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

Kashani-Amin, Elaheh; Tabatabaei‐Malazy, Ozra; Sakhteman, Amirhossein; Larijani, Bagher; Ebrahim‐Habibi, Azadeh

doi:10.2174/1570163815666180227162157

Cited by 12 publications

(8 citation statements)

References 150 publications

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“…The OsTHIC gene primary protein sequence was subjected to secondary structure prediction analysis. The secondary structure was predicted using NPS-GOR4 tool by the information theory algorithm [13,14].…”

Section: Prediction Of Osthic Gene Secondary Structurementioning

confidence: 99%

Prediction and Validation of 3-Dimensional Structure of Rice OsTHIC Abiotic Stress Responsive Gene

et al. 2022

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Rice is an important cereal crop believed to have been cultivated for hundred years. The ancestry and evolution of this plant and its diverse cultivars remain contentious. Thus, determining the cultivar's molecular mechanism of abiotic stress-responsive genes using a bioinformatics system continues to be an area to investigate. For better knowledge of the mechanisms of the abiotic stress-responsive gene from rice, a novel stress-related gene named OsTHIC was selected for this study. The OsTHIC gene accessions were collected from NCBI, then predict its secondary structure. I-TASSER server was used to predict the 3-dimensional [3D] model of the gene protein and validated using ERRAT and Ramachandran plot. The OsTHIC gene appeared to be highly conserved and structurally functional. The secondary structure of the OsTHIC indicated a high percentage of a random coil [47.35%], followed by an alpha helix [45.05%], then an extended strand [10.61%]. The prediction using I-TASSER modeller produced structures based on the protein sequence. The protein 3D model showed different model qualities using the two-refinement software which ERRAT Plot model refinement having the best score at 97.266%.

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Section: Prediction Of Osthic Gene Secondary Structurementioning

confidence: 99%

Prediction and Validation of 3-Dimensional Structure of Rice OsTHIC Abiotic Stress Responsive Gene

et al. 2022

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“…The huge amount of protein sequences that lack the residue-level annotations has motivated the development of hundreds of computational methods that predict these annotations from the sequences. For instance, there are over 60 predictors of the secondary structure [5] , [6] , [7] , over 100 predictors of the intrinsic disorder [8] , [9] , [10] , [11] , [12] , and close to 40 predictors of the residues that bind nucleic acids [13] , [14] , [15] . Some of these methods are heavily used, which can be indirectly measured by their citations.…”

Section: Introductionmentioning

confidence: 99%

“…Availability of the many sequence-based predictors of the residue-level annotations has spurred numerous studies that survey and compare these tools [1] , [2] , [5] , [6] , [7] , [8] , [9] , [10] , [11] , [13] , [14] , [15] , [29] , [30] , [31] , [32] , [33] , [34] , [35] , [36] , [37] , [38] , [39] , [40] , [41] , [42] , [43] , [44] , [45] , [46] . A large portion of these studies focuses on the empirical comparative assessment of their predictive performance.…”

Section: Introductionmentioning

confidence: 99%

Complementarity of the residue-level protein function and structure predictions in human proteins

Biró

Zhao

Kurgan

2022

Computational and Structural Biotechnology Journal

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“…Hundreds of these predictors have been developed over the last few decades ( 5–24 ). For instance, there are over 60 tools for predicting secondary structure ( 10 , 22 , 23 ), over 70 predictors for intrinsic disorder ( 14 , 16 , 20 , 21 ), and close to 40 predictors of AAs-nucleic acids interactions ( 24 ). Recent empirical assessments demonstrate that many of these tools provide accurate predictions ( 11 , 25–31 ).…”

Section: Introductionmentioning

confidence: 99%

DescribePROT: database of amino acid-level protein structure and function predictions

Zhao

Katuwawala

Oldfield

et al. 2020

Nucleic Acids Research

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We present DescribePROT, the database of predicted amino acid-level descriptors of structure and function of proteins. DescribePROT delivers a comprehensive collection of 13 complementary descriptors predicted using 10 popular and accurate algorithms for 83 complete proteomes that cover key model organisms. The current version includes 7.8 billion predictions for close to 600 million amino acids in 1.4 million proteins. The descriptors encompass sequence conservation, position specific scoring matrix, secondary structure, solvent accessibility, intrinsic disorder, disordered linkers, signal peptides, MoRFs and interactions with proteins, DNA and RNAs. Users can search DescribePROT by the amino acid sequence and the UniProt accession number and entry name. The pre-computed results are made available instantaneously. The predictions can be accesses via an interactive graphical interface that allows simultaneous analysis of multiple descriptors and can be also downloaded in structured formats at the protein, proteome and whole database scale. The putative annotations included by DescriPROT are useful for a broad range of studies, including: investigations of protein function, applied projects focusing on therapeutics and diseases, and in the development of predictors for other protein sequence descriptors. Future releases will expand the coverage of DescribePROT. DescribePROT can be accessed at http://biomine.cs.vcu.edu/servers/DESCRIBEPROT/.

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

Abstract: This study provides a comprehensive insight about the recent usage of SSP tools which could be helpful for selecting a proper tool's choice.

Cited by 12 publications

References 150 publications

Prediction and Validation of 3-Dimensional Structure of Rice OsTHIC Abiotic Stress Responsive Gene

Prediction and Validation of 3-Dimensional Structure of Rice OsTHIC Abiotic Stress Responsive Gene

Complementarity of the residue-level protein function and structure predictions in human proteins

DescribePROT: database of amino acid-level protein structure and function predictions

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