Small macrocycles with four or fewer amino acids are among the most potent natural products known, but there is currently no way to systematically generate such compounds. We describe a computational method for identifying ordered macrocycles composed of alpha, beta, gamma, and 17 other amino acid backbone chemistries, which we used to predict 14.9 million closed cycles composed of >42,000 monomer combinations. We chemically synthesized 18 macrocycles predicted to adopt single low-energy states and determined their x-ray or nuclear magnetic resonance structures; 15 of these were very close to the design models. We illustrate the therapeutic potential of these macrocycle designs by developing selective inhibitors of three protein targets of current interest. By opening up a vast space of readily synthesizable drug-like macrocycles, our results should considerably enhance structure-based drug design.

中文翻译：

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化学多样化结构大环低聚酰胺的广泛发现

具有四个或更少氨基酸的小大环是已知的最有效的天然产物之一，但目前还没有办法系统地生成此类化合物。我们描述了一种计算方法，用于识别由 α、β、γ 和其他 17 种氨基酸主链化学组成的有序大环，我们用它来预测由超过 42,000 个单体组合组成的 1490 万个闭环。我们化学合成了 18 个预计采用单一低能态的大环化合物，并确定了它们的 X 射线或核磁共振结构；其中 15 个非常接近设计模型。我们通过开发当前感兴趣的三种蛋白质靶标的选择性抑制剂来说明这些大环设计的治疗潜力。通过开辟易于合成的类药物大环化合物的广阔空间，我们的结果将大大增强基于结构的药物设计。