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A peptide bond covalently attaches amino acids through a dehydration reaction. One amino acid's carboxyl group and another amino acid's amino group combine, releasing a water molecule. The resulting bond is the peptide bond. The products that such linkages form are peptides. As more amino acids join this growing chain, the resulting chain is a polypeptide. Each polypeptide has a free amino group at one end. This end has the N-terminal, or the amino-terminal, and the other end has a free...
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Proteins can form homomeric complexes with another unit of the same protein or heteromeric complexes with different types.  Most protein complexes self-assemble spontaneously via ordered pathways, while some proteins need assembly factors that guide their proper assembly. Despite the crowded intracellular environment, proteins usually interact with their correct partners and form functional complexes.
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Protein glycosylation starts in the ER lumen and continues in the Golgi apparatus. Glycosyltransferases catalyze the addition of sugar molecules or glycosylation of proteins. Usually, these enzymes add sugars to the hydroxyl groups of selected serine or threonine residues to form O-linked glycans or the amino groups of asparagine residues to form N-linked glycans. Different positions on the same polypeptide chain can contain differently linked glycans.
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Top-down Multiscale Approach To Simulate Peptide Self-Assembly from Monomers.

Xiaochuan Zhao1, Chenyi Liao1, Yong-Tao Ma1

  • 1Department of Chemistry , The University of Vermont , Burlington , Vermont 05405 , United States.

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|January 25, 2019
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Summary

This study introduces a multiresolution modeling approach, integrating coarse-grained (CG), mixed-resolution, and all-atom (AA) simulations for peptide assembly. This method accurately predicts peptide assembly, oligomer distribution, and secondary structures, validated with amyloid peptides.

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Area of Science:

  • Computational Chemistry
  • Biophysics
  • Molecular Modeling

Background:

  • Atomistic simulations face limitations in modeling peptide assembly over large time and length scales.
  • Understanding peptide self-assembly is crucial for various biological processes and disease mechanisms.

Purpose of the Study:

  • To develop and validate a novel multiresolution modeling approach for simulating peptide assembly.
  • To provide practical guidelines for large-scale peptide self-assembly simulations.

Main Methods:

  • Integration of coarse-grained (CG), mixed-resolution, and all-atom (AA) modeling within a single simulation framework.
  • Development of automated tools for model transformations and oligomer formation monitoring.
  • Theoretical estimation of optimal simulation lengths for each modeling resolution.

Main Results:

  • The multiresolution approach accurately predicted the assembly level, oligomer distribution, and secondary structures of melittin.
  • Simulations showed good agreement with experimental data and previous all-atom simulations.
  • Successful validation with amyloid peptides (β-amyloid 16-22, GNNQQNY, α-synuclein fibril 35-55) demonstrated the approach's versatility.

Conclusions:

  • The integrated multiresolution modeling strategy effectively overcomes the limitations of atomistic simulations for peptide assembly.
  • This approach offers a synergistic advantage by combining different resolutions for enhanced accuracy and efficiency.
  • The study provides a robust framework and practical guidelines for future large-scale peptide self-assembly simulations.