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Mechanisms of Biomolecular Self-Assembly Investigated Through In Situ Observations of Structures and Dynamics.

Sakshi Yadav SchmidKacper J LachowskiHuat Thart ChiangLilo D PozzoJim De YoreoShuai Zhang
Published in: Angewandte Chemie (International ed. in English) (2023)
Biomolecular self-assembly of hierarchical materials is a precise and adaptable bottom-up approach to synthesizing across scales with considerable energy, health, environment, sustainability, and information technology applications. To achieve desired functions in biomaterials, it is essential to directly observe assembly dynamics and structural evolutions that reflect the underlying energy landscape and the assembly mechanism. This review will summarize the current understanding of biomolecular assembly mechanisms based on in situ characterization and discuss the broader significance and achievements of newly gained insights. In addition, we will also introduce how emerging deep learning/machine learning-based approaches, multiparametric characterization, and high-throughput methods can boost the development of biomolecular self-assembly. The objective of this review is to accelerate the development of in situ characterization approaches for biomolecular self-assembly and to inspire the next generation of biomimetic materials.
Keyphrases
  • machine learning
  • deep learning
  • high throughput
  • healthcare
  • public health
  • artificial intelligence
  • health information
  • mental health
  • single cell
  • mass spectrometry