Automatic assignment of metal-containing peptides in proteomic LC-MS and MS/MS data sets

Abstract

Transition metal-containing proteins and enzymes are critical for the maintenance of cellular function and metal-based (metallo)drugs are commonly used for the treatment of many diseases, such as cancer. Detection and characterisation of metallodrug targets is crucial for improving drug-design and therapeutic efficacy. Due to the unique isotopic ratios of many metal species, and the complexity of proteomic samples, standard MS data analysis of these species is unsuitable for accurate assignment. Herein a new method for differentiating metal-containing species within complex LCMS data is presented based upon the Smart Numerical Annotation Procedure (SNAP). SNAP-LC accounts for the change in isotopic envelopes for analytes containing non-standard species, such as metals, and will accurately identify, record, and display the particular spectra within extended LCMS runs that contain target species, and produce accurate lists of matched peaks, greatly assisting the identification and assignment of modified species and tailored to the metals of interest. Analysis of metallated species obtained from tryptic digests of common blood proteins after reactions with three candidate metallodrugs is presented as proof-of-concept examples and demonstrates the effectiveness of SNAP-LC for the fast and accurate elucidation of metallodrug targets.