scholarly journals Secondary-structure prediction from the sequence of Drosophila melanogaster (fruitfly) alcohol dehydrogenase

1980 ◽  
Vol 187 (3) ◽  
pp. 884-886 ◽  
Author(s):  
D R Thatcher ◽  
L Sawyer
Keyword(s):  
Drosophila Melanogaster ◽  
Secondary Structure ◽  
Alcohol Dehydrogenase ◽  
Structure Prediction ◽  
Secondary Structure Prediction

scholarly journals The complete amino acid sequence of three alcohol dehydrogenase alleloenzymes (AdhN-11, AdhS and AdhUF) from the fruitfly Drosophila melanogaster

1980 ◽  
Vol 187 (3) ◽  
pp. 875-883 ◽  
Author(s):  
D R Thatcher
Keyword(s):  
Drosophila Melanogaster ◽  
Amino Acid ◽  
Amino Acid Sequence ◽  
Alcohol Dehydrogenase ◽  
Aspartic Acid ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
British Library ◽  
Horse Liver ◽  
And Staphylococcus Aureus

The sequence of three alcohol dehydrogenase alleloenzymes from the fruitfly Drosophila melanogaster has been determined by the sequencing of peptides produced by trypsin, chymotrypsin, thermolysin, pepsin and Staphylococcus aureus-V8-proteinase digestion. The amino acid sequence shows no obvious homology with the published sequences of the horse liver and yeast enzymes, and secondary structure prediction suggests that the nucleotide-binding domain is located in the N-terminal half of the molecule. The amino acid substitutions between AdhN-11 (a point mutation of AdhF), AdhS and AdhUF alleloenzymes were identified. AdhN-11 alcohol dehydrogenase differed from the other two by a glycine-14-(AdhS and AdhUF)-to-aspartic acid substitution, the AdhS enzyme from AdhN-11 and AdhUF enzymes by a threonine-192-(AdhN-11 and AdhUF)-to-lysine (AdhS) substitution and the AdhUF enzyme was found to differ by an alanine-45-(AdhS and AdhN-11)-to-aspartic acid (AdhUF) charge substitution and a ‘silent’ asparagine-8-(AdhS and AdhN-11)-to-alanine (AdhUF) substitution. Detailed sequence evidence has been deposited as Supplementary Publication SUP 50107 (36 pages) at the British Library Lending Division, Boston Spa, Wetherby, West Yorkshire LS23 7BQ, U.K., from whom copies can be obtained on the terms indicated in Biochem. J. (1978) 169, 5.

A Systematic Review on Popularity, Application and Characteristics of Protein Secondary Structure Prediction Tools

2019 ◽  
Vol 16 (2) ◽  
pp. 159-172 ◽  
Author(s):  
Elaheh Kashani-Amin ◽  
Ozra Tabatabaei-Malazy ◽  
Amirhossein Sakhteman ◽  
Bagher Larijani ◽  
Azadeh Ebrahim-Habibi
Keyword(s):  
Systematic Review ◽  
Secondary Structure ◽  
Structure Prediction ◽  
Web Of Science ◽  
Secondary Structure Prediction ◽  
Structural Information ◽  
Protein Secondary Structure ◽  
Structural Features ◽  
Prediction Tools ◽  
Insight Into

Background: Prediction of proteins’ secondary structure is one of the major steps in the generation of homology models. These models provide structural information which is used to design suitable ligands for potential medicinal targets. However, selecting a proper tool between multiple Secondary Structure Prediction (SSP) options is challenging. The current study is an insight into currently favored methods and tools, within various contexts. Objective: A systematic review was performed for a comprehensive access to recent (2013-2016) studies which used or recommended protein SSP tools. Methods: Three databases, Web of Science, PubMed and Scopus were systematically searched and 99 out of the 209 studies were finally found eligible to extract data. Results: Four categories of applications for 59 retrieved SSP tools were: (I) prediction of structural features of a given sequence, (II) evaluation of a method, (III) providing input for a new SSP method and (IV) integrating an SSP tool as a component for a program. PSIPRED was found to be the most popular tool in all four categories. JPred and tools utilizing PHD (Profile network from HeiDelberg) method occupied second and third places of popularity in categories I and II. JPred was only found in the two first categories, while PHD was present in three fields. Conclusion: This study provides a comprehensive insight into the recent usage of SSP tools which could be helpful for selecting a proper tool.

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