To successfully achieve PROTrEIN´s goals, we designed a comprehensive research program around PROTrEIN´s three main Research objectives. The success of the project – where PROTrEIN ESRs made crucial contributions in achieving and overdelivering on the network´s goals, as well as important contributions to basic research, personalized medicine, biomarker discovery, protein structure analysis, and therapeutics development - is a testament to the dedication of all partners, the excellence of the training and supervision, and the fruitful collaborations forged.
In Research Objective 1, several AI-driven tools were developed to enhance computational proteomics. These tools included a deep learning model to predict peptide stability; the XMass model, that improves spectral library generation ; the iDeepLC model that significantly improves peptide retention time prediction for modified peptides; and Prosit-XL, which accurately predicts fragment ion intensities for cross-linked peptides. These advancements have accelerated proteomics workflows, enabling more reliable and precise analyses and providing researchers with enhanced tools to uncover deeper insights into biological processes and disease mechanisms.
In Research Objective 2, computational advancements were made to improve mass spectrometry data analysis and expand the detection of novel proteoforms. Software tools were developed to address long-standing challenges in processing raw MS spectra, providing powerful new workflows for detecting hidden proteoforms. Furthermore, new open-search strategies and integrated scoring pipelines were introduced to help identify and quantify phosphorylation sites; and updated cross-linking search engines enabled more confident detection of protein–protein and protein–nucleic acid interactions.
In Research Objective 3, computational tools were developed to enhance multi-omics visualization and biological interpretation.A Perseus module integrated proteomic and fMRI data, enabling analysis of protein behavior in relation to brain activity. A circadian rhythm analysis toolkit was introduced; and the NuXL search engine was integrated into Proteome Discoverer, improving protein-nucleic acid complex analysis.Multi-omics data visualization was implemented in RDConnect, aiding rare disease diagnosis in 216 individuals. Network-based algorithms were developed to link proteomes to phenotypes, and a web-based game was created to teach protein interactions and drug mechanisms. A VR experience, "Seen the Unseen," was developed to illustrate molecular interactions, with further gamified tools in progress.
All PROTrEIN fellows presented their work at international conferences and meetings, and several manuscripts have been published, with many more in the pipeline. The whole consortium was involved in communication and outreach activities, such as social media campaigns, Wikipedia editathons , and the PROTrEIN art installation.
Innovation and entrepreneurship skills were also an important focus. PROTrEIN’s training program practical and theoretical training to help ESRs develop business ideas, participate in a pitching competition, and receive expert feedback on translating research into viable business ventures.
