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

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

doi:10.1093/bioinformatics/btaa781

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

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

Chemical and Structural Biology (TMED)

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

Motivation: 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.

Original language	English (US)
Pages (from-to)	1176-1177
Number of pages	2
Journal	Bioinformatics
Volume	37
Issue number	8
DOIs	https://doi.org/10.1093/bioinformatics/btaa781
State	Published - Apr 15 2021

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AU - Shao, Hongzhao

AU - Boulton, Stephen

AU - Olivieri, Cristina

AU - Mohamed, Hebatallah

AU - Akimoto, Madoka

AU - Subrahmanian, Manu Veliparambil

AU - Veglia, Gianluigi

AU - Markley, John L.

AU - Melacini, Giuseppe

AU - Lee, Woonghee

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

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