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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
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Analysis and design of disordered polypeptides with optimized sequence patterning properties.

Arjun Singh1, Ali Ukperaj1, Gregory L Dignon1

  • 1Department of Chemical and Biochemical Engineering, Rutgers University, Piscataway, NJ, United States.

Biorxiv : the Preprint Server for Biology
|February 27, 2026
PubMed
Summary
This summary is machine-generated.

We developed new methods to compare and design intrinsically disordered proteins (IDPs). These tools enable prediction and control of IDP phase separation for biomedical applications.

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Area of Science:

  • Biophysics
  • Computational Biology
  • Protein Science

Background:

  • Intrinsically disordered proteins (IDPs) lack stable structures and their conformational ensemble dictates function.
  • IDP behavior, including phase separation, is governed by amino acid composition and sequence patterning.
  • Existing metrics for sequence patterning are limited, especially for sequences of varying lengths and compositions.

Purpose of the Study:

  • To develop a normalization scheme for sequence patterning metrics (SCD, SHD) applicable to diverse IDP sequences.
  • To create a computational framework for designing novel IDPs with specific patterning features and tunable phase behavior.
  • To enable rapid prediction of IDP behavior and facilitate rational design for various applications.

Main Methods:

  • Introduced a shuffle-based normalization scheme for sequence charge decoration (SCD) and sequence hydropathy decoration (SHD).
  • Developed a Monte Carlo-based sequence design algorithm incorporating SCD, SHD, sequence aromatic decoration (SAD), compositional RMSD, and a ΔG predictor.
  • Validated the design approach using coarse-grained molecular dynamics (MD) simulations.

Main Results:

  • The normalization scheme allows effective comparison of sequence patterning across dissimilar IDP sequences.
  • Designed IDP sequences demonstrated tunable phase separation behavior in MD simulations.
  • The developed computational framework successfully generated novel IDPs with desired patterning properties.

Conclusions:

  • The novel normalization and design framework enables rational design of IDPs with predictable phase behavior.
  • This approach facilitates the creation of IDPs for biomedical and biotechnology applications.
  • The study provides a powerful tool for basic biophysical research on IDPs.