In a groundbreaking development for the field of artificial intelligence (AI), researchers at Harvard Medical School have unveiled a new tool called PINNACLE that promises to revolutionize the analysis of proteins. Published in Nature Methods, the study led by Marinka Zitnik, assistant professor of biomedical informatics at Harvard Medical School, introduces a novel approach that considers the contextual nuances of protein behavior within specific tissues and cells.
Current AI models often analyze proteins in isolation, disregarding the intricate interactions and variations that occur within different cellular and tissue contexts. PINNACLE, however, recognizes the significance of these contextual factors, enabling a more comprehensive understanding of protein function and malfunction.
Proteins, composed of twenty different amino acids, are essential for various biological functions in the human body. They interact not only with each other but also with other molecules like DNA and RNA, forming complex networks of protein interactions. PINNACLE’s unique advantage lies in its ability to identify how proteins behave differently in distinct cell and tissue types. By decoding these variations, the tool can predict precise drug targets for malfunctioning proteins, potentially leading to more effective and tailored therapies.
PINNACLE complements existing single-representation models by analyzing protein interactions within diverse cellular contexts. This capability allows researchers to gain deeper insights into protein function, cellular processes, and disease mechanisms. Moreover, the tool can aid in identifying potential drug targets and predicting the effects of different medications in specific cell types.
The development of PINNACLE comes at a time when the optimization of the drug discovery process is crucial. Bringing a new drug to market can take up to 15 years and cost billions of dollars, with a high failure rate. By streamlining the identification of drug targets, PINNACLE has the potential to significantly enhance the efficiency of drug development.
The researchers trained PINNACLE using human cell data from a comprehensive multiorgan atlas, incorporating multiple networks of protein-protein interactions, cell type-to-cell type interactions, and tissues. The tool has already generated nearly 395,000 multidimensional protein representations, surpassing the limited capabilities of current models.
While the current version of PINNACLE covers 156 cell types and 62 tissues and organs, the researchers plan to expand its cellular repertoire by incorporating data from millions of cells sampled from the entire human body. This expansion will further enhance the tool’s ability to analyze protein behavior across various contexts.