High-throughput testing of the specificity of protein-binding ligands has typically involved the use of protein microarrays. However, these arrays typically require that the multiple proteins be purified and surface immobilized, which has made the overall technique difficult to expand to a wide range of targets and overall costly. The present approach, dubbed PLATO (parallel analysis of translated open reading frames [ORFs]), tackles the issue by binding analysis of in vitro displayed full-length proteins whose identity is determined through high-throughput DNA sequencing of the corresponding mRNA.
Using ribosome display, the authors* prepared a library of proteins based on the human ORFeome consisting of 15,483 cDNAs. Through the processes of in vitro transcription and translation, the proteins were produced, while the corresponding mRNAs remained tethered to them through the ribosomes. The ribosome-displayed library was screened for binding to surface-captured ligands of interest; after appropriate washing and mRNA elution steps, the top binders were elucidated through sequencing (see Figure).
The overall process of ribosome display, affinity selection, and sample preparation for sequencing could be automated for high-throughput application. The first proof-of-concept experiments involved mapping the interactome for LYN kinase, identifying protein targets for antibodies from autoimmune disease patients, and finally, profiling gefitinib, a small molecule epidermal growth factor tyrosine kinase inhibitor, for interactions with additional targets.
While limitations of PLATO, such as inability to capture the entire proteome through the existing ORFeome libraries and potential complications associated with the spatial constraints posed by the ribosome display, are being discussed by the authors, it is expected that this new approach will have a following in the near future.
*Abstract from Nature Biotechnology 2013, Volume 31: 331–334
Identifying physical interactions between proteins and other molecules is a critical aspect of biological analysis. Here we describe PLATO, an in vitro method for mapping such interactions by affinity enrichment of a library of full-length open reading frames displayed on ribosomes, followed by massively parallel analysis using DNA sequencing. We demonstrate the broad utility of the method for human proteins by identifying known and previously unidentified interacting partners of LYN kinase, patient autoantibodies, and the small-molecules gefitinib and dasatinib.