FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants.
FireProt: Energy- and Evolution-Based Computational Design of Thermostable Multiple-Point Mutants.
复制标题
FireProt：热稳定多点突变体的基于能量和进化的计算设计。
DOI：
10.1371/journal.pcbi.1004556
复制
发表时间：
2015-11
影响因子：
4.3
通讯作者：
Damborsky J
中科院分区：
文献类型：
--
作者：
Bednar D;Beerens K;Sebestova E;Bendl J;Khare S;Chaloupkova R;Prokop Z;Brezovsky J;Baker D;Damborsky J
人们对增加蛋白质的稳定性以增强其作为生物催化剂、治疗剂、诊断剂和纳米材料的效用有极大的兴趣。定向进化是一种强大的，但在实验上很费力的方法。计算方法提供了有吸引力的替代方案。然而，由于预测的可靠性有限以及取代的潜在拮抗作用，通常只能通过计算机模拟预测单点突变，进行实验验证，然后重组为多点突变体。因此，仍然需要进行大量筛选。在这里，我们提出了FireProt，一个强大的计算策略，用于预测高度稳定的多点突变体，结合基于能量和进化的方法与智能过滤，以确定添加剂稳定突变。FireProt的可靠性和适用性通过验证其对ProTherm数据库中656个突变的预测来证明。我们证明了模型酶卤代烷烃脱卤酶DhaA和γ-六氯环己烷脱氯化氢酶LinA的热稳定性可以通过构建和表征少数多点突变体而显著增加（Δ Tm = 24°C和21°C）。FireProt可以应用于任何具有三级结构和同源序列的蛋白质，并将促进快速开发用于生物医学和生物技术应用的稳健蛋白质。蛋白质越来越多地用于许多生物技术应用。决定蛋白质适用性的一个关键特性是它们在操作条件下的稳定性。天然蛋白质可以通过改变其结构来稳定。分子生物学的方法允许随意对蛋白质结构进行修饰-突变，但是在哪里突变以及引入哪种氨基酸以获得更好的稳定性并不简单。计算方法可用于使用计算机预测稳定突变。目前的计算方法预测单点突变库，需要单独构建，测试和重组，导致不平凡的实验工作。在这里，我们提出了一个强大的计算策略预测多点突变，提供非常稳定的蛋白质与最小的实验努力。
There is great interest in increasing proteins’ stability to enhance their utility as biocatalysts, therapeutics, diagnostics and nanomaterials. Directed evolution is a powerful, but experimentally strenuous approach. Computational methods offer attractive alternatives. However, due to the limited reliability of predictions and potentially antagonistic effects of substitutions, only single-point mutations are usually predicted in silico, experimentally verified and then recombined in multiple-point mutants. Thus, substantial screening is still required. Here we present FireProt, a robust computational strategy for predicting highly stable multiple-point mutants that combines energy- and evolution-based approaches with smart filtering to identify additive stabilizing mutations. FireProt’s reliability and applicability was demonstrated by validating its predictions against 656 mutations from the ProTherm database. We demonstrate that thermostability of the model enzymes haloalkane dehalogenase DhaA and γ-hexachlorocyclohexane dehydrochlorinase LinA can be substantially increased (ΔT m = 24°C and 21°C) by constructing and characterizing only a handful of multiple-point mutants. FireProt can be applied to any protein for which a tertiary structure and homologous sequences are available, and will facilitate the rapid development of robust proteins for biomedical and biotechnological applications. Proteins are increasingly used in numerous biotechnological applications. A key property determining proteins’ applicability is their stability under operating conditions. Natural proteins can be stabilized by modification of their structure. Methods of molecular biology allow introduction of modifications–mutations–to the protein structure at will, but it is not straightforward where to mutate and which amino acid to introduce for better stability. Computational methods can be used for prediction of stabilizing mutations using computers. Current computational methods predict libraries of single-point mutations, which need to be constructed individually, tested and recombined, resulting in non-trivial experimental effort. Here we present a robust computational strategy for predicting multiple-point mutants, providing extremely stabilized proteins with a minimal experimental effort.