折叠(DSP实现)
计算机科学
高分子
能源景观
蛋白质结构预测
航程(航空)
分辨率(逻辑)
运动学
化学
生物系统
算法
蛋白质结构
人工智能
物理
工程类
航空航天工程
生物
机械工程
生物化学
经典力学
标识
DOI:10.1146/annurev.biochem.77.062906.171838
摘要
Advances over the past few years have begun to enable prediction and design of macromolecular structures at near-atomic accuracy. Progress has stemmed from the development of reasonably accurate and efficiently computed all-atom potential functions as well as effective conformational sampling strategies appropriate for searching a highly rugged energy landscape, both driven by feedback from structure prediction and design tests. A unified energetic and kinematic framework in the Rosetta program allows a wide range of molecular modeling problems, from fibril structure prediction to RNA folding to the design of new protein interfaces, to be readily investigated and highlights areas for improvement. The methodology enables the creation of novel molecules with useful functions and holds promise for accelerating experimental structural inference. Emerging connections to crystallographic phasing, NMR modeling, and lower-resolution approaches are described and critically assessed.
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