Department of Chemistry, King's College London, London, UK.
Department of Engineering and Materials Science, Johns Hopkins University, Baltimore, MD, USA.
J Membr Biol. 2021 Feb;254(1):75-96. doi: 10.1007/s00232-021-00174-1. Epub 2021 Feb 10.
The use of designed antimicrobial peptides as drugs has been impeded by the absence of simple sequence-structure-function relationships and design rules. The likely cause is that many of these peptides permeabilize membranes via highly disordered, heterogeneous mechanisms, forming aggregates without well-defined tertiary or secondary structure. We suggest that the combination of high-throughput library screening with atomistic computer simulations can successfully address this challenge by tuning a previously developed general pore-forming peptide into a selective pore-former for different lipid types. A library of 2916 peptides was designed based on the LDKA template. The library peptides were synthesized and screened using a high-throughput orthogonal vesicle leakage assay. Dyes of different sizes were entrapped inside vesicles with varying lipid composition to simultaneously screen for both pore size and affinity for negatively charged and neutral lipid membranes. From this screen, nine different LDKA variants that have unique activity were selected, sequenced, synthesized, and characterized. Despite the minor sequence changes, each of these peptides has unique functional properties, forming either small or large pores and being selective for either neutral or anionic lipid bilayers. Long-scale, unbiased atomistic molecular dynamics (MD) simulations directly reveal that rather than rigid, well-defined pores, these peptides can form a large repertoire of functional dynamic and heterogeneous aggregates, strongly affected by single mutations. Predicting the propensity to aggregate and assemble in a given environment from sequence alone holds the key to functional prediction of membrane permeabilization.
设计抗菌肽作为药物的应用受到缺乏简单的序列-结构-功能关系和设计规则的阻碍。其可能的原因是，许多这些肽通过高度无序、异质的机制来渗透细胞膜，形成没有明确定义的三级或二级结构的聚集体。我们认为，高通量文库筛选与原子计算机模拟的结合，可以通过调整先前开发的通用成孔肽，成功应对这一挑战，使其成为针对不同脂质类型的选择性成孔剂。基于 LDKA 模板设计了一个包含 2916 个肽的文库。使用高通量正交囊泡渗漏测定法合成并筛选文库肽。具有不同脂质组成的囊泡内包封了不同大小的染料，以同时筛选孔径和对带负电荷和中性脂质膜的亲和力。通过这种筛选，选择、测序、合成和表征了 9 种具有独特活性的不同 LDKA 变体。尽管序列变化很小，但这些肽中的每一种都具有独特的功能特性，形成小或大的孔，并对中性或阴离子脂质双层具有选择性。长规模、无偏原子分子动力学 (MD) 模拟直接揭示了这些肽可以形成一大类功能动态和异质聚集体，而不是刚性的、明确定义的孔，并且强烈受到单个突变的影响。仅从序列预测在给定环境中聚集和组装的倾向是功能预测膜通透性的关键。
