{"doi":"10.1073/pnas.1620646114","title":"Bacterial proteostasis balances energy and chaperone utilization efficiently","abstract":"<jats:title>Significance</jats:title>\n          <jats:p>A cell’s proteins must be properly folded. Therefore, cells have chaperones that help other proteins, their clients, fold and not aggregate. The machinery is like a hospital: it assesses the “sickness” of the patient (finds improperly folded proteins), sends the patient to the right doctor (sorts the protein to the right chaperone), and cures the disease (folds or disaggregates the protein). How are sick proteins recognized and routed to the right chaperone? How does the machine handle different growth rates? Here, we model proteostasis. We find that it can handle any arbitrary client protein, that it spends the least energy on least sick proteins, and that the cell produces just enough chaperone to keep the proteome folded but no more.</jats:p>","journal":"Proceedings of the National Academy of Sciences","year":2017,"id":22548,"datarank":2.088803205296355,"base_score":4.276666119016055,"endowment":4.276666119016055,"self_citation_contribution":0.6414999178524083,"citation_network_contribution":1.4473032874439467,"self_endowment_contribution":0.6414999178524083,"citer_contribution":1.4473032874439467,"corpus_percentile":null,"corpus_rank":null,"citation_count":71,"citer_count":64,"citers_with_citation_signal":52,"citers_with_endowment":52,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":141414,"name":"Daniel W. Farrell","orcid":null,"position":1,"is_corresponding":false},{"id":141415,"name":"Ken A. Dill","orcid":null,"position":2,"is_corresponding":false},{"id":141413,"name":"Mantu Santra","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"base_score":4.276666119016055,"endowment":4.276666119016055,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"28292901","pmcid":"PMC5380058","openalex_id":"https://openalex.org/W2596147899","authors":[],"funders":[{"funder_name":"National Science Foundation","grant_id":"1205881","title":"Collaborative Research: Maximum Caliber: An Approach to Modeling Stochastic Dynamics in Biology."}],"total_grants":1,"fwci":3.1396,"citation_percentile":0.9242276,"influential_citations":3,"citation_trend":[{"year":2017,"count":6},{"year":2018,"count":7},{"year":2019,"count":9},{"year":2020,"count":6},{"year":2021,"count":10},{"year":2022,"count":11},{"year":2023,"count":8},{"year":2024,"count":7},{"year":2025,"count":4},{"year":2026,"count":3}],"oa_status":"bronze","license":"http://www.pnas.org/site/misc/userlicense.xhtml","oa_locations":[{"url":"https://www.pnas.org/content/pnas/114/13/E2654.full.pdf","host_type":"journal"},{"url":"https://www.pnas.org/content/pnas/114/13/E2654.full.pdf","host_type":"BRONZE"},{"url":"https://www.pnas.org/content/pnas/114/13/E2654.full.pdf","host_type":"publisher"},{"url":"http://www.pnas.org/syndication/doi/10.1073/pnas.1620646114","host_type":"publisher"},{"url":"https://pnas.org/doi/pdf/10.1073/pnas.1620646114","host_type":"publisher"},{"url":"https://doi.org/10.1073/pnas.1620646114","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/28292901","host_type":"repository"},{"url":"https://escholarship.org/uc/item/42s2k1qw","host_type":""},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5380058","host_type":"repository"},{"url":"https://dx.doi.org/10.1073/pnas.1620646114","host_type":""},{"url":"https://doi.org/https://doi.org/10.1073/pnas.1620646114","host_type":""}],"fields_of_study":["Protein Structure and Dynamics","Bacterial Genetics and Biotechnology","RNA and protein synthesis mechanisms","Medicine","Biology","0301 basic medicine","0303 health sciences","03 medical and health sciences","Bacterial Proteins","Escherichia coli","Models, Molecular","Molecular Chaperones","Protein Aggregates","Protein Folding","Protein Transport","Proteostasis"],"mesh_terms":["Proteostasis","Bacterial Proteins","Escherichia coli","Models, Molecular","Protein Folding","Molecular Chaperones","Protein Transport","Protein Aggregates"],"keywords":["Proteostasis","Chaperone (clinical)","Proteome","Protein folding","Cell biology","Co-chaperone","Biology","Computational biology","Chemistry","Heat shock protein","Bioinformatics","Hsp70","Biochemistry","Medicine","Chaperone","Shields Down","Shields Up","Models, Molecular","1.1 Normal biological development and functioning","Molecular","Protein Aggregates","Protein Transport","Bacterial Proteins","Underpinning research","Models","Escherichia coli","Generic health relevance","Molecular Chaperones"],"sdg_mappings":[{"sdg_number":3,"sdg_label":"3. Good health"},{"sdg_number":13,"sdg_label":"13. Climate action"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-06-07T12:27:14.558330Z","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":[]}