Hit deconvolution from phenotypic screens
Identify protein targets for small-molecule or peptide hits that show clear cellular activity but lack known binding partners.
Thermal Proteome Profiling (TPP) Service
When you need to move from "active phenotype" to concrete protein targets without redesigning your compounds, thermal proteome profiling is one of the few technologies that can keep the biology intact. Our TPP service combines cell-based thermal shift workflows with Orbitrap-based LC–MS/MS to map target engagement, off-targets, and MoA directly in cells, tissues, and lysates—without probes or affinity tags.
- Probe-free, proteome-wide target discovery – Identify on-targets and off-targets in native cellular and tissue matrices.
- Mechanism-of-action and pathway mapping – Link stability shifts to complexes, PTMs, and pathway-level rewiring.
- Flexible TPP modes for different questions – TPP-TR, TPP-CCR, ITSA, and PISA to balance depth, dose–response, and throughput.
- Validated LC–MS/MS platform and analysis – Orbitrap-class HRAM instruments, QC-anchored workflows, and decision-ready data packages.
What Is Thermal Proteome Profiling (TPP) and How Does It Work?
Thermal proteome profiling (TPP) is a proteome-wide thermal stability approach that links ligand binding to changes in protein solubility. By combining cell-based thermal shift workflows with quantitative LC–MS/MS, TPP reveals how compounds engage protein targets in native cellular and tissue environments.
Because TPP reads out protein state rather than only expression levels, it can uncover:
- Direct drug–target interactions
- Changes in protein–protein interactions and complexes
- Post-translational modifications that alter stability
- Pathway-level rewiring under compound treatment
TPP Technology Principles
As proteins are heated, they gradually unfold, expose hydrophobic regions, and aggregate. Each protein has a characteristic melting profile, often summarized by its melting temperature (Tm).
When a ligand binds, this profile can shift:
- Many proteins become more stable, with higher Tm
- Some become less stable, with lower Tm
In a TPP experiment, samples with and without compound treatment are challenged at one or more temperatures. After heating:
- Aggregated proteins are removed by centrifugation
- Remaining soluble proteins are digested and analyzed by LC–MS/MS
- Protein abundance is modeled as a function of temperature or compound concentration
By comparing treated versus control samples, TPP detects statistically significant stability shifts across the proteome and prioritizes candidate direct and indirect targets for follow-up.
Key Benefits of Thermal Proteome Profiling
Probe-free, label-free readout
Use compounds in their native form without affinity tags or bulky reporter groups.
Proteome-wide, unbiased profiling
Monitor thousands of proteins at once, capturing both expected and unexpected targets in a single dataset.
Direct and indirect effects in one experiment
In-cell and tissue experiments report direct binding, complex formation, and downstream signalling events in a unified framework.
Complementary to other omics
Focus on protein state and stability, adding a dimension that standard expression-based proteomics and transcriptomics cannot provide.
Technical Services
Service Scope
Method Comparison
Workflow
Platform
Sample Requirements
Deliverables
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When to Use Thermal Proteome Profiling
Mechanism-of-action mapping
Link compounds or natural products to upstream targets, downstream effectors, and pathway-level changes in cells or tissues.
Off-target and safety profiling
Detect proteins whose stability is altered beyond the intended target and flag potential safety or selectivity risks early.
Disease vs healthy comparisons
Compare thermal stability patterns between disease and control samples to reveal dysregulated proteins, complexes, and pathways.
Metabolic regulation and endogenous ligands
Study how endogenous metabolites or cofactors modulate enzyme stability and activity across the proteome.
Target engagement in relevant models
Confirm that tool compounds or development candidates engage their intended targets in the same matrices used for efficacy studies.
TPP Experimental Modes
We provide several TPP modes to match different project goals, throughput needs, and budgets.
Temperature-Range TPP (TPP-TR)
Use TPP-TR when you want full thermal profiles and robust ΔTm estimates.
