Evolution of it-Peptide Self-Assembly: From Understanding to Prediction and Control

被引:9
作者
Ferguson, Andrew L. [1 ]
Tovar, John D. [2 ]
机构
[1] Univ Chicago, Pritzker Sch Mol Engn, Chicago, IL 60637 USA
[2] Johns Hopkins Univ, Dept Chem, Baltimore, MD 21218 USA
基金
美国国家科学基金会;
关键词
NUCLEATED-POLYMERIZATION MODEL; PI-CONJUGATED OLIGOPEPTIDES; ENERGY-TRANSFER; AMINO-ACID; NANOSTRUCTURES; FIELD; AGGREGATION; SIMULATION; DESIGN;
D O I
10.1021/acs.langmuir.2c02399
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Supramolecular materials derived from the self -assembly of engineered molecules continue to garner tremendous scientific and technological interest. Recent innovations include the realization of nano-and mesoscale particles (0D), rods and fibrils (1D), sheets (2D), and even extended lattices (3D). Our research groups have focused attention over the past 15 years on one particular class of supramolecular materials derived from oligopeptides with embedded pi-electron units, where the oligopeptides can be viewed as substituents or side chains to direct the assembly of the central pi-electron cores. Upon assembly, the pi-systems are driven into close cofacial architectures that facilitate a variety of energy migration processes within the nanomaterial volume, including exciton transport, voltage trans-mission, and photoinduced electron transfer. Like many practi-tioners of supramolecular materials science, many of our initial molecular designs were designed with substantial inspiration from biologically occurring self-assembly coupled with input from chemical intuition and molecular modeling and simulation. In this feature article, we summarize our current understanding of the pi-peptide self-assembly process as documented through our body of publications in this area. We address fundamental spectroscopic and computational tools used to extract information regarding the internal structures and energetics of the pi-peptide assemblies, and we address the current state of the art in terms of recent applications of data science tools in conjunction with high -throughput computational screening and experimental assays to guide the efficient traversal of the pi-peptide molecular design space. The abstract image details our integrated program of chemical synthesis, spectroscopic and functional characterization, multiscale simulation, and machine learning which has advanced the understanding and control of the assembly of synthetic pi-conjugated peptides into supramolecular nanostructures with energy and biomedical applications.
引用
收藏
页码:15463 / 15475
页数:13
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