Software to predict the change in protein stability upon point mutation is a valuable tool for a number of biotechnological and scientific problems. To facilitate the development of such software and provide easy access to the available experimental data, the ProTherm database was created. Biases in the methods and types of information collected has led to disparity in the types of mutations for which experimental data is available. For example, mutations to alanine are hugely overrepresented whereas those involving charged residues, especially from one charged residue to another, are underrepresented. ProTherm subsets created as benchmark sets that do not account for this often underrepresent tense certain mutational types. This issue introduces systematic biases into previously published protocols’ ability to accurately predict the change in folding energy on these classes of mutations. To resolve this issue, we have generated a new benchmark set with these problems corrected. We have then used the benchmark set to test a number of improvements to the point mutation energetics tools in the Rosetta software suite.

中文翻译：

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蛋白质突变自由能的预测：基准和采样改进提高分类精度

用于预测点突变时蛋白质稳定性变化的软件是解决许多生物技术和科学问题的宝贵工具。为了促进此类软件的开发并提供对可用实验数据的轻松访问，创建了 ProTherm 数据库。所收集信息的方法和类型的偏差导致了可用实验数据的突变类型的差异。例如，丙氨酸的突变被严重过度代表，而那些涉及带电残基的突变，尤其是从一个带电残基到另一个，则被低估了。作为基准集创建的 ProTherm 子集没有考虑到这一点，通常代表紧张的某些突变类型。这个问题将系统性偏差引入到以前发布的协议中，以准确预测这些类突变的折叠能量变化的能力。为了解决这个问题，我们生成了一个新的基准集，并纠正了这些问题。然后，我们使用基准集来测试 Rosetta 软件套件中点突变能量学工具的一些改进。