- Multiple temperature points spanning the relevant denaturation range
- Melting curves fitted in compound and control conditions for each protein
- ΔTm and curve shape changes used to nominate candidate targets
TPP-TR is well-suited for in-depth target deconvolution, complex MoA work, or high-value compounds.
Compound-Concentration TPP (TPP-CCR)
Use TPP-CCR when dose–response information is critical.
- Samples treated with a concentration series of the compound
- Temperature fixed or varied in a limited range
- Concentration-dependent shifts in solubility used to estimate apparent binding potency
TPP-CCR is useful for ranking hits, comparing analogs, or approximating EC50-like metrics at the proteome level.
Isothermal Shift Assay (ITSA)
Use ITSA when you need higher throughput with reduced complexity.
- A single, carefully selected temperature in the melting transition region
- One point per sample, which reduces LC–MS/MS load
- Differential abundance at that temperature reveals stability changes between treated and control
ITSA is ideal for screening campaigns, early SAR support, or orthogonal validation of known targets.
Proteome Integral Solubility Alteration (PISA)
Use PISA when you want higher efficiency across multiple temperatures.
- Samples heated at multiple temperatures are combined before LC–MS/MS
- The combined signal approximates the integrated area under each protein's melting curve
- Compound-induced changes in integrated solubility provide a compact readout of stability shifts
PISA is well-suited for comparative studies across multiple compounds or conditions at moderate cost.
Choosing Between TPP and Related Target-Identification Technologies
| Criteria | Thermal Proteome Profiling (TPP) | Activity-Based Protein Profiling (ABPP) | Affinity Pull-Down / Chemical Proteomics | Crosslinking MS (XL-MS) | Cell-Based Thermal Shift (CETSA-like, WB) | Biophysical Binding Assays (MST / SPR / ITC) |
| Primary question | Which proteins change thermal stability upon compound treatment in cells/tissues? | Which active enzymes or nucleophiles are covalently labeled by my probe? | Which proteins bind to an immobilized/tagged compound in a given lysate or fraction? | Which proteins are in direct physical contact or close proximity in complexes? | Does my compound stabilize/destabilize this one specific protein in cells? | Does my compound bind this purified protein and with what affinity/kinetics? |
| Proteome coverage | Proteome-wide | Proteome-wide, but limited to probe-reactive proteins | Proteome-wide around the affinity matrix | Proteome-wide interaction network / complexes | Single or limited number of proteins | Single protein or small panel |
| Compound requirements | Native compound, no tag required | Needs reactive warhead + reporter/handle (probe design) | Needs immobilization or tag (biotin, handle, linker) | Often no modification to compound; crosslinker added to sample | Native compound, no tag required | Native compound; usually high purity and solubility |
| Readout type | Change in thermal stability / solubility of proteins | Covalent labeling of active targets by probe | Enrichment of binding partners on affinity matrix | Covalent crosslinks reporting distance restraints / contacts | Thermal stability shift of one protein (band intensity vs temperature) | Direct binding parameters (KD, kon/koff, thermodynamics) |
| Detects indirect / downstream effects | Yes, can capture downstream pathway changes and complex remodeling | Mostly direct reactive targets; some downstream changes if combined with expression data | Mostly direct binders and tightly associated complexes | Captures complexes and interaction topology, not downstream signalling per se | Mostly direct target engagement; indirect effects limited | No; limited to direct interaction with purified protein |
| Live cell / tissue compatibility | Yes (in-cell TPP) and lysates | Often yes (cell-permeable probes) | Mostly lysates; some live-cell variants | Yes, cells or lysates depending on protocol | Yes, live cells or lysates | No; requires purified protein in defined buffer |
| Throughput (relative) | Medium–high (depends on mode: TR / ITSA / PISA) | Medium–high (depends on probe set and LC–MS capacity) | Medium (per compound / bait) | Medium (complex sample prep and analysis) | Low–medium (per protein target) | Low–medium (one protein–ligand pair per run) |
