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从头蛋白质设计。I. 探索稳定性和特异性。

De novo protein design. I. In search of stability and specificity.

作者信息

Koehl P, Levitt M

机构信息

Department of Structural Biology, Fairchild Building, Stanford University, Stanford, CA 94305, USA.

出版信息

J Mol Biol. 1999 Nov 12;293(5):1161-81. doi: 10.1006/jmbi.1999.3211.

Abstract

We have developed a fully automated protein design strategy that works on the entire sequence of the protein and uses a full atom representation. At each step of the procedure, an all-atom model of the protein is built using the template protein structure and the current designed sequence. The energy of the model is used to drive a Monte Carlo optimization in sequence space: random moves are either accepted or rejected based on the Metropolis criterion. We rely on the physical forces that stabilize native protein structures to choose the optimum sequence. Our energy function includes van der Waals interactions, electrostatics and an environment free energy. Successful protein design should be specific and generate a sequence compatible with the template fold and incompatible with competing folds. We impose specificity by maintaining the amino acid composition constant, based on the random energy model. The specificity of the optimized sequence is tested by fold recognition techniques. Successful sequence designs for the B1 domain of protein G, for the lambda repressor and for sperm whale myoglobin are presented. We show that each additional term of the energy function improves the performance of our design procedure: the van der Waals term ensures correct packing, the electrostatics term increases the specificity for the correct native fold, and the environment solvation term ensures a correct pattern of buried hydrophobic and exposed hydrophilic residues. For the globin family, we show that we can design a protein sequence that is stable in the myoglobin fold, yet incompatible with the very similar hemoglobin fold.

摘要

我们开发了一种全自动蛋白质设计策略,该策略作用于蛋白质的整个序列,并使用全原子表示法。在该过程的每一步,都利用模板蛋白质结构和当前设计的序列构建蛋白质的全原子模型。模型的能量用于驱动序列空间中的蒙特卡罗优化:根据 metropolis 准则接受或拒绝随机移动。我们依靠稳定天然蛋白质结构的物理力来选择最佳序列。我们的能量函数包括范德华相互作用、静电作用和环境自由能。成功的蛋白质设计应该具有特异性,并且生成与模板折叠兼容且与竞争折叠不兼容的序列。基于随机能量模型,我们通过保持氨基酸组成恒定来施加特异性。通过折叠识别技术测试优化序列的特异性。展示了针对蛋白质 G 的 B1 结构域、λ 阻遏物和抹香鲸肌红蛋白的成功序列设计。我们表明,能量函数的每个附加项都提高了我们设计过程的性能:范德华项确保正确堆积,静电项增加对正确天然折叠的特异性,环境溶剂化项确保掩埋的疏水残基和暴露的亲水残基具有正确的模式。对于珠蛋白家族,我们表明我们可以设计出一种在肌红蛋白折叠中稳定但与非常相似的血红蛋白折叠不兼容的蛋白质序列。

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