qLILBID-MS: Quantitative Protein Interaction Analysis

• qLILBID-MS is a laser-induced mass spectrometry technique that quantifies noncovalent protein–protein interaction affinities using liquid bead microdroplets.
• The method relies on calibrated laser-induced dissociation to accurately determine equilibrium dissociation constants (K_D) even for weak interactions.
• qLILBID-MS offers rapid analysis with low sample requirements, making it ideal for high-throughput drug discovery and mechanistic studies.

Quantitative Laser-Induced Liquid Bead Ion Desorption Mass Spectrometry (qLILBID-MS) is a modern analytical technique employed for the determination of noncovalent protein–protein interaction affinities, with particular emphasis on homodimeric complexes. It operates by correlating the extent of laser-induced dissociation of biomolecular complexes within liquid microbeads to their equilibrium concentrations, enabling direct quantification of dissociation constants ($K_D$) with minimal sample requirements and rapid experimental throughput. The methodology is particularly suitable for investigating dynamic protein–protein interfaces, screening small-molecule modulators, and quantifying interaction strengths in drug discovery workflows.

1. Principle of qLILBID-MS

qLILBID-MS relies on generating microdroplets of an aqueous biomolecular solution, transferring these droplets into vacuum, and irradiating them with an infrared (IR) laser pulse. The absorbed laser energy causes explosive expansion of the droplet—quantified as the “explosion width” (ew)—reflecting the magnitude of energy transferred to the sample. This process simultaneously ionizes the constituent biomolecules and induces partial dissociation of noncovalent complexes.

The mass spectra collected after laser irradiation capture the abundance of monomer and dimer ions, which jointly reflect both the solution-phase equilibrium and any additional laser-induced breakdown. To correct for laser-induced dissociation and assess the true equilibrium ratio, qLILBID-MS measures $I'_D,\text{LILBID}$:

$$I'_D,\text{LILBID} = \frac{\int\text{monomer peaks}}{\int\text{monomer} + \text{dimer peaks}}$$

This observed ion ratio is then calibrated using standard reference complexes (with known $K_D$) to yield the solution-phase dissociation ratio $I'_D,\text{solution}$, correcting for laser effects via a calibration factor $k_{ew}$ determined at a standard explosion width (e.g., $ew = 1100\,\mu$m):

$$\ln(I'_D,\text{solution}) = \ln(I'_D,\text{LILBID}) + \ln(k_{ew})$$

2. Methodological Workflow and Quantitative Analysis

For accurate $K_D$ determination, the workflow comprises:

1. Microdroplet generation from a buffered solution containing the proteins of interest.
2. Transfer into high vacuum and irradiation with a controlled IR laser pulse.
3. Simultaneous recording of mass spectra and droplet explosion width to map energy input and dissociation.
4. Quantitative extraction of monomer and dimer peak integrals from the spectra.
5. Calibration using reference complexes and the standardized explosion width.

For homodimer equilibrium ($D \rightleftharpoons 2M$), the dissociation constant is:

$K_D = \frac{[M]^2}{[D]}$

The solution-phase dissociation ratio,

$I'_D,\text{solution} = \frac{n(M)}{n(M) + n(D)}$

is related to the total concentration ($C_\text{total} = [M] + 2[D]$), and the final corrected expression for the dissociation constant is:

$$K_D = \frac{2\,C_\text{total}\,(1 - I'_D,\text{solution})^2}{1 - 2\,I'_D,\text{solution}}$$

(See equations (1), (2), and (4b/S16) in (Schulte et al., 9 Oct 2025).)

Resolving signal overlap is critical for homooligomeric studies. qLILBID-MS employs dilution to shift equilibrium, or covalent crosslinking to lock the dimeric state and separate charge state distributions, avoiding mass/charge ambiguities inherent to native mass spectrometry.

3. Sensitivity, Sample Requirements, and Scalability

qLILBID-MS achieves high sensitivity, detecting protein complexes with sample amounts measured in hundreds of picomoles—orders of magnitude lower than required for isothermal titration calorimetry (ITC), which typically demands milligrams of protein. The method yields reliable $K_D$ values in the high micromolar range, capturing previously inaccessible affinities, and supports rapid, scalable analysis due to its ability to directly determine equilibrium states from single samples and rapidly acquire spectra across a range of laser energies.

