Cited by 8Chemical Synthesis and AnalysisProtein Structure and DynamicsSupramolecular Self-Assembly in Materials

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A high-throughput workflow to analyze sequence-conformation relationships and explore hydrophobic patterning in disordered peptoids

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Abstract

Understanding how a macromolecule's primary sequence governs its conformational landscape is crucial for elucidating its function, yet these design principles are still emerging for macromolecules with intrinsic disorder. Herein, we introduce a high-throughput workflow that implements a practical colorimetric conformational assay, introduces a semi-automated sequencing protocol using MALDI-MS/MS, and develops a generalizable sequence-structure algorithm. Using a model system of 20mer peptidomimetics containing polar glycine and hydrophobic N-butylglycine residues, we identified nine classifications of conformational disorder and isolated 122 unique sequences across varied compositions and conformations. Conformational distributions of three compositionally identical library sequences were corroborated through atomistic simulations and ion mobility spectrometry coupled with liquid chromatography. A data-driven strategy was developed using existing sequence variables and data-derived 'motifs' to inform a machine learning algorithm towards conformation prediction. This multifaceted approach enhances our understanding of sequence-conformation relationships and offers a powerful tool for accelerating the discovery of materials with conformational control.

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Metadata

Authors
Day, E. C., Chittari, S. S., Cunha, K. C., Zhao, R. J., Dodds, J. N., Davis, D. C., Baker, E. S., Berlow, R. B., Shea, J.-E., Kulkarni, R. U., & Knight, A. S.
Affiliations
  • University of North Carolina at Chapel Hill (US)
  • University of California, Santa Barbara (US)
  • Insilico Medicine (United States) (US)
Corresponding author
Knight, Abigail S.
Venue
Chem
Publisher
Elsevier BV
Published
2024-11
Volume
10
Issue
11
Pages
3444-3458
ISSN
2451-9294 (ISSN-L)
OpenAlex
W4402295723
Cited by
8
References
2
Citations by year
2026: 5 · 2025: 2 · 2024: 1
FWCI
1.09
Type
journal article
Language
en
Open access
Locations
  • Chem (publishedVersion)
  • ChemRxiv (acceptedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
Funders
  • American Society for Engineering Education National Defense Science and Engineering Graduate Fellowship (DGE-2040435)
  • National Institute of General Medical Sciences (RM1 GM145416)
  • National Science Foundation (MCB-1716956, CHE-1828183, ACI-1548562, CNS-1725797, MCA05S027)
  • National Cancer Institute (P30CA016086)
  • NICHD (P50 HD103573)
  • University of North Carolina (SCR_019060)
  • Basic Energy Sciences (DE-SC0021295)
  • National Institute of Environmental Health Sciences (P42 ES027704)
  • U.S. Department of Energy
  • Office of Science
  • School of Medicine, University of North Carolina at Chapel Hill
  • Department of Biochemistry and Biophysics, College of Science, Oregon State University
  • National Institutes of Health
  • NINDS (P30 NS045892)
  • Materials Research Science and Engineering Center, Harvard University (NSF DMR\u20132308708)
  • Air Force Office of Scientific Research (FA9550-20-1-0172)
  • US Environmental Protection Agency (STAR RD 84003201)
Topics
  • Physical Sciences › Chemistry › Organic Chemistry › Chemical Synthesis and Analysis
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Physical Sciences › Materials Science › Biomaterials › Supramolecular Self-Assembly in Materials
Keywords
peptoids, ion mobility spectrometry, peptidomimetics

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