Ramakrishnan Maithreyi, van Teijlingen Alexander, Tuttle Tell, Ulijn R V
Advanced Science Research Center (ASRC) at the Graduate Center, City University of New York (CUNY), New York, NY 10031, USA.
Department of Chemistry, Hunter College, The City University of New York, New York, NY 10065, USA.
Angew Chem Int Ed Engl. 2023 Apr 24;62(18):e202218067. doi: 10.1002/anie.202218067. Epub 2023 Feb 14.
Interest in peptide-based supramolecular materials has grown extensively since the 1980s and the application of computational methods has paralleled this. These methods contribute to the understanding of experimental observations based on interactions and inform the design of new supramolecular systems. They are also used to virtually screen and navigate these very large design spaces. Increasingly, the use of artificial intelligence is employed to screen far more candidates than traditional methods. Based on a brief history of computational and experimentally integrated investigations of peptide structures, we explore recent impactful examples of computationally driven investigation into peptide self-assembly, focusing on recent advances in methodology development. It is clear that the integration between experiment and computation to understand and design new systems is becoming near seamless in this growing field.
自20世纪80年代以来，人们对基于肽的超分子材料的兴趣大幅增长，计算方法的应用也与此同步发展。这些方法有助于基于相互作用理解实验观察结果，并为新超分子体系的设计提供信息。它们还用于虚拟筛选和探索这些非常大的设计空间。越来越多地，人工智能被用于筛选比传统方法多得多的候选物。基于肽结构的计算与实验综合研究的简要历史，我们探讨了计算驱动的肽自组装研究中最近有影响力的例子，重点关注方法学发展的最新进展。显然，在这个不断发展的领域中，实验与计算之间为理解和设计新体系而进行的整合正变得几乎无缝。
