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Uncovering Non-random Binary Patterns Within Sequences of Intrinsically Disordered Proteins.

Megan C Cohan1, Min Kyung Shinn1, Jared M Lalmansingh2

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Journal of Molecular Biology
|December 5, 2021
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Summary

We developed NARDINI, a computational method to identify non-random sequence patterns in intrinsically disordered proteins (IDPs). This approach uses z-scores to compare patterns against a null model, aiding in understanding sequence-ensemble relationships.

Keywords:
CIDERNARDINIbinary patternsintrinsically disordered proteins/regions

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Area of Science:

  • Proteomics
  • Computational Biology
  • Biophysics

Background:

  • Intrinsically disordered proteins (IDPs) exhibit sequence-ensemble relationships governed by residue patterns.
  • Existing methods for describing these patterns lack interoperability across different IDP compositions and lengths.

Purpose of the Study:

  • To introduce NARDINI (Non-random Arrangement of Residues in Disordered Regions Inferred using Numerical Intermixing), a computational method for discovering shared, non-random sequence patterns in IDPs.
  • To establish a framework for analyzing sequence-ensemble relationships that is adaptable to varying amino acid compositions and protein lengths.

Main Methods:

  • NARDINI generates an ensemble of scrambled sequences to create a composition-specific null model for sequence patterns.
  • Pattern-specific z-scores are computed to quantify deviations from the null model, identifying putative non-random patterns.
  • The method was applied to well-studied IDP systems and across homologs/orthologs.

Main Results:

  • NARDINI successfully identified non-random linear sequence patterns in three model IDP systems.
  • The z-scores derived from NARDINI proved effective in analyzing sequence patterns across homologous and orthologous IDPs.
  • Demonstrated the utility of NARDINI for studying sequence-ensemble relationships in diverse IDP contexts.

Conclusions:

  • NARDINI provides a robust computational tool for identifying non-random sequence patterns in IDPs.
  • The developed z-scores offer a versatile metric for theoretical and computational descriptions of sequence-ensemble relationships in IDPs.
  • NARDINI is expected to facilitate the design of novel IDPs with engineered sequence-function relationships.