| Best suited for | Probe-free target discovery, off-target mapping, MoA and pathway analysis | Mapping active-site targets of covalent drugs or reactive metabolites | High-confidence direct binders of a tagged compound, focused chemoproteomics | Defining protein–protein interaction networks and complex architecture | Validating thermal stabilization of a known target in its native context | Precise quantification of binding affinity and kinetics for defined targets |
| Main strengths | Label-free; works in cells/tissues; sees direct and indirect effects in one dataset | Direct readout of functional, active populations; excellent for covalent inhibitors | Strong evidence for direct binding; good for SAR around a chemical series | Structural/interaction insight; can validate or refine interaction models | Simple, relatively fast validation assay for one or a few targets | Gold standard for quantitative binding parameters and mechanism (on/off rates, thermodynamics) |
| Main limitations | Requires enough material and MS time; downstream effects can complicate direct vs indirect interpretation | Requires careful probe design; limited to proteins with suitable reactive residues | Requires compound tagging and optimization of linker chemistry and control experiments | Sample prep is complex; crosslink identification and analysis can be demanding | Not proteome-wide; needs high-quality antibodies or tags | No cellular context; does not report on target engagement or pathway effects in cells |
| When to choose instead of TPP | – | When you specifically want active-site covalent targets and are willing to design probes | When you have a single lead series and want high-confidence direct binders for that chemotype | When your primary question is which proteins interact with which, not primarily drug targets | When you already know the target and just need a fast, low-plex engagement assay | When you need exact KD/kinetics for a small number of protein–ligand pairs |
| When to combine with TPP | – | Use ABPP to validate direct covalent targets found by TPP or refine target classes | Use pull-down to confirm specific direct binders among TPP candidates | Use XL-MS to map complex architecture for interaction changes suggested by TPP | Use CETSA-like WB to orthogonally validate selected TPP hits at the single-protein level | Use MST/SPR/ITC to characterize binding of priority TPP targets in detail |
Thermal Proteome Profiling Workflow: From Sample to Targets
1
Study design and assay selection
- Define biological question, sample type, and compound modality
- Select TPP-TR, TPP-CCR, ITSA, or PISA and choose in-cell or lysate format
2
Sample preparation
- Prepare cells, tissues, microorganisms, or body fluids under non-denaturing conditions
- For lysates, use extraction buffers that preserve protein activity and complexes
3
Compound or metabolite incubation
- Incubate samples with test compound(s) or vehicle
- For metabolites or natural products, adjust conditions to mimic physiological exposure
4
Thermal challenge
- Apply a temperature series or a single diagnostic temperature
- Use controlled heating and rapid cooling to maintain soluble fractions
5
Separation of soluble and aggregated proteins
- Remove denatured proteins by high-speed centrifugation
- Collect supernatants containing the soluble protein fraction
6
Protein digestion and LC–MS/MS acquisition
- Digest soluble proteins (for example, with trypsin)
- Quantify peptides by high-resolution LC–MS/MS
7
Bioinformatics and target calling
- Normalize data and fit melting or dose–response models where appropriate
- Identify proteins with significant stability changes and rank candidates by effect size and consistency
TPP Instrumentation and Platform Capabilities
Mass spectrometers
- Primary platform: Thermo Scientific Orbitrap Q Exactive HF-X / Exploris 480 HRAM LC–MS/MS system (typical MS¹ resolution 60,000–120,000 at m/z 200; MS² 15,000–30,000).
- For projects requiring special designs, we can deploy equivalent Orbitrap-class instruments with comparable resolving power and sensitivity.
LC separation
- Nano-flow UHPLC systems (e.g., EASY-nLC 1200, UltiMate 3000 RSLCnano) with C18 columns (75 μm ID, 15–50 cm).
- Typical gradients of 60–120 min per run to balance depth, throughput, and TPP replicate design.
