Chen Yao Chi, Sargsyan Karen, Wright Jon D, Chen Yu-Hsien, Huang Yi-Shuian, Lim Carmay
Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan.
Elife. 2024 Sep 16;13:RP96643. doi: 10.7554/eLife.96643.
Experimental detection of residues critical for protein-protein interactions (PPI) is a time-consuming, costly, and labor-intensive process. Hence, high-throughput PPI-hot spot prediction methods have been developed, but they have been validated using relatively small datasets, which may compromise their predictive reliability. Here, we introduce PPI-hotspot, a novel method for identifying PPI-hot spots using the free protein structure, and validated it on the largest collection of experimentally confirmed PPI-hot spots to date. We explored the possibility of detecting PPI-hot spots using (i) FTMap in the PPI mode, which identifies hot spots on protein-protein interfaces from the protein structure, and (ii) the interface residues predicted by AlphaFold-Multimer. PPI-hotspot yielded better performance than FTMap and SPOTONE, a webserver for predicting PPI-hot spots given the protein sequence. When combined with the AlphaFold-Multimer-predicted interface residues, PPI-hotspot yielded better performance than either method alone. Furthermore, we experimentally verified several PPI-hotspot-predicted PPI-hot spots of eukaryotic elongation factor 2. Notably, PPI-hotspot can reveal PPI-hot spots not obvious from complex structures, including those in contact with binding partners. PPI-hotspot serves as a valuable tool for understanding PPI mechanisms and aiding drug design. It is available as a web server (https://ppihotspotid.limlab.dnsalias.org/) and open-source code (https://github.com/wrigjz/ppihotspotid/).
对蛋白质-蛋白质相互作用（PPI）至关重要的残基进行实验检测是一个耗时、昂贵且 labor-intensive 的过程。因此，已开发出高通量 PPI 热点预测方法，但这些方法使用的数据集相对较小，这可能会影响其预测可靠性。在此，我们介绍了 PPI-hotspot，这是一种利用游离蛋白质结构识别 PPI 热点的新方法，并在迄今为止最大的一组经实验确认的 PPI 热点上对其进行了验证。我们探索了使用以下方法检测 PPI 热点的可能性：（i）PPI 模式下的 FTMap，它从蛋白质结构中识别蛋白质-蛋白质界面上的热点；（ii）AlphaFold-Multimer 预测的界面残基。PPI-hotspot 的性能优于 FTMap 和 SPOTONE（一个根据蛋白质序列预测 PPI 热点的网络服务器）。当与 AlphaFold-Multimer 预测的界面残基结合使用时，PPI-hotspot 的性能优于单独使用任何一种方法。此外，我们通过实验验证了真核生物延伸因子 2 的几个由 PPI-hotspot 预测的 PPI 热点。值得注意的是，PPI-hotspot 可以揭示从复杂结构中不明显的 PPI 热点，包括那些与结合伴侣接触的热点。PPI-hotspot 是理解 PPI 机制和辅助药物设计的宝贵工具。它以网络服务器（https://ppihotspotid.limlab.dnsalias.org/）和开源代码（https://github.com/wrigjz/ppihotspotid/）的形式提供。
