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Computational design of heterochiral peptides against a helical target

机译:针对螺旋靶的杂手性肽的计算设计

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Polypeptides incorporating D-amino acids occasionally occur in nature and are an important class of pharmaceutical molecules. With the use of heterochiral Monte Carlo (HCMC), a method inspired by the de novo design of proteins, we develop peptide scaffolds for interacting with a molecular target, a left-handed alpha-helix. The HCMC approach concurrently seeks to optimize a peptide sequence, its internal conformation, and its docked conformation with a target surface. Several major classes of interactions are observed: (1) homochiral interactions between two alpha(L) helices, (2) heterochiral interactions between an alpha(L) and an alpha(R) helix, and (3) heterochiral interactions between the alpha(L) target and novel nonhelical structures. We explore the application of HCMC to simulating the preferential enantioselectivity of heterochiral complexes. Implications for biomimetic design in molecular recognition are discussed.
机译:掺入D-氨基酸的多肽偶尔会出现在自然界中,并且是一类重要的药物分子。通过使用异手性蒙特卡洛(HCMC)(一种从头设计蛋白质的方法),我们开发了与分子靶标(左手α-螺旋)相互作用的肽支架。 HCMC方法同时寻求优化肽序列,其内部构象及其与靶标表面的对接构象。观察到了几种主要的相互作用类型:(1)两个alpha(L)螺旋之间的同手性相互作用;(2)alpha(L)和alpha(R)螺旋之间的异手性相互作用;以及(3)alpha(L)之间的异手性相互作用L)目标和新颖的非螺旋结构。我们探索了HCMC在模拟异手性配合物优先对映选择性中的应用。讨论了仿生设计在分子识别中的意义。

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