Singapore — Bruker Corporation has announced new timsUltra AIP and timsOmni workflows aimed at expanding functional proteomics capabilities for drug discovery, development and disease biology research.
The company unveiled the new workflows at the Human Proteome Organization World Congress 2026, highlighting advances in protein sequence coverage, targeted validation, glycopeptide characterization, structural proteomics and oligonucleotide analysis.
Bruker said a new multi-enzyme dia-PASEF workflow combines complementary protease digests with the timsUltra AIP ultra-high sensitivity mass spectrometer to increase protein sequence coverage. In Parkinson’s brain samples, the method generated about 350,000 peptides per sample and identified about 14,500 protein isoforms corresponding to more than 10,000 canonical proteins.
“Deep sequence coverage is central to understanding proteoform biology. By combining complementary protease digests with sensitive dia-PASEF, we can improve peptide coverage and gain a more confident and detailed view of isoforms and proteoforms that otherwise remain hidden,” said Nikolai Slavov, Founding Director of the Parallel Squared Technology Institute and Distinguished Professor of Biological Engineering at Northeastern University.
Bruker also introduced new ProteoScape workflows that connect discovery proteomics using PASEF methods with prm-PASEF targeted validation on the same timsTOF platform. The approach is designed to help researchers move more directly from discovery studies to targeted analysis of proteins, pathways and biomarkers.
“Together with Bruker, we have developed automated workflows that bridge discovery proteomics and targeted assays. By simplifying and accelerating method development, this enables more precise quantitation, helping translate complex proteomics data into actionable biological insights,” said Stanley Stevens Jr. of the University of South Florida.
The company also highlighted Spectronaut v21, which uses AI transfer learning to adapt analysis models to new mass spectrometry acquisition modes and instrument capabilities without requiring complete model redevelopment.
“New acquisition modes and instrument configurations now become available before large training datasets can be generated,” said Tejas Gandhi of Biognosys. “Spectronaut’s transfer-learning accelerates AI model adaptation quickly as new MS technologies and methods become available.”
Bruker is also advancing glycoproteomics with Guided PASEF EXciD, a timsOmni workflow designed for fast, selective electron-based fragmentation and mobility-resolved glycopeptide characterization.
“A major challenge in glycoproteomics is translating complementary peptide and glycan fragment information into confident, biologically meaningful insights. By combining intelligent trapped eXd with automated analysis in FragPipe, researchers can readily characterize site-specific glycosylation and glycan structural diversity in complex biological samples,” said Daniel Polasky, Assistant Professor in Pathology at the University of Michigan.
Bruker also announced a co-marketing and development agreement with Affipro Analytics for integrated hydrogen-deuterium exchange mass spectrometry workflows. The collaboration combines Affipro HDX-MS automation, Bruker HyStar control and Affipro DeutEx analysis software for studies of molecular interactions, protein conformation and structure.
“By combining Affipro’s workflow expertise with TIMS separation, we provide more structural information at higher throughput to accelerate AI-assisted drug discovery and structural biology,” said Petr Novak, co-founder of Affipro Analytics and Group Leader Structural Biology and Cell Signaling at the Institute of Microbiology of the Czech Academy of Sciences.
Bruker also reported advances in nucleic acid analysis using timsOmni, including electron detachment dissociation and Omnitrap MS3 workflows for RNA and DNA oligonucleotide characterization. The company said the methods can provide complete sequence coverage in certain oligonucleotide analyses and support native top-down studies of folded RNA structures.
“We are combining proteome depth, PTMs, proteoforms, protein interactions, and conformational and spatial context to enable richer multimodal training data for next-generation biological AI models,” said Frank H. Laukien, President and CEO of Bruker. “These complementary molecular dimensions can extend existing models for drug discovery and mechanisms of action with information closely linked to biological function, helping advance molecular medicine more rapidly in the post-genomic era.”
