Creative proteomics

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

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