Real Biology, Actionable Data
Why Cellular Context Matters for RBP Target Engagement
Cellular target engagement data provide mechanistic evidence of whether compounds interact with their intended targets in living systems, supporting hit confirmation, series prioritization, and early optimization decisions. The value of target engagement data depends on using assay formats that match the target’s biology and interaction mode.
Many target engagement approaches measure isolated components or infer engagement indirectly. These approaches can be informative, but they may not reflect how targets behave in intact cells, where native context can influence interaction state and engagement readouts.
This challenge is often acute for RNA-binding proteins, where compound effects can arise from changes in the RNA–protein interaction state rather than from a single enzymatic activity or a stability shift.
Ribolytix addresses this by directly quantifying compound-induced changes in endogenous RNA–protein interactions in intact cells. The result is engagement-linked, mechanism-proximal data generated under native cellular conditions—without tags, overexpression systems, engineered reporters, or assumptions based on protein stabilization.
What Makes Our Approach Different
Many target engagement strategies rely on engineered systems or indirect proxies that can be informative, but may not reflect how RNA-binding proteins behave under native cellular conditions. In practice, this often includes reliance on one or more of the following:
Engineered cellular readouts (e.g., reporter constructs or non-endogenous expression) rather than endogenous targets
Tags, overexpression, or artificial constructs that can alter protein behavior relative to native context
Proxy readouts that infer engagement from downstream activity or stability shifts rather than directly measuring the interaction state
In contrast, the Ribolytix platform uses in-cell UV crosslinking to preserve native RNA–protein interactions and directly quantifies compound-dependent changes in endogenous RNA–protein interaction levels. Engagement can be measured for nominated targets (RBP-TE™) and, when needed, profiled at RBPome scale by quantitative mass spectrometry (RBP-SP™).
By directly interrogating RNA–protein complexes as they exist in living cells, this approach avoids dependence on engineered reporters, tags/overexpression, or stability-based assumptions. The result is engagement-linked, mechanism-proximal data that supports earlier, more confident decision-making in hit confirmation, selectivity assessment, and lead series prioritization.
RBP Selectivity Profiling
(RBP-SP™)
Broad, unbiased selectivity profiling across the RBPome
Label-free, mass-spectrometry–based measurement of cellular target engagement across the RNA-binding proteome. Resolves mechanism-relevant engagement patterns and identifies early selectivity liabilities to inform progression decisions.
RBP Target Engagement
(RBP-TE™)
Focused, quantitative assessment of cellular target engagement
Label-free, cellular target engagement assays that quantify engagement IC₅₀ values and time-dependent engagement kinetics for nominated RNA-binding protein targets to support medicinal chemistry optimization.
The Ribolytix platform at a glance
Native Biology
Measures target engagement in intact cells under native conditions, supporting translational relevance and reducing artifacts associated with cell-free or overexpression systems.
Label and tag-free
Quantifies native, endogenous targets without engineered tags, fluorescent labels, or protein overexpression that can distort biology and generate false positives.
No Stability Assumptions
Directly quantifies target engagement via RNA–protein interaction state rather than inferring binding from stability shifts, providing mechanism-coupled readouts relevant to RBP target biology.