Information theoretic measures for quantifying sequence–ensemble relationships of intrinsically disordered proteins. Issue 4 (3rd August 2019)

• Record Type: Journal Article
• Authors: Cohan, Megan C; Ruff, Kiersten M; Pappu, Rohit V
• Editors: Other, A N
• Is Part Of: Protein engineering, design & selection. Volume 32:Issue 4(2019)
• Page Start: 191
• Page End: 202
• Publication Date: 2019-08-03
• Subjects: computations -- ensemble entropy matrix -- intrinsically disordered proteins -- protein design -- sequence-ensemble relationships; Protein engineering -- Periodicals; 660.63
• DOI: 10.1093/protein/gzz014
• Languages: English
• ISSNs: 1741-0126

Abstract

Abstract: Intrinsically disordered proteins (IDPs) contribute to a multitude of functions. De novo design of IDPs should open the door to modulating functions and phenotypes controlled by these systems. Recent design efforts have focused on compositional biases and specific sequence patterns as the design features. Analysis of the impact of these designs on sequence-function relationships indicates that individual sequence/compositional parameters are insufficient for describing sequence-function relationships in IDPs. To remedy this problem, we have developed information theoretic measures for sequence–ensemble relationships (SERs) of IDPs. These measures rely on prior availability of statistically robust conformational ensembles derived from all atom simulations. We show that the measures we have developed are useful for comparing sequence-ensemble relationships even when sequence is poorly conserved. Based on our results, we propose that de novo designs of IDPs, guided by knowledge of their SERs, should provide improved insights into their sequence–ensemble–function relationships.