Literature DB >> 33573110

ELIHKSIR Web Server: Evolutionary Links Inferred for Histidine Kinase Sensors Interacting with Response Regulators.

Claude Sinner1, Cheyenne Ziegler1, Yun Ho Jung1, Xianli Jiang1, Faruck Morcos1,2,3.   

Abstract

Two-component systems (TCS) are signaling machinery that consist of a histidine kinases (HK) and response regulator (RR). When an environmental change is detected, the HK phosphorylates its cognate response regulator (RR). While cognate interactions were considered orthogonal, experimental evidence shows the prevalence of crosstalk interactions between non-cognate HK-RR pairs. Currently, crosstalk interactions have been demonstrated for TCS proteins in a limited number of organisms. By providing specificity predictions across entire TCS networks for a large variety of organisms, the ELIHKSIR web server assists users in identifying interactions for TCS proteins and their mutants. To generate specificity scores, a global probabilistic model was used to identify interfacial couplings and local fields from sequence information. These couplings and local fields were then used to construct Hamiltonian scores for positions with encoded specificity, resulting in the specificity score. These methods were applied to 6676 organisms available on the ELIHKSIR web server. Due to the ability to mutate proteins and display the resulting network changes, there are nearly endless combinations of TCS networks to analyze using ELIHKSIR. The functionality of ELIHKSIR allows users to perform a variety of TCS network analyses and visualizations to support TCS research efforts.

Entities:  

Keywords:  bacterial signaling; fitness landscape; interaction specificity; mutational phenotypes; phosphorylation; statistical inference

Year:  2021        PMID: 33573110      PMCID: PMC7911359          DOI: 10.3390/e23020170

Source DB:  PubMed          Journal:  Entropy (Basel)        ISSN: 1099-4300            Impact factor:   2.524


  25 in total

1.  Functional characterization in vitro of all two-component signal transduction systems from Escherichia coli.

Authors:  Kaneyoshi Yamamoto; Kiyo Hirao; Taku Oshima; Hirofumi Aiba; Ryutaro Utsumi; Akira Ishihama
Journal:  J Biol Chem       Date:  2004-11-02       Impact factor: 5.157

Review 2.  Profile hidden Markov models.

Authors:  S R Eddy
Journal:  Bioinformatics       Date:  1998       Impact factor: 6.937

3.  The two-component signalling networks of Mycobacterium tuberculosis display extensive cross-talk in vitro.

Authors:  Ruchi Agrawal; Akancha Pandey; Mayooreshwar P Rajankar; Narendra M Dixit; Deepak K Saini
Journal:  Biochem J       Date:  2015-05-01       Impact factor: 3.857

4.  Toward rationally redesigning bacterial two-component signaling systems using coevolutionary information.

Authors:  Ryan R Cheng; Faruck Morcos; Herbert Levine; José N Onuchic
Journal:  Proc Natl Acad Sci U S A       Date:  2014-01-21       Impact factor: 11.205

Review 5.  Evolution of two-component signal transduction systems.

Authors:  Emily J Capra; Michael T Laub
Journal:  Annu Rev Microbiol       Date:  2012-06-28       Impact factor: 15.500

Review 6.  Interaction fidelity in two-component signaling.

Authors:  Hendrik Szurmant; James A Hoch
Journal:  Curr Opin Microbiol       Date:  2010-02-03       Impact factor: 7.934

Review 7.  Inter-residue, inter-protein and inter-family coevolution: bridging the scales.

Authors:  Hendrik Szurmant; Martin Weigt
Journal:  Curr Opin Struct Biol       Date:  2017-11-05       Impact factor: 6.809

8.  A Combined Computational and Genetic Approach Uncovers Network Interactions of the Cyanobacterial Circadian Clock.

Authors:  Joseph S Boyd; Ryan R Cheng; Mark L Paddock; Cigdem Sancar; Faruck Morcos; Susan S Golden
Journal:  J Bacteriol       Date:  2016-08-25       Impact factor: 3.490

9.  Designing bacterial signaling interactions with coevolutionary landscapes.

Authors:  Ryan R Cheng; Ellinor Haglund; Nicholas S Tiee; Faruck Morcos; Herbert Levine; Joseph A Adams; Patricia A Jennings; José N Onuchic
Journal:  PLoS One       Date:  2018-08-20       Impact factor: 3.240

10.  Connecting the Sequence-Space of Bacterial Signaling Proteins to Phenotypes Using Coevolutionary Landscapes.

Authors:  R R Cheng; O Nordesjö; R L Hayes; H Levine; S C Flores; J N Onuchic; F Morcos
Journal:  Mol Biol Evol       Date:  2016-09-07       Impact factor: 16.240

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