Data from: ProtASR: an evolutionary framework for ancestral protein reconstruction with selection on folding stability

The computational reconstruction of ancestral proteins provides information on past biological events and has practical implications for biomedicine and biotechnology. Currently available tools for ancestral sequence reconstruction (ASR) are often based on empirical amino acid substitution models that assume that all sites evolve at the same rate and under the same process. However, this assumption is frequently violated because protein evolution is highly heterogeneous due to different selective constraints among sites. Here, we present ProtASR, a new evolutionary framework to infer ancestral protein sequences accounting for selection on protein stability. First, ProtASR generates site-specific substitution matrices through the structurally constrained mean-field substitution model (MF), which considers both unfolding and misfolding stability. We previously showed that MF models outperform empirical amino acid substitution models, as well as other structurally constrained substitution models, both in terms of likelihood and correctly inferring amino acid distributions across sites. In the second step, ProtASR adapts a well-established maximum-likelihood (ML) ASR procedure to infer ancestral proteins under MF models. A known bias of ML ASR methods is that they tend to overestimate the stability of ancestral proteins by under-estimating the frequency of deleterious mutations. We compared ProtASR under MF to two empirical substitution models (JTT and CAT), reconstructing the ancestral sequences of simulated proteins. ProtASR yields reconstructed proteins with less biased stabilities, which are significantly closer to those of the simulated proteins. Analysis of extant protein families suggests that folding stability evolves through time across protein families, potentially reflecting neutral fluctuation. Some families exhibit a more constant protein folding stability, while others are more variable. ProtASR is freely available from https://github.com/miguelarenas/protasr and includes detailed documentation and ready-to-use examples. It runs in seconds/minutes depending on protein length and alignment size.祖先蛋白质的计算重建能够为解析远古生物学事件提供关键信息，在生物医学与生物技术领域具备重要的实际应用价值。当前主流的祖先序列重建（Ancestral Sequence Reconstruction, ASR）工具，多基于经验性氨基酸替换模型，这类模型假设所有蛋白质位点以统一速率演化且遵循完全一致的突变过程。然而这一假设往往与实际情况不符，因为蛋白质演化过程中，不同位点面临的选择约束存在显著差异，导致演化过程呈现高度异质性。本文提出ProtASR——一款全新的演化分析框架，可在考量蛋白质稳定性选择压力的前提下精准推断祖先蛋白质序列。首先，ProtASR通过结构约束平均场替换模型（Structurally Constrained Mean-Field Substitution Model, MF）生成位点特异性替换矩阵，该模型同时兼顾蛋白质的解折叠稳定性与错配折叠稳定性。我们此前的研究已证实，相较于经验性氨基酸替换模型及其他结构约束型替换模型，平均场模型在似然值拟合以及准确预测位点间氨基酸分布两个维度均表现更优。第二步，ProtASR适配了一套成熟的最大似然（Maximum Likelihood, ML）祖先序列重建流程，以在平均场模型框架下完成祖先蛋白质的推断。已知基于最大似然的祖先序列重建方法存在一项固有偏差：这类方法往往会低估有害突变的发生频率，进而高估祖先蛋白质的稳定性。我们将基于平均场模型的ProtASR与两款经典经验性替换模型（JTT与CAT）进行对比实验，通过重建模拟蛋白质的祖先序列展开验证。实验结果表明，ProtASR所重建的蛋白质稳定性偏差更小，其结果与模拟蛋白质的真实稳定性更为接近，且差异具备统计学显著性。对现存蛋白质家族的演化分析显示，不同蛋白质家族的折叠稳定性随时间呈现动态变化，这一现象可能反映了中性演化的随机波动。部分蛋白质家族的折叠稳定性相对恒定，而另一些家族的稳定性则波动更为显著。ProtASR可通过https://github.com/miguelarenas/protasr免费获取，配套包含详细的官方文档与可直接运行的示例代码，其运行耗时依蛋白质长度与序列比对规模而定，通常仅需数秒至数分钟。