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From Sequence Definition to Structure‐Property Relationships in Discrete Synthetic Macromolecules: Insights from Molecular Modeling
Author(s) -
Dellemme David,
Kardas Sinan,
Tonneaux Corentin,
Lernould Julien,
Fossépré Mathieu,
Surin Mathieu
Publication year - 2025
Publication title -
angewandte chemie international edition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.831
H-Index - 550
eISSN - 1521-3773
pISSN - 1433-7851
DOI - 10.1002/anie.202420179
Subject(s) - sequence (biology) , macromolecule , computer science , property (philosophy) , order (exchange) , biological system , computational biology , biochemical engineering , algorithm , chemistry , biology , engineering , philosophy , biochemistry , epistemology , finance , economics
Abstract Inspired by the exquisite properties emerging from the sequence order in nucleic acids and proteins, researchers are increasingly considering synthetic sequence‐defined macromolecules (SDMs) to reach precise functions, e.g. for catalysis, data storage, energy, and health. Although researchers develop iterative techniques permitting the synthesis of perfectly defined sequences, there is still an important gap to achieve the desired properties leading to their utilization as materials. This arises from the fact that the effect of the sequence order on the 3D structure is unknown for most current synthetic SDMs. Although the Protein Data Bank gathers hundreds of thousands of elucidated 3D structures of proteins, and many more computed (using, e.g., AlphaFold), extended information on sequence‐structure relationships does not exist yet for synthetic SDMs. To tackle this problem for relatively flexible synthetic macromolecules, one can nowadays utilize the existing tools of molecular modeling simulations. In this review, we report an advanced practice to reveal the 3D structures and the interactions, through the combination of all‐atom molecular dynamics simulations and network analysis applied to different types of SDMs. By combining the computational results to the experimental ones, we show the potential of this approach for an in‐depth understanding of the sequence‐structure‐property relationships in discrete macromolecular systems, toward guiding their rational design for specific functions.

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