Harvard researchers outline roadmap to solve orphan receptor challenge

A new review highlights how synthetic biology, AI, and spatial omics could transform ligand-receptor discovery from one-by-one searches into network-level mapping.

Cells communicate through secreted signaling proteins that regulate metabolism, immunity, development, and tissue repair. But for many of these molecules, scientists still do not know which receptors receive their signals - a long-standing problem that limits both basic biology and drug discovery.

In a review recently published in EXO – Beyond the Cell, researchers from Harvard Medical School present a roadmap for addressing this "orphan receptor" challenge. The study evaluates current deorphanization methods and outlines how next-generation technologies could transform ligand-receptor discovery from a slow, one-at-a-time process into scalable, network-level analysis.

The authors - Myeonghoon Han and Norbert Perrimon (Member of NAS, AAAS), - examined three major approaches currently used in the field.

Biochemical methods such as affinity purification-mass spectrometry (AP-MS) directly detect ligand-receptor interactions but often struggle to capture weak or transient extracellular binding events. Genetic screening platforms, including RNAi and CRISPR-based approaches, can provide physiological relevance or high-throughput scalability, yet they typically depend on measurable cellular phenotypes that are often unknown for orphan ligands. Computational tools such as AlphaFold-Multimer and AlphaFold3 have dramatically expanded large-scale interaction prediction, but current models remain limited in their ability to account for protein processing and post-translational modifications that influence real-world receptor binding.

Rather than advocating for any single strategy, the review argues that the field's future lies in integration. One major direction involves multiplexed screening platforms capable of testing entire ligand and receptor libraries simultaneously, enabling network-level discovery instead of one-pair-at-a-time identification.

The review also highlights emerging technologies designed to overcome one of the field's biggest technical barriers: weak and transient extracellular interactions. Approaches such as AVEXIS and covalent capture systems including SpyTag/SpyCatcher can stabilize short-lived binding events that are otherwise difficult to detect.

Among the most promising advances, the authors emphasize synthetic biology systems such as synNotch, JUPITER, and PAGER. Unlike traditional approaches that depend on binding strength, these systems record physical contact events themselves. Even brief ligand-receptor encounters can trigger durable fluorescent or genetic signals, helping researchers bypass long-standing challenges associated with low-affinity interactions and receptor internalization.

The review further argues that ligand-receptor discovery must be integrated with single-cell and spatial transcriptomics technologies to understand where signaling molecules are produced, which cells express their receptors, and how communication networks operate within native tissues. Tools such as CellPhoneDB, FlyPhoneDB2, MERFISH, and Slide-seq are increasingly enabling this systems-level view.

The authors conclude that future deorphanization efforts will likely combine biochemical stabilization, high-throughput screening, AI-based prediction, synthetic biology, and spatial omics approaches. Together, these technologies could substantially improve how researchers map the signaling networks that coordinate physiology across tissues and organs.