Minimal sample preparation and no need for labeling lower both operational complexity and cost. These attributes position qLILBID-MS as a cost-effective method for affinity quantification, especially in high-throughput screening workflows.

4. Analytical Performance and Comparative Advantages

The accuracy of qLILBID-MS has been validated through case studies. For Bovine Serum Albumin (BSA) homodimers, qLILBID-MS yielded $K_D$ measurements (9 ± 3 µM via crosslinking, 11 ± 4 µM via dilution) consistent with orthogonal literature values. The method’s suitability extends to weak interactions—quantifying affinities of Tryparedoxin (Tpx) homodimers induced by molecular glues, with $K_D$ ranging from 5 ± 4 µM up to 370 ± 110 µM—even where ITC fails for very weak binding.

Unlike techniques such as ITC, which can struggle with overlapping species or low-affinity interactions, qLILBID-MS distinguishes monomer/dimer contributions even in homooligomeric systems by manipulating equilibrium concentrations or covalently stabilizing complexes. Typical limitations of competing techniques—in sample consumption, matrix complexity, and requirement for signal labeling—are circumvented.

Technique	Sample Requirement	Accessible Affinity Range
qLILBID-MS	~hundreds of pmol	High nM – high µM (sensitive)
Isothermal Titration Calorimetry (ITC)	mg-scale protein	Down to low µM (limited by weak binding)

5. Applications to Drug Discovery Workflows

qLILBID-MS enables direct and quantitative monitoring of protein–protein interaction affinities central to drug discovery and design of proximity-inducing molecules (e.g., molecular glues, PROTACs). The approach is well suited for SAR studies, enabling screening of ligand libraries and detection of incremental changes in $K_D$ due to point mutations or chemical modifications. Its rapid acquisition and low sample demand make it an integral tool for early-stage workflows, prioritizing candidates that modulate homodimeric assemblies.

Real-world applications include tracking mutation-induced affinity changes at protein interfaces and profiling the influence of diverse molecular glues on dimer stability, with demonstrated robustness across a broad affinity spectrum.

6. Comparison with Related Laser-Based Mass Spectrometry Techniques

While both qLILBID-MS and Laser Desorption/Ionization Mass Spectrometry (LD-MS) employ laser energy for analyte ionization, their operational regimes differ. LD-MS is optimized for solid samples and excels in life-detection technologies for planetary exploration due to its robustness, in situ applicability, and ultra-low detection limits (picomol–femtomol mm⁻²), as illustrated by its implementation in the Mars Organic Molecule Analyzer (MOMA) and ORIGIN platforms (Ligterink et al., 2020).

In contrast, qLILBID-MS specializes in quantitative analysis within liquid environments, capitalizing on droplet-based sample handling. Sensitivity in qLILBID-MS is linked to preserving liquid bead conditions, and although highly promising for laboratory-based quantification, its field robustness and in situ reliability are under active development.

Method	Sample State	Main Application	Sensitivity/Accuracy
qLILBID-MS	Liquid bead	Laboratory quantification	~High (µM–nM K_D)
LD-MS	Solid	Planetary exploration	Picomol–femtomol

A plausible implication is that qLILBID-MS is likely to become increasingly prevalent in bioanalytical and pharmacological contexts where precise, low-sample quantification is required, particularly as field-deployable droplet-based strategies mature.

7. Limitations and Outlook

qLILBID-MS is robust and versatile within controlled laboratory settings. Its capacity to disentangle overlapping charge state distributions through sample dilution and covalent crosslinking extends its utility to challenging homooligomeric systems. However, current limitations pertain to its sensitivity dependencies on droplet environment preservation and its ongoing field qualification for in situ deployment. Comparative reliability with mature in situ LD-MS systems remains an active research topic.

Continued methodological refinement, calibration against well-characterized complexes, and integration into high-throughput pipelines are required to further establish qLILBID-MS as a standard affinity quantification tool. Its demonstrated performance in quantifying previously inaccessible weak affinities, coupled with compatibility with minimal sample volumes and complex backgrounds, underscores its potential impact on mechanistic molecular biology and drug discovery.