Creative proteomics

05/28/2026

Permeability ≠ intracellular concentration. Two compounds with the same Caco-2 Papp can have wildly different accumulation inside cells — and that's the number that actually drives target engagement and pharmacology.

Creative Proteomics' Intracellular Accumulation MS service measures what permeability assays miss: the absolute, label-free concentration of your parent compound inside living cells, directly quantified by LC-MS/MS.

No fluorescent tags. No radioactivity. Just your compound as-is, rigorously washed to remove membrane-bound drug, then extracted and quantified by MRM with matrix-matched standard curves. Only parent compound detected — metabolites excluded.

Service modes: → Single time-point screening — rank up to 50 compounds by intracellular exposure → Multi time-point kinetics — Css, Tss, uptake/efflux rates → Concentration-dependent — apparent Km, Vmax, saturation → Custom models — primary cells, 3D spheroids, resistant lines

Critical for PROTACs, macrocycles, and bRo5 molecules where prediction fails and direct measurement is the only reliable option. Also essential for distinguishing efflux-mediated resistance from target mutations.

Validated by Gordon et al. (J Biomol Screen, 2016), demonstrating up to 100 compounds/day on RapidFire MS — and showing that similar permeability does not predict similar accumulation.

Explore the service: https://www.creative-proteomics.com/mass-target/intracellular-accumulation-ms.htm

05/28/2026

What metabolic pathways does your drug actually perturb? Not just which metabolites go up or down — but which pathways shift, and what that means for mechanism, off-target effects, and resistance.

Creative Proteomics' MassTarget™ Metabolic Pathway Drug-Response Mapping goes beyond standard metabolomics. Using high-resolution LC-MS with untargeted metabolomics, we detect 3,000–8,000 metabolic features per run and map hundreds of confidently annotated metabolites onto KEGG pathways via MetaboAnalyst enrichment. Experimental designs are customized to your question — dose-response, time-course, combination therapy, or resistance comparisons.

A published study (Metabolomics, 2025) applied this workflow to a β-lapachone derivative (WK0202) in human subjects, revealing pathway-level shifts in amino acid metabolism, arginine biosynthesis, and lipid remodeling linked to NQO1/Nrf2 activation.

Key applications: MoA studies, off-target screening, resistance mechanisms, synergy optimization, and pharmacodynamic biomarker discovery.

Every project includes raw LC-MS data, full statistical analysis (PCA, PLS-DA, volcano plots), and a publication-ready pathway enrichment report.

Explore the service: https://www.creative-proteomics.com/mass-target/metabolic-pathway-drug-response.htm

05/28/2026

Protein interactions that matter most are often the hardest to capture. Membrane complexes fall apart during lysis. Weak and transient binders wash out. Traditional pull-downs return abundant contaminants and miss the biology you came for.

Proximity labeling proteomics changes the equation.

By fusing a promiscuous biotin ligase (BioID, TurboID, miniTurbo) or peroxidase (APEX2) to your protein of interest, you tag neighboring proteins directly in living cells — before lysis, before purification, before the native context is lost. Streptavidin enrichment then pulls out the biotinylated interactome for LC-MS/MS identification.

Creative Proteomics supports multiple enzyme strategies: → TurboID / miniTurbo — rapid, broad labeling for comprehensive neighborhood mapping → BioID — slower, tighter radius for spatial precision → APEX2 — sub-minute labeling for compartment-specific studies → Drug-treated vs. control comparative analysis → Organelle, membrane, and signaling complex proximity mapping

A landmark study applied TurboID across the type I interferon pathway and identified 103 proximity interactors, including PJA2 — a novel negative regulator validated downstream. Interactions invisible to conventional methods.

https://www.creative-proteomics.com/mass-target/proximity-labeling.htm

05/28/2026

2D Thermal Proteome Profiling — Two Dimensions, One Clear Answer

Identifying a drug's true binding targets in living cells is one of the hardest challenges in early-stage drug discovery. Single-dimension thermal shift assays (1D-TPP) give you useful data—but they can't always distinguish a real binder from background noise.

2D-TPP changes that.

By combining a drug concentration gradient with a temperature gradient, 2D-TPP creates a two-dimensional matrix that reveals dose-dependent thermal stabilization. Real binders show a clear concentration–response relationship. False positives don't.

What this means for your research:

→ Test unmodified compounds directly—no probe synthesis required → Work in live cells under native physiological conditions → Profile thousands of proteins simultaneously with TMT-MS → Identify both on-target and off-target interactions with statistical confidence

A landmark study (Kurzawa et al., Nat Commun 2020) demonstrated this power by profiling the HDAC8 inhibitor PCI-34051. 2D-TPP confirmed HDAC8 binding and uncovered LAP3 as an unsuspected off-target—a finding that would have been missed by conventional approaches.

