Disease Mechanism and Pathway Analysis Service

Your team has identified a compound of interest, a disease-relevant mutation, or a phenotypic hit — and now the real question emerges: how does it work? What cellular pathways does it engage? Is the observed phenotype driven by target engagement, signaling modulation, metabolic reprogramming, or a combination of these?

Answering these questions is the central challenge of preclinical drug discovery. Yet the complexity of disease mechanisms means that no single analytical readout can capture the full picture. A compound that inhibits a kinase may produce no change in that kinase's protein abundance — its effect is on phosphorylation state, not expression level. A metabolic shift observed in a disease model might be a primary driver or a secondary consequence of broader pathway dysregulation. Distinguishing cause from effect requires layered evidence from multiple experimental dimensions.

The MassTarget platform is designed specifically for this challenge. Rather than offering a single assay or omics modality, we integrate seven complementary categories of MS-based services — spanning target engagement, signaling analysis, metabolic profiling, chemical proteomics, ADME characterization, multi-omics integration, and high-throughput screening — into a coordinated disease mechanism analysis workflow. This enables your team to build a complete mechanistic picture from a single project engagement, with each layer providing orthogonal evidence that strengthens the conclusions drawn from the others.

Disease mechanism analysis in drug discovery typically progresses through a hierarchy of questions, each requiring a different analytical approach. The MassTarget platform addresses them systematically:

Target Engagement Level. Is the compound engaging its intended target in the disease-relevant cellular context? Which proteins does it bind beyond the primary target? Questions at this level are answered through affinity-based approaches — affinity selection MS (AS-MS), equilibrium dialysis–MS binding, and native ESI-MS for noncovalent complexes — combined with cellular thermal stability profiling such as thermal proteome profiling (TPP) and 2D-TPP, which report target engagement and off-target binding directly in live cells without requiring compound modification.

Signaling and PTM Level. Once target engagement is confirmed, the next question is which signaling pathways are modulated. Protein abundance changes alone rarely reveal pathway activation. Phosphoproteomics activation mapping captures phosphorylation events across thousands of sites, identifying kinase cascades and network-level signaling changes. Ubiquitinomics, acetylomics, and other PTM-focused analyses further refine the view.

Metabolic and Functional Level. What are the functional consequences of pathway modulation? Untargeted and targeted metabolomics capture the metabolic state of treated cells or tissue — shifts in energy metabolism, lipid homeostasis, nucleotide biosynthesis, and oxidative stress markers. Our untargeted metabolomics for MoA service provides a direct functional readout that complements proteomic and signaling data.

Chemical and Covalent Level. For covalent inhibitors, natural products, and probes that bind through reactive chemistry, understanding which residues are modified and which proteins are engaged requires dedicated chemical proteomic approaches. Activity-based protein profiling (ABPP), reactive residue profiling (Cys/Lys/Tyr/Ser), and photoaffinity labelling (PAL-MS) identify direct protein targets and modification sites with residue-level resolution.

ADME and Metabolite Level. Understanding the metabolic fate of a compound is essential for interpreting disease mechanism data. Our ADME/DMPK research platforms cover metabolic stability, metabolite identification (MetID), and drug permeability profiling, providing the pharmacokinetic context for mechanism-of-action studies.

The MassTarget platform organizes its disease mechanism analysis capabilities into seven service categories. Each category contains multiple individual service modules that can be selected, combined, or sequenced according to your specific research question.

When multiple omics datasets are generated from the same sample set, our seventh category — Multi-Omics Integration and Systems Analysis — correlates proteomic, phosphoproteomic, metabolomic, and lipidomic changes into unified pathway maps, adding a systems-level dimension to mechanism interpretation.

Selecting the right combination of analytical modules is the first step in designing an effective disease mechanism study. The table below maps common research questions to the most appropriate MassTarget service modules.

Sample requirements vary depending on the selected service modules. The following table provides general guidelines for the most common sample types.

Note: For multi-modality projects combining target engagement, omics, and ADME analyses, sample requirements may vary. We provide a detailed intake checklist after the initial scoping consultation.

Each project delivers module-level outputs tailored to the selected services, plus a comprehensive integration report. Standard deliverables include:

1. Module-level QC reports — Performance metrics for each service module: protein identification depth, phosphosite localization confidence, metabolite annotation rate, thermal stability curve quality, binding assay reproducibility.
2. Differential expression and binding tables — For each omics modality: fold changes, p-values, FDR. For binding modules: binding curves, affinity estimates, target lists with confidence scores.
3. Pathway enrichment — KEGG, Reactome, GO, and WikiPathways enrichment analyses for each dataset, with cross-module comparison of enriched pathways.
4. Integrated pathway map — Unified visualization of dysregulated pathways with annotations showing which module(s) contributed each piece of evidence.
5. Written biological interpretation — A project-specific narrative connecting the experimental findings to your original research question, with prioritized pathway nodes and candidate follow-up targets.

Not every disease mechanism project requires all seven service categories. The right strategy depends on your project stage, compound modality, and the specific research questions you need to answer:

Hit-to-lead stage. If your priority is establishing that a compound engages its intended target and understanding the basic mechanism, start with target engagement (AS-MS or TPP) and global proteomics. Add phosphoproteomics if the target is a kinase or signaling protein.

Lead optimization stage. At this stage, off-target liability and metabolic stability become critical. Add chemical proteomics (ABPP or PAL-MS) for off-target profiling and ADME modules (metabolic stability, MetID) for PK characterization.

Natural products or phenotypic hits. If the target is unknown, begin with chemical proteomics (ABPP, PAL-MS, or reactive residue profiling) and untargeted metabolomics with GNPS molecular networking for mechanism deconvolution.

Late-stage candidate characterization. For compounds nearing preclinical nomination, a full multi-modal assessment combining target engagement, signaling, metabolic, chemical proteomic, and ADME modules provides the comprehensive evidence package needed for candidate selection decisions.

We will work with your team to design the optimal module combination and provide a detailed project proposal before any work begins.