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Protein folding with stochastic L-systems

机译：带有随机L系统的蛋白质折叠

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Protein molecules adopt a specific global 3D structure in order to carry out their biological function. To achieve this native state a newly formed protein molecule has to fold. The folding process and the final fold are both determined by the sequence of amino acids making up the protein chain. It is not currently possible to predict the conformation of the native state from the amino acid sequence alone and the protein folding process is still not fully understood. We are using L-systems, sets of rewriting rules, to model the folding of protein-like structures. Models of protein folding vary in complexity and the amount of prior knowledge they contain on existing native protein structures. In a previous paper we presented a method of using open L-systems to model the folding of protein-like structures using physics-based rewriting rules. Here we present an L-systems model of protein folding that uses knowledge-based rewriting rules and stochastic L-systems.
机译：蛋白分子采用特定的全局3D结构以执行其生物学功能。为了达到这种天然状态，新形成的蛋白质分子必须折叠。折叠过程和最终折叠都由构成蛋白质链的氨基酸序列决定。当前不可能仅从氨基酸序列预测天然状态的构象，并且蛋白质折叠过程仍未被完全理解。我们正在使用L系统（重写规则集）来模拟蛋白质样结构的折叠。蛋白质折叠的模型在复杂性和它们在现有天然蛋白质结构上所包含的先验知识的数量方面有所不同。在先前的论文中，我们提出了一种使用开放L系统的方法，该方法使用基于物理的重写规则对蛋白质样结构的折叠进行建模。在这里，我们介绍一种蛋白质折叠的L系统模型，该模型使用基于知识的重写规则和随机L系统。

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