Literature DB >> 30945212

Advances in Protein Super-Secondary Structure Prediction and Application to Protein Structure Prediction.

Elijah MacCarthy1, Derrick Perry1, Dukka B Kc2.   

Abstract

Due to the advancement in various sequencing technologies, the gap between the number of protein sequences and the number of experimental protein structures is ever increasing. Community-wide initiatives like CASP have resulted in considerable efforts in the development of computational methods to accurately model protein structures from sequences. Sequence-based prediction of super-secondary structure has direct application in protein structure prediction, and there have been significant efforts in the prediction of super-secondary structure in the last decade. In this chapter, we first introduce the protein structure prediction problem and highlight some of the important progress in the field of protein structure prediction. Next, we discuss recent methods for the prediction of super-secondary structures. Finally, we discuss applications of super-secondary structure prediction in structure prediction/analysis of proteins. We also discuss prediction of protein structures that are composed of simple super-secondary structure repeats and protein structures that are composed of complex super-secondary structure repeats. Finally, we also discuss the recent trends in the field.

Entities:  

Keywords:  Complex super-secondary structure; Free modeling; Protein structure prediction; Proteins with complex super-secondary structure repeats; Proteins with simple super-secondary structure repeats; Secondary structure prediction; Simple secondary structure; Template-based modeling

Mesh:

Substances:

Year:  2019        PMID: 30945212     DOI: 10.1007/978-1-4939-9161-7_2

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  2 in total

1.  RF-MaloSite and DL-Malosite: Methods based on random forest and deep learning to identify malonylation sites.

Authors:  Hussam Al-Barakati; Niraj Thapa; Saigo Hiroto; Kaushik Roy; Robert H Newman; Dukka Kc
Journal:  Comput Struct Biotechnol J       Date:  2020-03-04       Impact factor: 7.271

Review 2.  Current Approaches in Supersecondary Structures Investigation.

Authors:  Vladimir R Rudnev; Liudmila I Kulikova; Kirill S Nikolsky; Kristina A Malsagova; Arthur T Kopylov; Anna L Kaysheva
Journal:  Int J Mol Sci       Date:  2021-11-02       Impact factor: 5.923

  2 in total

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