Revealing the Structural Fingerprints of Disease: Q&A with Faraz Choudhury

Why It Matters

Targeting disease‑specific conformations provides a path to more selective therapeutics, potentially reducing toxicity and improving success rates in drug development.

Key Takeaways

• Traditional discovery ignores protein structural changes.
• SPCs expose disease‑specific epitopes on cell surfaces.
• Immuto combines mass‑spec proteomics with AI for target mapping.
• Conformation‑selective antibodies improve safety and efficacy.
• Early AML program shows in‑vivo activity without hematopoietic toxicity.

Pulse Analysis

Most drug‑discovery pipelines still rely on genomics, transcriptomics, or bulk proteomics, which capture sequence mutations or expression levels but ignore how proteins fold under pathological stress. In oncology and other complex diseases, the same wild‑type protein can adopt a distinct three‑dimensional shape that creates novel surface epitopes. These disease‑specific surface protein conformations (SPCs) act as structural fingerprints, allowing researchers to differentiate malignant cells from healthy counterparts without a genetic alteration. Recognizing SPCs therefore opens a new dimension for target validation that traditional methods simply miss.

Immuto’s platform operationalizes this insight by interrogating the surfaceome of patient‑derived models in situ. High‑resolution mass spectrometry tags extracellular regions, generating a proteome‑wide map of conformational states. The resulting high‑dimensional dataset is fed into machine‑learning pipelines that flag statistically robust shape changes, rank them by disease prevalence, and predict three‑dimensional epitopes suitable for antibody binding. Once a target SPC is confirmed, Immuto engineers binders that lock onto the disease‑specific geometry while sparing the native form, streamlining the path from discovery to therapeutic candidate.

The strategic advantage of conformational selectivity is twofold: it widens the therapeutic window and reduces late‑stage attrition caused by off‑target toxicity. Early preclinical data from Immuto’s acute myeloid leukemia program demonstrate potent tumor engagement and negligible impact on healthy hematopoietic stem cells, a proof point that could translate into safer, more effective biologics. As the industry seeks to replenish pipelines with high‑value assets, integrating structural proteomics and AI promises to redefine target classes, accelerate timelines, and ultimately reshape the economics of drug development.