{"doi":"10.3390/biom10010121","title":"Protein Backbone and Average Particle Dynamics in Reconstituted Discoidal and Spherical HDL Probed by Hydrogen Deuterium Exchange and Elastic Incoherent Neutron Scattering","abstract":"Lipoproteins are supramolecular assemblies of proteins and lipids with dynamic characteristics critically linked to their biological functions as plasma lipid transporters and lipid exchangers. Among them, spherical high-density lipoproteins are the most abundant forms of high-density lipoprotein (HDL) in human plasma, active participants in reverse cholesterol transport, and associated with reduced development of atherosclerosis. Here, we employed elastic incoherent neutron scattering (EINS) and hydrogen-deuterium exchange mass spectrometry (HDX-MS) to determine the average particle dynamics and protein backbone local mobility of physiologically competent discoidal and spherical HDL particles reconstituted with human apolipoprotein A-I (apoA-I). Our EINS measurements indicated that discoidal HDL was more dynamic than spherical HDL at ambient temperatures, in agreement with their lipid-protein composition. Combining small-angle neutron scattering (SANS) with contrast variation and MS cross-linking, we showed earlier that the most likely organization of the three apolipoprotein A-I (apoA-I) chains in spherical HDL is a combination of a hairpin monomer and a helical antiparallel dimer. Here, we corroborated those findings with kinetic studies, employing hydrogen-deuterium exchange mass spectrometry (HDX-MS). Many overlapping apoA-I digested peptides exhibited bimodal HDX kinetics behavior, suggesting that apoA-I regions with the same amino acid composition located on different apoA-I chains had different conformations and/or interaction environments.","journal":"Biomolecules","year":2020,"id":115495,"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":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9629,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":541082,"name":"Judith Peters","orcid":"0000-0001-5151-7710","position":1,"is_corresponding":false},{"id":542086,"name":"Gary S. Gerstenecker","orcid":null,"position":2,"is_corresponding":false},{"id":541083,"name":"Celalettin Topbaş","orcid":"0000-0003-2406-1070","position":3,"is_corresponding":false},{"id":541084,"name":"Liming Hou","orcid":"0000-0002-4551-5636","position":4,"is_corresponding":false},{"id":542087,"name":"J. Combet","orcid":null,"position":5,"is_corresponding":false},{"id":108894,"name":"Joseph A. DiDonato","orcid":"0000-0002-1641-1758","position":6,"is_corresponding":false},{"id":262182,"name":"Jonathan D. Smith","orcid":"0000-0002-0415-386X","position":7,"is_corresponding":false},{"id":541085,"name":"Kerry‐Anne Rye","orcid":"0000-0002-9751-917X","position":8,"is_corresponding":false},{"id":108895,"name":"Stanley L. Hazen","orcid":"0000-0001-7124-6639","position":9,"is_corresponding":false},{"id":261939,"name":"Valentin Gogonea","orcid":"0000-0002-6154-8497","position":0,"is_corresponding":true}],"reference_count":74,"raw_metadata":null,"created_at":"2026-07-18T23:13:36.820928Z","pmid":"31936876","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":[]}