Significant efforts have been invested into understanding and predicting the molecular consequences of mutations in protein coding regions, however nearly all approaches have been developed using globular, soluble proteins. These methods have been shown to poorly translate to studying the effects of mutations in membrane proteins. To fill this gap, here we report, mCSM-membrane, a user-friendly web server that can be used to analyse the impacts of mutations on membrane protein stability and the likelihood of them being disease associated. mCSM-membrane derives from our well-established mutation modelling approach that uses graph-based signatures to model protein geometry and physicochemical properties for supervised learning. Our stability predictor achieved correlations of up to 0.72 and 0.67 (on cross validation and blind tests, respectively), while our pathogenicity predictor achieved a Matthew's Correlation Coefficient (MCC) of up to 0.77 and 0.73, outperforming previously described methods in both predicting changes in stability and in identifying pathogenic variants. mCSM-membrane will be an invaluable and dedicated resource for investigating the effects of single-point mutations on membrane proteins through a freely available, user friendly web server at http://biosig.unimelb.edu.au/mcsm_membrane.

中文翻译：

---

mCSM 膜：预测突变对跨膜蛋白的影响。

已经投入大量努力来理解和预测蛋白质编码区突变的分子后果，但是几乎所有方法都是使用球状可溶性蛋白质开发的。这些方法已被证明不能很好地转化为研究膜蛋白突变的影响。为了填补这一空白，我们在这里报告了 mCSM-membrane，这是一种用户友好的网络服务器，可用于分析突变对膜蛋白稳定性的影响以及它们与疾病相关的可能性。mCSM-membrane 源自我们成熟的突变建模方法，该方法使用基于图形的签名来模拟蛋白质几何形状和物理化学特性以进行监督学习。我们的稳定性预测器实现了高达 0.72 和 0.67 的相关性（分别在交叉验证和盲测中），而我们的致病性预测器实现了高达 0.77 和 0.73 的马修相关系数 (MCC)，在预测稳定性变化和识别致病变异方面优于先前描述的方法。mCSM-membrane 将成为一种宝贵的专用资源，用于通过 http://biosig.unimelb.edu.au/mcsm_membrane 上免费提供的用户友好型网络服务器研究单点突变对膜蛋白的影响。