Designing Multifunctional Biomaterials via Protein Self-Assembly

Aleksei Solomonov, Anna Kozell, Ulyana Shimanovich

Research output: Contribution to journalShort surveypeer-review

Abstract

Protein self-assembly is a fundamental biological process where proteins spontaneously organize into complex and functional structures without external direction. This process is crucial for the formation of various biological functionalities. However, when protein self-assembly fails, it can trigger the development of multiple disorders, thus making understanding this phenomenon extremely important. Up until recently, protein self-assembly has been solely linked either to biological function or malfunction; however, in the past decade or two it has also been found to hold promising potential as an alternative route for fabricating materials for biomedical applications. It is therefore necessary and timely to summarize the key aspects of protein self-assembly: how the protein structure and self-assembly conditions (chemical environments, kinetics, and the physicochemical characteristics of protein complexes) can be utilized to design biomaterials. This minireview focuses on the basic concepts of forming supramolecular structures, and the existing routes for modifications. We then compare the applicability of different approaches, including compartmentalization and self-assembly monitoring. Finally, based on the cutting-edge progress made during the last years, we summarize the current knowledge about tailoring a final function by introducing changes in self-assembly and link it to biomaterials’ performance.

Original languageEnglish
Article numbere202318365
JournalAngewandte Chemie - International Edition
Volume63
Issue number14
Early online date11 Jan 2024
DOIs
StatePublished - 2 Apr 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2024 The Authors. Angewandte Chemie International Edition published by Wiley-VCH GmbH.

Funding

U.S. acknowledges financial support from the Nella and Leon Benoziyo Center for Neurological Diseases. In addition, U.S. thanks the Perlman family for funding the Shimanovich Lab at the Weizmann Institute of Science: “This research was made possible in part by the generosity of the Harold Perlman Family.” The authors would like to acknowledge partial support from the GMJ Schmidt Minerva Center of Supramolecular Architectures at the Weizmann Institute, Mondry Family Fund for University of Michigan/Weizmann collaboration, Gerald Schwartz and Heather Reisman Foundation, and WIS Sustainability and Energy Research Initiative (SAERI). This research was supported by a research grant from the Tom and Mary Beck Center for Advanced and Intelligent Materials at the Weizmann Institute of Science, Rehovot, Israel, supported by a research grant from the Estate of David A. Fishstrom. The authors are also grateful to Steve Manch for editing the English in the manuscript.

FundersFunder number
Gerald Schwartz and Heather Reisman Foundation
Mondry Family Fund for University of Michigan/Weizmann
Perlman family for funding the Shimanovich Lab
SAERI
Tom and Mary Beck Center for Advanced and Intelligent Materials at the Weizmann Institute of Science
WIS Sustainability and Energy Research Initiative
Weizmann Institute
Weizmann Institute of Science

    Keywords

    • Artificial Intelligence
    • Biomaterials
    • Machine Learning
    • Proteins
    • Self-Assembly

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