Accurate disulfide-bonding network predictions improveab initiostructure prediction of cysteine-rich proteins | Zendy

Jing Yang | Zendy; Bao-Ji He | Zendy; Richard Jang | Zendy; Yang Zhang | Zendy; Hong-Bin Shen | Zendy

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Accurate disulfide-bonding network predictions improveab initiostructure prediction of cysteine-rich proteins

Author(s) -

Jing Yang,

Bao-Ji He,

Richard Jang,

Yang Zhang,

Hong-Bin Shen

Publication year - 2015

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/btv459

Subject(s) - benchmark (surveying) , cysteine , ab initio , disulfide bond , computer science , protein structure prediction , chemistry , computational biology , protein structure , bioinformatics , data mining , biochemistry , biology , geodesy , organic chemistry , enzyme , geography

Cysteine-rich proteins cover many important families in nature but there are currently no methods specifically designed for modeling the structure of these proteins. The accuracy of disulfide connectivity pattern prediction, particularly for the proteins of higher-order connections, e.g., >3 bonds, is too low to effectively assist structure assembly simulations.

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