While nature evolved polypeptides over billions of years, protein design by evolutionary mimicry is progressing at a far more rapid pace. The mutation, selection, and amplification steps of the evolutionary cycle may be imitated in the laboratory using existing proteins, or molecules created de novo from random sequence space, as starting templates. However, the astronomically large number of possible polypeptide sequences remains an obstacle to identifying and isolating functionally interesting variants. Intelligently designed libraries and improved search techniques are consequently important for future advances. In this regard, combining experimental and computational methods holds particular promise for the creation of tailored protein receptors and catalysts for tasks unimagined by nature.

中文翻译：

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通过定向进化进行蛋白质设计。

尽管自然界在数十亿年的时间里进化出多肽，但通过进化模仿进行蛋白质设计的步伐却要快得多。进化周期的突变，选择和扩增步骤可以在实验室中使用现有的蛋白质或从随机序列空间重新创建的分子作为起始模板来进行模拟。然而，天文学上大量可能的多肽序列仍然是鉴定和分离功能上有趣的变体的障碍。因此，智能设计的库和改进的搜索技术对于未来的发展非常重要。在这方面，将实验方法和计算方法结合起来，对于为自然界无法想象的任务创建定制的蛋白质受体和催化剂具有特别的希望。