Performance metrics important for TPP
| Metric | Typical spec (representative) | Relevance for TPP |
| Mass accuracy | ~ ±3 ppm after calibration | Confident IDs and reliable stability shifts |
| Resolution (MS¹ / MS²) | 60k–120k / 15k–45k at m/z 200 | Separates close species, cleaner quant |
| Dynamic range | 4–5 orders of magnitude | Quantifies abundant and low-abundance targets |
| Quantification mode | LFQ, DIA, optional TMT multiplexing | Flexible designs for TR, CCR, ITSA, PISA |
| Technical reproducibility | Typical protein CVs <15–20% | Robust detection of real ΔTm / solubility changes |
| System QC | Routine QC runs for ID rate and RT stability | Demonstrates instrument stability per batch |
Q Exactive HF-X MS (Figure from Thermo)
Orbitrap Exploris 480 (Figure from Thermo)
Sample Submission Guidelines for TPP Analysis
To ensure robust thermal proteome profiling (TPP) data, please prepare and ship samples according to the guidelines below. Final amounts and design (temperature points, replicates, TPP mode) will be confirmed during project scoping.
| Sample type | Recommended amount* (per condition) | Format & buffer | Storage & shipping |
| Intact cultured cells (adherent or suspension) | ≥ 5–10 × 10⁶ cells per condition (before splitting into temperature points / replicates) | Cell pellets gently washed (e.g., PBS), no serum; minimal residual medium | Snap-frozen pellets on dry ice; store at −80 °C |
| Cell lysates for TPP | Lysate containing ≥ 2–3 mg total protein per condition | Non-denaturing lysis buffer (mild detergent or detergent-free), low–moderate salt; protease inhibitors | Aliquoted lysates on dry ice; store at −80 °C |
| Animal or human research tissues / biopsies | Typically 50–100 mg wet tissue per condition | Clean pieces, briefly rinsed if needed and blotted to remove excess buffer | Snap-frozen immediately in cryotubes or foil; ship on dry ice |
| Primary cells and organoids | ≥ 1–3 × 10⁶ cells or ≥ 50–100 organoids per condition | Pellets in PBS or appropriate isotonic buffer, no fixatives | Snap-frozen pellets on dry ice; store at −80 °C |
| Bacteria, yeast, fungi | Pellet from ≥ 50–100 mL mid-log culture (or equivalent biomass) | Washed pellets in PBS or isotonic buffer, no antibiotics in final wash | Snap-frozen pellets on dry ice; store at −80 °C |
| Blood-derived samples (plasma, serum, PBMCs) | Plasma / serum: ≥ 500 µL per condition; PBMCs: ≥ 5–10 × 10⁶ cells | Plasma / serum: clear, non-hemolysed aliquots; PBMCs: washed pellets in PBS | Freeze at −80 °C and ship on dry ice |
| Other matrices (cell-free extracts, purified complexes, etc.) | To be defined case-by-case | Mild, non-denaturing buffer with documented composition | Store at −80 °C; ship on dry ice |
*Exact amounts may vary with project design; we will confirm minimum input requirements during study planning.
Deliverables: Data Packages and Reports
- Raw LC–MS/MS data files in vendor format (and/or converted open formats on request).
- Processed protein and peptide quantification tables for all samples and temperature points.
- Lists of proteins with significant stability changes, including basic statistics (effect size, p-values or q-values).
- Quality control summary report, covering identification numbers, replicate consistency, and overall data performance.
Proteome-wide TPP stability shifts and melting curves.
Volcano plot of ΔTm vs –log10(q) with highlighted hits, plus example control vs treated melting curves.
Pathway-level interpretation of TPP stability changes.
Heatmap of protein stability shifts across doses and dot plot of enriched pathways defining compound MoA.
You May Want to Know
What types of compounds work best in thermal proteome profiling?
TPP works well for most small molecules, fragments, and many peptides as long as they are sufficiently soluble and can reach their targets in the chosen matrix (cells, lysates, or tissues). Affinity does not have to be ultra-high, but realistic exposure conditions matter: we usually aim for concentrations that are pharmacologically relevant yet compatible with cell health and solvent limits. For larger biologics, we focus on formats and incubation conditions that realistically reflect target engagement (for example, cell-surface or receptor-focused designs).