If you're in phenotypic screening, lead optimization, or drug repurposing, 2D-TPP gives you the resolution to make better decisions.

Explore the service: https://www.creative-proteomics.com/mass-target/2d-tpp.htm

05/19/2026

The ER Has a Secret to Keeping Its Redox Balance. It's a Transporter Called SLC33A1 — and Now We Know How It Works.

Here's a problem cell biologists have wondered about for years: the endoplasmic reticulum needs to be more oxidizing than the rest of the cell to fold proteins properly. But how does it get rid of the oxidized glutathione (GSSG) that builds up during protein folding?

A new study in Nature Cell Biology provides the answer.

Researchers developed a rapid method to isolate pure ER fractions — and used it to identify SLC33A1 as the transporter that exports GSSG out of the ER.

What this means:

🧬 ER redox balance is actively maintained. GSSG doesn't just diffuse out. SLC33A1 pumps it out, keeping the ER oxidizing enough for protein folding.

🔬 New method, new discoveries. The rapid ER immunoprecipitation strategy they developed is itself a breakthrough — enabling organelle-specific metabolomics at a resolution that wasn't possible before.

⚕️ Disease connections. SLC33A1 mutations cause Huppke-Brendel syndrome (a fatal metabolic disorder). And KEAP1-mutant lung cancers depend on SLC33A1 — making it a potential drug target.

A fundamental question in cell biology just got answered.

Full article: nature.com/articles/s41556-026-01929-5

We developed a rapid endoplasmic reticulum (ER) immunoprecipitation strategy to isolate ER fractions and, by using it, identified SLC33A1 as an ER transporter that exports oxidized glutathione. This finding provides insight into how the ER sets redox balance and provides a framework to define how ER...

05/19/2026

A TCA Cycle Metabolite Just Got a New Job: It Directly Controls Whether a Cell Makes DNA Building Blocks.

Here's a finding that changes how we think about metabolism and cell division.

Succinate — a molecule you probably know as a TCA cycle intermediate — turns out to directly control whether a cell can make pyrimidines, the building blocks of DNA and RNA.

A new study highlighted in Nature Metabolism shows that succinate binds and inhibits ATCase, the enzyme that starts the pyrimidine synthesis pathway. When succinate builds up, pyrimidine production drops. Cells can't make enough nucleotides. They can't enter S phase.

What this means:

🧬 Metabolism talks directly to the cell cycle. Not through energy charge or redox state — through a direct enzyme inhibition. Succinate is a signal, not just a fuel.

🔬 Time-lapse aspartate tracing uncovered it. The researchers tracked aspartate (the substrate of ATCase) over time and saw exactly when and how flux shifts when succinate accumulates.

⚕️ Relevance to cancer. SDH-deficient tumors accumulate succinate. This mechanism suggests they may be vulnerable to pyrimidine synthesis inhibitors — a potential therapeutic angle.

The metabolic network is also a regulatory network. Every intermediate carries information.

Full article: nature.com/articles/s42255-026-01523-x

Cell metabolism is a dynamic network of highly interconnected biochemical reactions. In this issue of Nature Metabolism, time-lapse analysis of the amino acid aspartate revealed an unexpected regulation of de novo pyrimidine biosynthesis by the tricarboxylic acid cycle metabolite succinate, with imp...

05/19/2026

An Activated T Cell Rewires Its Metabolism in Minutes. Are You Measuring What Fuels — or Fails — Your Immunotherapy?

Here's what immunotherapy developers are increasingly realizing: immune cell metabolism isn't just a bystander. It's the engine.

A T cell that can't switch to glycolysis won't proliferate. A macrophage stuck in the wrong metabolic state won't kill tumors. A CAR-T cell that runs out of metabolic fuel will exhaust.

Creative Proteomics' Immunometabolism MS Profiling service quantifies exactly this — the metabolic state of your immune cells, with absolute precision.

What we measure:

🧬 50+ immune-specific targets across 7 functional modules — checkpoint signaling, glycolysis, TCA cycle, amino acid regulation, redox balance, epigenetics, and lipid mediators.

🎯 Absolute quantification. Every target uses isotope-labeled internal standards. Not relative abundance — real concentrations.

🔬 Low-input validated. Works with

05/19/2026

Lipid Changes Happen Hours After Drug Exposure — Before Genes Even Respond. Here's How We Measure Them.

