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通过序列独立片段组装模拟进行从头蛋白质折叠设计。

De novo protein fold design through sequence-independent fragment assembly simulations.

机构信息

Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109.

Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109.

出版信息

Proc Natl Acad Sci U S A. 2023 Jan 24;120(4):e2208275120. doi: 10.1073/pnas.2208275120. Epub 2023 Jan 19.

Abstract

De novo protein design generally consists of two steps, including structure and sequence design. Many protein design studies have focused on sequence design with scaffolds adapted from native structures in the PDB, which renders novel areas of protein structure and function space unexplored. We developed FoldDesign to create novel protein folds from specific secondary structure (SS) assignments through sequence-independent replica-exchange Monte Carlo (REMC) simulations. The method was tested on 354 non-redundant topologies, where FoldDesign consistently created stable structural folds, while recapitulating on average 87.7% of the SS elements. Meanwhile, the FoldDesign scaffolds had well-formed structures with buried residues and solvent-exposed areas closely matching their native counterparts. Despite the high fidelity to the input SS restraints and local structural characteristics of native proteins, a large portion of the designed scaffolds possessed global folds completely different from natural proteins in the PDB, highlighting the ability of FoldDesign to explore novel areas of protein fold space. Detailed data analyses revealed that the major contributions to the successful structure design lay in the optimal energy force field, which contains a balanced set of SS packing terms, and REMC simulations, which were coupled with multiple auxiliary movements to efficiently search the conformational space. Additionally, the ability to recognize and assemble uncommon super-SS geometries, rather than the unique arrangement of common SS motifs, was the key to generating novel folds. These results demonstrate a strong potential to explore both structural and functional spaces through computational design simulations that natural proteins have not reached through evolution.

摘要

从头设计蛋白质通常包含两个步骤,包括结构设计和序列设计。许多蛋白质设计研究都集中在序列设计上,使用源自 PDB 中天然结构的支架,从而探索蛋白质结构和功能空间的新领域。我们开发了 FoldDesign 来通过序列独立的复制交换蒙特卡罗(REMC)模拟从特定的二级结构(SS)分配中创建新的蛋白质折叠。该方法在 354 个非冗余拓扑结构上进行了测试,其中 FoldDesign 始终能够创建稳定的结构折叠,同时平均重现 87.7%的 SS 元素。同时,FoldDesign 支架具有良好的结构,埋置残基和溶剂暴露区域与天然结构非常匹配。尽管与输入 SS 约束和天然蛋白质的局部结构特征高度一致,但设计的支架大部分具有与 PDB 中天然蛋白质完全不同的全局折叠,这突出了 FoldDesign 探索蛋白质折叠空间新领域的能力。详细的数据分析表明,成功的结构设计的主要贡献在于优化的能量力场,其中包含了一组平衡的 SS 包装项,以及 REMC 模拟,该模拟与多个辅助运动相结合,可以有效地搜索构象空间。此外,识别和组装不常见的超 SS 几何形状的能力,而不是常见 SS 基序的独特排列,是生成新折叠的关键。这些结果表明,通过计算设计模拟探索结构和功能空间的潜力很大,而自然蛋白质通过进化尚未达到这些空间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fec5/9942881/c0b4ef59c455/pnas.2208275120fig01.jpg

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