Can thermal proteome profiling detect membrane proteins and nuclear targets?
Yes, but coverage depends strongly on sample preparation. Standard TPP designs capture many cytosolic and nuclear proteins, and a subset of membrane proteins that are accessible under mild, non-denaturing lysis. If your main interest is membrane receptors, transporters, or multi-pass proteins, we can adapt the lysis buffer, extraction strategy, and LC–MS method to maximize representation while still preserving thermal behaviour, and we will be transparent about expected coverage for your target class.
How do you decide on temperatures, concentration points, and replicates in a TPP study?
Temperature and concentration design is driven by your biological question and material constraints. For TR-style experiments, we select a temperature range that includes clear pre- and post-transition regions plus several points in the melting region; for CCR-style designs, we balance the number of concentration points against the need for replicates. We typically simulate expected effect sizes and use pilot data or literature on similar systems to propose a design that gives interpretable curves without over-consuming sample or instrument time.
How robust are TPP hits, and how do you control false positives and false negatives?
Hit robustness in TPP comes from three layers: experimental design, quantitative quality, and statistics. We use biological or technical replicates, QC runs, and retention-time / identification-rate monitoring to ensure stable acquisition; then we apply models and thresholds that account for curve shape, effect size, and variability rather than single data points. Finally, we flag candidates by confidence tier and recommend orthogonal follow-up (e.g., CETSA-like Westerns, pull-down, or biophysical assays) for key decisions, helping you focus on the most reliable targets without over-interpreting borderline shifts.
When should I choose TPP instead of ABPP, pull-down, or biophysical binding assays?
TPP is most useful when you want probe-free, proteome-wide insight into how a compound reshapes protein stability in intact cells or tissues, including indirect network effects. If your main need is mapping covalent active-site targets with bespoke probes, ABPP is often better; if you already have a tagged bait and want only high-confidence direct binders for a specific chemotype, affinity pull-down may be more efficient; if you only need precise KD and kinetics for a single purified target, MST/SPR/ITC are more appropriate. Many clients use TPP for discovery and shortlisting, then layer ABPP, pull-down, or biophysical assays onto a reduced candidate list.
Can TPP be applied to primary tissues, patient-derived models, or limited material?
Yes, TPP can be adapted to primary tissues, organoids, and other precious samples, but the design often needs to be more focused. We may reduce the number of temperatures, concentrate on a single mode (for example, ITSA or a simplified TR panel), or restrict the number of treatment conditions to stay within realistic input amounts. During scoping, we will estimate feasible depth and coverage based on your available material and help you choose the most informative experiment that uses that material wisely.
How do you deal with compound solubility, stability, and DMSO tolerance in TPP?
Solubility and formulation are critical, because aggregation, precipitation, or excessive solvent can distort thermal responses. We typically define an acceptable solvent window (for example, a maximum DMSO percentage), then explore stock concentrations and dilutions that keep both solubility and cell viability in a safe range. If there are known stability issues (light sensitivity, rapid hydrolysis, strong protein binding in serum), we incorporate them into incubation times, temperature design, and control conditions so that observed thermal shifts truly reflect target engagement rather than compound artefacts.
Is thermal proteome profiling suitable for fragment-based or weak-affinity compounds?
TPP can support fragment or weak-affinity projects, especially when high local concentrations and favourable exposure conditions are achievable. In these cases, we usually favour modes that maximise sensitivity to subtle shifts (for example, carefully chosen temperatures, increased replicates, or lysate-based formats that remove permeability barriers). We set expectations clearly at design stage, and where necessary we recommend combining TPP with higher-sensitivity interaction assays for final validation.
Reference
- Gholizadeh, Elham, et al. " A new drug discovery approach based on thermal proteome profiling to develop more effective drugs." Middle East J Rehabil Health 8.2 (2021): 1-9.
