论文标题
蛋白质折叠在现代时代：行人指南
Protein folding in the modern era: a pedestrian's guide
论文作者
论文摘要
从原发性氨基酸序列中蛋白质二级和三级结构的预测既是一个非常重要且难以置信的困难问题。准确预测蛋白质的天然结构可以提供有关其功能的关键见解，最终导致药物设计和疾病诊断的突破。从1960年代的最早折叠实验到当今最先进的算法的使用，该领域的历史悠久。本文回顾了蛋白质折叠的历史，重点是现代方法如何解决蛋白质折叠问题。假设只有对生物化学的基本知识，我们将探索基督徒安宁森的古典实验，牛RNase，赛勒斯·艾尔维塔尔（Cyrus Levinthal）提出的蛋白质折叠的悖论，现代机器学习方法的成功以及量子折叠的量子计算的希望。
The prediction of protein secondary and tertiary structures from the primary amino acid sequence is both an incredibly important and incredibly difficult problem. Accurate prediction of a protein's native structure can provide critical insights about its function, ultimately leading to breakthoughs in drug design and disease diagnosis. The field has a rich history, from the earliest folding experiments in the 1960's to the use of state-of-the-art algorithms today; this article reviews protein folding's history with an emphasis on how modern methods are tackling the protein folding problem. Assuming only a basic knowledge of biochemistry, we'll explore Christian Anfinsen's classical experiments with bovine RNase, the paradox of protein folding proposed by Cyrus Levinthal, the success of modern machine learning methods, and the promise of quantum computation for protein folding.
