{"doi":"10.17760/d20621548","title":"Development of improved drug-target profiling methods using mass spectrometry-based thermal stability assays","abstract":"Most drug candidates in the development pipeline fail during Phase II clinical trials because of inefficacy or unacceptable safety profiles. The costly financial burden of failed late-stage drug candidates may be transferred to the few drugs that successfully navigate the approval process. The efficient discovery and development of therapeutic drugs require deep profiling of interactions between drug candidates and their biological targets for gaining a critical understanding of therapeutic mechanisms while limiting unwanted binding to other (off-target) proteins, which can lead to adverse reactions or toxic effects. Thermal proteome profiling (TPP) and the mass spectrometry-based cellular thermal shift assay (CETSA MS) are adaptations of the CETSA technique, which exploit the phenomenon of ligand-induced thermal stabilization of proteins. Collectively referred to as mass spectrometry-based thermal stability assays (MS-TSA), they have refined the process of drug target profiling. While the rapidly evolving MS-TSA techniques have provided remarkable insights into the drug-protein interactome, challenges remain, particularly in obtaining melting curves from low-abundance and poorly soluble proteins. The objective of this dissertation is to innovate the conventional MS-TSA approaches with novel combinations of MS-enabling technologies for enhanced performance. We specifically focused on improving the characterization of melting profiles for proteins that are low in abundance and poorly soluble. Chapter 1 presents a historical overview on the tools that preceded current drug-target profiling techniques, which provides context and insight about the modern drug discovery setting. A thorough review discussing the evolution of MS-TSA approaches and their impact on pharmaceutical research is also included in Chapter 1. Chapters 2 and 3 assess the integration of MS-enabling technologies with the current MS-TSA tequnique. In Chapter 2, we introduced the improved MS-based acquisition approaches for thermal stability assays (iMAATSA), which combine several MS-enabling technologies. The novel combination of technologies demonstrated a synergistic effect on the MS-TSA performance by increased protein identifications and high-quality protein melting curves using a model biological system. Aspects of iMAATSA were further developed in Chapter 3, where the membrane-enriched stable isotope isobaric-labeled carrier channel (meSIILCC) approach was introduced and demonstrated improved detection of membrane proteins in MS-TSA. After testing four membrane protein-enrichment protocols, a commercially available kit was selected to improve the performance of the meSIILCC workflow. A separate DMSO-only control MS-TSA experiment using the optimized meSIILCC was conducted. A significant increase in the number of identified unique and quantified peptides per protein for proteins annotated with \"plasma membrane\" was demonstrated using the meSIILCC approach. Also, the acquired results identified unsuitable isobaric tag channels for the meSIILCC approach due to isotope interference. In the final Chapter, we focus on how MS-TSA could be utilized in the future and highlight aspects that need to be further developed. --Author's abstract","journal":null,"year":2023,"id":415704,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9531,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1079051,"name":"Clifford G. Phaneuf","orcid":"0000-0001-5015-6212","position":0,"is_corresponding":true}],"reference_count":178,"raw_metadata":null,"created_at":"2026-07-19T01:22:15.958504Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}