Choteau Sébastien A, Maldonado Kevin, Bergon Aurélie, Cristianini Marceau, Boujeant Mégane, Drets Lilian, Brun Christine, Spinelli Lionel, Zanzoni Andreas
Aix-Marseille University, Inserm, TAGC, UMR_S1090, Turing Centre for Living Systems, Marseille, France.
CNRS, Marseille, France.
F1000Res. 2025 Mar 28;14:128. doi: 10.12688/f1000research.160063.2. eCollection 2025.
The increasing incidence of emerging infectious diseases is posing serious global threats. Therefore, there is a clear need for developing computational methods that can assist and speed up experimental research to better characterize the molecular mechanisms of microbial infections.
In this context, we developed INT, an open-source computational workflow for large-scale protein-protein interaction inference between microbe and human by detecting putative molecular mimicry elements mediating the interaction with host proteins: short linear motifs (SLiMs) and host-like globular domains. INT exploits these putative elements to infer the interaction with human proteins by using known templates of domain-domain and SLiM-domain interaction templates. INT also provides robust Monte-Carlo simulations to assess the statistical significance of SLiM detection which suffers from false positives, and an interaction specificity filter to account for differences between motif-binding domains of the same family. We have also made INT available via a web server.
In two use cases, INT can identify potential interfaces in experimentally detected interaction between pathogenic type-3 secreted effectors and human proteins and infer biologically relevant interactions between Marburg virus and human proteins.
The INT workflow can be instrumental to better understand the molecular details of microbe-host interactions.
新发传染病发病率的不断上升对全球构成了严重威胁。因此，迫切需要开发能够辅助并加速实验研究的计算方法，以更好地描述微生物感染的分子机制。
在此背景下，我们开发了INT，这是一种开源计算工作流程，通过检测介导与宿主蛋白相互作用的假定分子模拟元件：短线性基序（SLiMs）和类宿主球状结构域，来推断微生物与人类之间大规模的蛋白质-蛋白质相互作用。INT利用这些假定元件，通过使用已知的结构域-结构域和SLiM-结构域相互作用模板，来推断与人类蛋白质的相互作用。INT还提供强大的蒙特卡洛模拟，以评估易出现假阳性的SLiM检测的统计显著性，并提供一个相互作用特异性过滤器，以考虑同一家族基序结合结构域之间的差异。我们还通过网络服务器提供了INT。
在两个用例中，INT可以识别致病性3型分泌效应器与人类蛋白质之间实验检测到的相互作用中的潜在界面，并推断马尔堡病毒与人类蛋白质之间的生物学相关相互作用。
INT工作流程有助于更好地理解微生物与宿主相互作用的分子细节。
