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Kunold, E.

Publications and source records attributed to Kunold, E..

2 recordsLinked to original sources

Proteoform-level deconvolution reveals a broader spectrum of ibrutinib off-targets

Over the last decade, proteome-wide mapping of drug interactions has revealed that most targeted drugs bind to not only their intended targets, but additional proteins as well. However, the majority of these studies have focused on analyzing proteins as encoded by their genes, thus neglecting the fact that most proteins exist as dynamic populations of multiple proteoforms. Here, we addressed this problem by combining the use of thermal proteome profiling (TPP), a powerful method for proteome analysis, with proteoform detection to refine the target landscape of an approved drug, ibrutinib. We revealed that, in addition to known targets, ibrutinib exhibits an intricate network of interactions involving multiple different proteoforms. Notably, we discovered affinity for specific proteoforms that link ibrutinib to mechanisms in immunomodulation and cellular processes like Golgi trafficking, endosomal trafficking, and glycosylation. These insights provide a framework for interpreting clinically observed off-target and adverse events. More generally, our findings highlight the importance of proteoform-level deconvolution in understanding drug interactions and their functional impacts, and offer a critical perspective for drug mechanism studies and potential applications in precision medicine.

molecular biology↗

Deep thermal proteome profiling for detection of proteoforms and drug sensitivity biomarkers

The complexity of the functional proteome extends significantly beyond the protein coding genome resulting in millions of proteoforms. Investigation of proteoforms and their functional roles is important to understand cellular physiology and its deregulation in diseases, but challenging to perform systematically. Here, we apply thermal proteome profiling with deep peptide coverage to detect functional proteoforms in acute lymphoblastic leukemia cell lines with different cytogenetic aberrations. We detect 15,846 proteoforms, capturing differently spliced, post-translationally modified, and cleaved proteins expressed from 9,290 genes. We identify differential coaggregation of proteoform pairs and establish links to disease biology. Moreover, we systematically make use of measured biophysical proteoform states to find specific biomarkers of drug sensitivity. Our approach thus provides a powerful and unique tool for systematic detection and functional annotation of proteoforms.

biochemistry↗