Advances in ion mobility and fragmentation are helping researchers move beyond protein identification and abundance measurements to investigate how molecular structure affects biological function.
In an interview recorded at ASMS 2026, Rohan Thakur, president of TOFWERK, a Bruker company, discusses how multidimensional mass spectrometry could support this shift. He outlined the role of trapped ion mobility spectrometry, multimodal fragmentation, quantitative proteomics, and artificial intelligence in extracting actionable insights from complex biological samples.
Moving Toward Functional Proteomics
Proteomics workflows often focus on identifying proteins and measuring changes in abundance. However, protein function also depends on molecular structure, conformation, and interactions with other proteins.
Thakur describes this emerging research direction as “Functional Proteomics 2.0.” The approach combines structural information with conventional proteomic measurements to provide a clearer view of how proteins behave inside cells.
Systems that combine trapped ion mobility spectrometry with several fragmentation techniques can characterize complex molecules through complementary analytical measurements. Researchers can apply electron-induced dissociation, electron capture dissociation, and collision-induced dissociation to generate different types of structural information from the same analyte.
This capability could prove valuable for studying complex biotherapeutics, including multispecific antibodies. Detailed fragmentation data can help scientists examine molecular architecture and determine how structural differences influence function.
Using Ion Mobility to Characterize Molecular Shape
Ion mobility adds a gas-phase separation step between chromatography and mass analysis. It separates ions according to their movement through a gas, which reflects characteristics such as size, shape, and charge.
The resulting collisional cross section values provide reproducible measurements of molecular shape. Researchers can use these values to filter complex samples and isolate specific molecular forms before fragmentation.
This extra dimension can distinguish compounds that may share similar mass-to-charge ratios but differ in conformation. By targeting individual structures, scientists can connect molecular shape with fragmentation patterns and biological activity.
The workflow combines several stages of selectivity: liquid chromatography separates compounds in the liquid phase, ion mobility separates them in the gas phase, and tandem mass spectrometry fragments and detects the selected ions. Each stage reduces sample complexity and makes the remaining analytical problem easier to solve.
Linking Discovery With Quantitative Analysis
Thakur also highlights the need to connect broad discovery experiments with accurate quantitative measurements.
Data-independent acquisition methods such as dia-PASEF can identify molecular changes across complex samples. Researchers may then need targeted follow-up studies to determine the size and consistency of those changes.
For example, a discovery experiment may identify differences between healthy and cancerous cells. Subsequent quantitative workflows can measure how much a specific protein or molecular feature has changed across larger sample groups.
Automating the transition from discovery to quantification could support population-scale studies while improving consistency across experiments.
Improving Data Quality for Artificial Intelligence
Artificial intelligence will play a growing role in interpreting multidimensional mass spectrometry data, but Thakur emphasizes that useful AI results depend on high-quality analytical inputs.
Ion mobility and additional separation stages may not always produce more data. Instead, they can produce cleaner, more selective data that computational models can interpret with greater confidence.
Human expertise remains central to the process. Algorithms can detect patterns and generate possible answers, but scientists must assess whether those results make biological and experimental sense.
By combining multidimensional separations, structural measurements, quantitative workflows, and expert interpretation, mass spectrometry could provide a more complete view of how protein structure drives function.
