{"doi":"10.17615/mqwj-8j03","title":"Volume Exclusion and Soft Interaction Effects on Protein Stability under Crowded Conditions","abstract":"Most proteins function in nature under crowded conditions, and crowding can change protein properties. Quantification of crowding effects, however, is difficult because solutions containing hundreds of grams per liter of macromolecules often interfere with observing the protein being studied. Models for macromolecular crowding tend to focus on the steric effects of crowders, neglecting potential chemical interactions between the crowder and the test protein. Here, we report the first systematic, quantitative, residue-level study of crowding effects on the equilibrium stability of a globular protein. We used a system comprising poly(vinylpyrrolidone)s (PVPs) of varying molecular weights as crowding agents and chymotrypsin inhibitor 2 (CI2) as a small globular test protein. Stability was quantified with NMR-detected amide 1H exchange. We analyze the data in terms of hard particle exclusion, confinement, and soft interactions. For all crowded conditions, nearly every observed residue experiences a stabilizing effect. The exceptions are residues where stabilities are unchanged. At a PVP concentration of 100 g/L, the data are consistent with theories of hard particle exclusion. At higher concentrations, the data are more consistent with confinement. The data show that the crowder also stabilizes the test protein by weakly binding its native state. We conclude that the role of native-state binding and other soft interactions need to be seriously considered when applying both theory and experiment to studies of macromolecular crowding.","journal":"Figshare","year":2020,"id":142164,"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":0.9543,"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":326172,"name":"Gary J. Pielak","orcid":"0000-0001-6307-542X","position":1,"is_corresponding":false},{"id":105100,"name":"Naima G. Sharaf","orcid":"0000-0002-3662-9228","position":2,"is_corresponding":false},{"id":520815,"name":"Conggang Li","orcid":"0000-0002-5798-1722","position":3,"is_corresponding":false},{"id":390723,"name":"Andrew C. Miklos","orcid":"0000-0002-1918-8352","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-18T23:17:31.424593Z","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":[]}