Literature DB >> 15016369

Allostery and coupled sequence variation in nuclear hormone receptors.

John Kuriyan1.   

Abstract

The analysis of correlated sequence variation in evolutionarily related proteins is beginning to provide useful information regarding allosteric coupling between different functional sites. Such an analysis has been carried out for the nuclear hormone receptors, and the conclusions tested by making mutations that switch the allosteric response to ligands of RXR heterodimers.

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Year:  2004        PMID： 15016369     DOI： 10.1016/s0092-8674(04)00125-4

Source DB:  PubMed          Journal:  Cell        ISSN： 0092-8674            Impact factor:   41.582


  8 in total

1.  Allosteric Dynamic Control of Binding.

Authors:  Fidan Sumbul; Saliha Ece Acuner-Ozbabacan; Turkan Haliloglu
Journal:  Biophys J       Date:  2015-08-31       Impact factor: 4.033

2.  iBIS2Analyzer: a web server for a phylogeny-driven coevolution analysis of protein families.

Authors:  Francesco Oteri; Edoardo Sarti; Francesca Nadalin; Alessandra Carbone
Journal:  Nucleic Acids Res       Date:  2022-06-07       Impact factor: 19.160

3.  Using affinity chromatography to engineer and characterize pH-dependent protein switches.

Authors:  Martin Sagermann; Richard R Chapleau; Elaine DeLorimier; Margarida Lei
Journal:  Protein Sci       Date:  2009-01       Impact factor: 6.725

4.  Residues crucial for maintaining short paths in network communication mediate signaling in proteins.

Authors:  Antonio del Sol; Hirotomo Fujihashi; Dolors Amoros; Ruth Nussinov
Journal:  Mol Syst Biol       Date:  2006-05-02       Impact factor: 11.429

5.  BIS2Analyzer: a server for co-evolution analysis of conserved protein families.

Authors:  Francesco Oteri; Francesca Nadalin; Raphaël Champeimont; Alessandra Carbone
Journal:  Nucleic Acids Res       Date:  2017-07-03       Impact factor: 16.971

6.  Protein fragments: functional and structural roles of their coevolution networks.

Authors:  Linda Dib; Alessandra Carbone
Journal:  PLoS One       Date:  2012-11-05       Impact factor: 3.240

7.  Coevolution analysis of Hepatitis C virus genome to identify the structural and functional dependency network of viral proteins.

Authors:  Raphaël Champeimont; Elodie Laine; Shuang-Wei Hu; Francois Penin; Alessandra Carbone
Journal:  Sci Rep       Date:  2016-05-20       Impact factor: 4.379

8.  AutoCoEv-A High-Throughput In Silico Pipeline for Predicting Inter-Protein Coevolution.

Authors:  Petar B Petrov; Luqman O Awoniyi; Vid Šuštar; M Özge Balci; Pieta K Mattila
Journal:  Int J Mol Sci       Date:  2022-03-20       Impact factor: 5.923
  8 in total

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