Analysis and prediction of protein folding energy changes upon mutation by element specific persistent homology | Zendy

Zixuan Cang | Zendy; Guo-Wei Wei | Zendy

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Analysis and prediction of protein folding energy changes upon mutation by element specific persistent homology

Author(s) -

Zixuan Cang,

Guo-Wei Wei

Publication year - 2017

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btx460

Subject(s) - mutation , homology modeling , pearson product moment correlation coefficient , stability (learning theory) , mutation rate , computational biology , correlation coefficient , computer science , correlation , persistent homology , mutagenesis , protein folding , folding (dsp implementation) , mathematics , protein design , protein structure , algorithm , biology , genetics , machine learning , statistics , gene , biochemistry , engineering , geometry , enzyme , electrical engineering

Site directed mutagenesis is widely used to understand the structure and function of biomolecules. Computational prediction of mutation impacts on protein stability offers a fast, economical and potentially accurate alternative to laboratory mutagenesis. Most existing methods rely on geometric descriptions, this work introduces a topology based approach to provide an entirely new representation of mutation induced protein stability changes that could not be obtained from conventional techniques.

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