Designing Multifunctional Biomaterials via Protein Self-Assembly

ANGEWANDTE CHEMIE-INTERNATIONAL EDITION(2024)

引用 0|浏览2
暂无评分
摘要
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. This Minireview sums up cutting-edge concepts regarding the formation of protein-based supramolecular structures, compartmentalization, and self-assembly monitoring; it compares the routes of their modifications and applications in multifunctional biomaterial design. We summarize the current knowledge about machine learning/artificial intelligence applications for protein structure prediction/obtainment and link it to biomaterial performance.+image
更多
查看译文
关键词
Artificial Intelligence,Biomaterials,Machine Learning,Proteins,Self-Assembly
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要