Literature DB >> 30097830

Nonfunctional Missense Mutants in Two Well Characterized Cytosolic Enzymes Reveal Important Information About Protein Structure and Function.

Ashley E Cole1, Fatmah M Hani1, Brian W Allen2, Paul C Kline3, Elliot Altman4.   

Abstract

The isolation and characterization of 42 unique nonfunctional missense mutants in the bacterial cytosolic β-galactosidase and catechol 2,3-dioxygenase enzymes allowed us to examine some of the basic general trends regarding protein structure and function. A total of 6 out of the 42, or 14.29% of the missense mutants were in α-helices, 17 out of the 42, or 40.48%, of the missense mutants were in β-sheets and 19 out of the 42, or 45.24% of the missense mutants were in unstructured coil, turn or loop regions. While α-helices and β-sheets are undeniably important in protein structure, our results clearly indicate that the unstructured regions are just as important. A total of 21 out of the 42, or 50.00% of the missense mutants caused either amino acids located on the surface of the protein to shift from hydrophilic to hydrophobic or buried amino acids to shift from hydrophobic to hydrophilic and resulted in drastic changes in hydropathy that would not be preferable. There was generally good consensus amongst the widely used algorithms, Chou-Fasman, GOR, Qian-Sejnowski, JPred, PSIPRED, Porter and SPIDER, in their ability to predict the presence of the secondary structures that were affected by the missense mutants and most of the algorithms predicted that the majority of the 42 inactive missense mutants would impact the α-helical and β-sheet secondary structures or the unstructured coil, turn or loop regions that they altered.

Entities:  

Keywords:  Coils; Hydropathy; Protein secondary structure; Unstructured regions; α-Helices; β-Sheets

Mesh:

Substances:

Year:  2018        PMID: 30097830     DOI: 10.1007/s10930-018-9786-6

Source DB:  PubMed          Journal:  Protein J        ISSN: 1572-3887            Impact factor:   2.371


  49 in total

1.  Protein secondary structure prediction based on position-specific scoring matrices.

Authors:  D T Jones
Journal:  J Mol Biol       Date:  1999-09-17       Impact factor: 5.469

2.  Porter: a new, accurate server for protein secondary structure prediction.

Authors:  Gianluca Pollastri; Aoife McLysaght
Journal:  Bioinformatics       Date:  2004-12-07       Impact factor: 6.937

3.  Structural biology. Versatility from protein disorder.

Authors:  M Madan Babu; Richard W Kriwacki; Rohit V Pappu
Journal:  Science       Date:  2012-09-21       Impact factor: 47.728

4.  Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network.

Authors:  James Lyons; Abdollah Dehzangi; Rhys Heffernan; Alok Sharma; Kuldip Paliwal; Abdul Sattar; Yaoqi Zhou; Yuedong Yang
Journal:  J Comput Chem       Date:  2014-09-12       Impact factor: 3.376

5.  The characterization of amino acid sequences in proteins by statistical methods.

Authors:  J M Zimmerman; N Eliezer; R Simha
Journal:  J Theor Biol       Date:  1968-11       Impact factor: 2.691

6.  A thermodynamic scale for the beta-sheet forming tendencies of the amino acids.

Authors:  C K Smith; J M Withka; L Regan
Journal:  Biochemistry       Date:  1994-05-10       Impact factor: 3.162

7.  A simple method for displaying the hydropathic character of a protein.

Authors:  J Kyte; R F Doolittle
Journal:  J Mol Biol       Date:  1982-05-05       Impact factor: 5.469

8.  Analysis of gene control signals by DNA fusion and cloning in Escherichia coli.

Authors:  M J Casadaban; S N Cohen
Journal:  J Mol Biol       Date:  1980-04       Impact factor: 5.469

9.  An archetypical extradiol-cleaving catecholic dioxygenase: the crystal structure of catechol 2,3-dioxygenase (metapyrocatechase) from Ppseudomonas putida mt-2.

Authors:  A Kita; S Kita; I Fujisawa; K Inaka; T Ishida; K Horiike; M Nozaki; K Miki
Journal:  Structure       Date:  1999-01-15       Impact factor: 5.006

10.  Alanine-scanning mutagenesis of the beta-sheet region of phage T4 lysozyme suggests that tertiary context has a dominant effect on beta-sheet formation.

Authors:  Molly M He; Zachary A Wood; Walter A Baase; Hong Xiao; Brian W Matthews
Journal:  Protein Sci       Date:  2004-08-31       Impact factor: 6.725

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