Bayesian network model that includes pair‑ wise conditional dependencies, and the regularized multinomial regression‑based correlated mutations (RMRCM) approach 42 takes into account the whole…”
Inter-residue, inter-protein and inter-family coevolution: bridging the scales (2017, methodology): “Predicted contacts have subsequently guided the prediction of hundreds of unknown protein structures [17-21].”
Simultaneous identification of specifically interacting paralogs and interprotein contacts by direct coupling analysis (2016, background): “contacts between bacterial signal transduction proteins, to help to assemble protein complexes (15, 16) and shed light on interaction specificity (17, 18).”
Predicting Functionally Informative Mutations in Escherichia coli BamA Using Evolutionary Covariance Analysis (2013, methodology): “DCA has been used successfully as a means of predicting protein structure, and it was recently used to identify interdomain contacts in the Bacillus subtilis sensor histidine kinase KinA for targeted mutagenesis (Dago et al. 2012; Szurmant and Hoch 2013).”
Toward rationally redesigning bacterial two-component signaling systems using coevolutionary information (2014, methodology): “Although other relevant methods for docking proteins exist (56–58), genomics-aided complex prediction has successfully been used to predict the HK/RR complex of TM0853/TM0468 within crystallographic accuracy of its experimentally determined structure (6) as well as to predict the active conformation”
Inverse statistical problems: from the inverse Ising problem to data science (2017, unknown): “bit correlations, which need not stem from proximity. This problem is addressed by an inverse approach aimed at nding the set of pairwise couplings that lead to the observed correlations or sequences [39,55,58,71,99,138,154,213,239]. Since each sequence position can be taken up by one of 20 amino ac”