Residue coevolution estimations coupled to machine learning methods are revolutionizing the ability of protein structure prediction approaches to model proteins that lack clear homologous templates in the Protein Data Bank (PDB). This has been patent in the last round of the Critical Assessment of Structure Prediction (CASP), which presented several very good models for the hardest targets. Unfortunately, literature reporting on these advances often lacks digests tailored to lay end users; moreover, some of the top-ranking predictors do not provide webservers that can be used by nonexperts. How can then end users benefit from these advances and correctly interpret the predicted models? Here we review the web resources that biologists can use today to take advantage of these state-of-the-art methods in their research, including not only the best de novo modeling servers but also datasets of models precomputed by experts for structurally uncharacterized protein families. We highlight their features, advantages and pitfalls for predicting structures of proteins without clear templates. We present a broad number of applications that span from driving forward biochemical investigations that lack experimental structures to actually assisting experimental structure determination in X-ray diffraction, cryo-EM and other forms of integrative modeling. We also discuss issues that must be considered by users yet still require further developments, such as global and residue-wise model quality estimates and sources of residue coevolution other than monomeric tertiary structure.

中文翻译：

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用于从头蛋白质结构预测的最先进的网络服务

残基协同进化估计与机器学习方法相结合，正在彻底改变蛋白质结构预测方法对蛋白质数据库 (PDB) 中缺乏明确同源模板的蛋白质进行建模的能力。这在上一轮结构预测的关键评估 (CASP) 中已获得专利，它为最难的目标提供了几个非常好的模型。不幸的是，关于这些进步的文献报道往往缺乏为非专业最终用户量身定制的摘要；此外，一些排名靠前的预测器不提供可供非专家使用的网络服务器。那么最终用户如何从这些进步中受益并正确解释预测模型？在这里，我们回顾了生物学家今天可以使用的网络资源，以在他们的研究中利用这些最先进的方法，不仅包括最好的从头建模服务器以及专家为结构未表征的蛋白质家族预先计算的模型数据集。我们强调了它们在没有明确模板的情况下预测蛋白质结构的特征、优势和缺陷。我们提出了广泛的应用，从推动缺乏实验结构的生化研究到实际辅助 X 射线衍射、冷冻电镜和其他形式的综合建模中的实验结构确定。我们还讨论了用户必须考虑但仍需要进一步发展的问题，例如全球和残基模型质量估计以及除单体三级结构之外的残基协同进化来源。