CHESPA/CHESCA-SPARKY: automated NMR data analysis plugins for SPARKY to map protein allostery | Zendy

Hongzhao Shao | Zendy; Stephen Boulton | Zendy; Cristina Olivieri | Zendy; Hebatallah Mohamed | Zendy; Madoka Akimoto | Zendy; Manu Veliparambil Subrahmanian | Zendy; Gianluigi Veglia | Zendy; John L. Markley | Zendy; Giuseppe Melacini | Zendy; Woonghee Lee | Zendy

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CHESPA/CHESCA-SPARKY: automated NMR data analysis plugins for SPARKY to map protein allostery

Author(s) -

Hongzhao Shao,

Stephen Boulton,

Cristina Olivieri,

Hebatallah Mohamed,

Madoka Akimoto,

Manu Veliparambil Subrahmanian,

Gianluigi Veglia,

John L. Markley,

Giuseppe Melacini,

Woonghee Lee

Publication year - 2020

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/btaa781

Subject(s) - plug in , computer science , visualization , allosteric regulation , software , download , data mining , nuclear magnetic resonance , world wide web , programming language , physics , enzyme

Correlated Nuclear Magnetic Resonance (NMR) chemical shift changes identified through the CHEmical Shift Projection Analysis (CHESPA) and CHEmical Shift Covariance Analysis (CHESCA) reveal pathways of allosteric transitions in biological macromolecules. To address the need for an automated platform that implements CHESPA and CHESCA and integrates them with other NMR analysis software packages, we introduce here integrated plugins for NMRFAM-SPARKY that implement the seamless detection and visualization of allosteric networks.

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