Here's something most drug discovery teams don't track: lipid remodeling.

It happens fast — within hours of drug exposure, well before transcriptional changes. It can reveal how a drug works, flag toxicity risks like phospholipidosis, and uncover resistance mechanisms that genomics alone misses.

Creative Proteomics' Cellular Lipidomics Drug Profiling service is built specifically for this.

What we cover:

🧬 500+ lipid species across 15+ classes. Glycerophospholipids, sphingolipids, sterols, glycerolipids, fatty acids, bioactive lipids — with isomer-level resolution.

🔬 Dual-column LC-MS/MS. HILIC separates by class. RP separates by species. Together they give you the full picture.

🎯 Seven analysis modes. Untargeted discovery, targeted quantification, toxicity screening, cancer vulnerability analysis, signaling lipid profiling, and more.

📊 Drug-tailored experimental design. Dose-response, time course, multiple replicates. Designed for discovery, not just description.

Real example: A 2025 study used this approach to show that FOLFOXIRI-resistant colorectal cancer cells share a common lipid remodeling program across four different cell lines — increased membrane saturation, altered ceramide signaling — that genomic analysis alone could not detect.

Minimum input: 1×10⁶ cells (micro-extraction). Turnaround: 4–6 weeks.

Learn more: creative-proteomics.com/mass-target/cellular-lipidomics-profiling.htm

05/19/2026

Your Drug Binds Its Target. But What's It Doing to the Rest of the Cell?

Here's a gap in early drug discovery: binding assays tell you the target is engaged. Cytotoxicity assays tell you the cells are alive or dead. But neither tells you what's happening to the cell's metabolism in between.

That's where cellular metabolomics screening comes in.

Creative Proteomics' service uses LC-MS/MS to profile drug-induced metabolic changes in live cells — without labels, without antibodies, without knowing what to look for in advance.

What we can do:

🧪 Untargeted profiling. Detect 2,000–5,000 metabolic features per run — discover unexpected metabolic effects you didn't design the experiment to find.

🎯 Targeted quantification. Absolute quant of 50–200 predefined metabolites using isotope-labeled internal standards — for validation and dose-response studies.

🔬 Any cell format. Adherent, suspension, primary cells, 3D spheroids, organoids — validated across 50+ cell types. Works with 96-well plates.

📊 Multi-omics integration. Pair metabolomics with transcriptomics, proteomics, or phosphoproteomics from the same system.

Real example: A 2019 study used this approach to show that polymer-encapsulated methotrexate produces a completely different metabolic fingerprint than free methotrexate — in both cancer cells and macrophages. Conventional cytotoxicity couldn't tell them apart. Metabolomics could.

Turnaround: 4–6 weeks. Minimum input: 5×10⁵ cells.

Learn more: creative-proteomics.com/mass-target/cellular-metabolomics-screening.htm

05/06/2026

Protein Abundance Didn't Change. But Something Structural Did. LiP-MS Sees It.

In drug discovery, one of the most frustrating outcomes is staring at a proteomics dataset where treated and control samples look identical — even when functional assays tell you something definitely happened. The protein is there. The mechanism is active. But conventional analysis shows no difference.

That's the gap Limited Proteolysis–Mass Spectrometry (LiP-MS) was designed to fill.

Here's how it works, simply: proteins in their native state have different surface regions exposed depending on whether they're bound to a compound, undergoing a conformational change, or interacting with a partner. A gentle protease treatment will cut these proteins differently depending on what's exposed. LiP-MS reads those cutting patterns and tells you which protein regions became more or less accessible after treatment — all at proteome scale.

Why this matters for real projects:

🧬 See structural changes, not just abundance changes. A protein can change conformation without changing concentration. LiP-MS catches what conventional proteomics misses.

🔬 No compound labeling needed. You don't need to chemically modify your small molecule to run LiP-MS. The readout comes from how the proteome responds, not from tracking the compound itself.

📊 Peptide-level evidence. LiP-MS output points toward specific protein regions that responded — giving you a map of where the structural effect occurred, not just a list of changed proteins.

🔄 Bridge to validation. LiP-MS results help you decide whether to pursue thermal-shift methods (TPP), higher-resolution structural analysis (HDX-MS), or chemoproteomics — with data guiding the choice.

At Creative Proteomics, our LiP-MS service handles everything from study design and native-state extraction through differential peptide analysis and decision-ready reporting. Your output includes peptide quantification tables, candidate protein prioritization, region mapping, and interpretation notes — not raw data you have to decode yourself.

Learn more: creative-proteomics.com/mass-target/lip-ms.htm