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Identifying natural substrates for chaperonins using a sequence-based approach.

ABSTRACT: The Escherichia coli chaperonin machinery, GroEL, assists the folding of a number of proteins. We describe a sequence-based approach to identify the natural substrate proteins (SPs) for GroEL. Our method is based on the hypothesis that natural SPs are those that contain patterns of residues similar to those found in either GroES mobile loop and/or strongly binding peptide in complex with GroEL. The method is validated by comparing the predicted results with experimentally determined natural SPs for GroEL. We have searched for such patterns in five genomes. In the E. coli genome, we identify 1422 (about one-third) sequences that are putative natural SPs. In Saccharomyces cerevisiae, 2885 (32%) of sequences can be natural substrates for Hsp60, which is the analog of GroEL. The precise number of natural SPs is shown to be a function of the number of contacts an SP makes with the apical domain (N(C)) and the number of binding sites (N(B)) in the oligomer with which it interacts. For known SPs for GroEL, we find approximately 4 < N(C) < 5 and 2

SUBMITTER: Stan G

PROVIDER: S-EPMC2253340 | biostudies-literature | 2005 Jan

REPOSITORIES: biostudies-literature

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Identifying natural substrates for chaperonins using a sequence-based approach.

Stan George G Brooks Bernard R BR Lorimer George H GH Thirumalai D D

Protein science : a publication of the Protein Society 20041202 1

The Escherichia coli chaperonin machinery, GroEL, assists the folding of a number of proteins. We describe a sequence-based approach to identify the natural substrate proteins (SPs) for GroEL. Our method is based on the hypothesis that natural SPs are those that contain patterns of residues similar to those found in either GroES mobile loop and/or strongly binding peptide in complex with GroEL. The method is validated by comparing the predicted results with experimentally determined natural SPs ...[more]

PMID: 15576562

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Project description:BackgroundIdentifying caregiver availability, particularly for patients with dementia or those with a disability, is critical to informing the appropriate care planning by the health systems, hospitals, and providers. This information is not readily available, and there is a paucity of pragmatic approaches to automatically identifying caregiver availability and type.ObjectiveOur main objective was to use medical notes to assess caregiver availability and type for hospitalized patients with dementia. Our second objective was to identify whether the patient lived at home or resided at an institution.MethodsIn this retrospective cohort study, we used 2016-2019 telephone-encounter medical notes from a single institution to develop a rule-based natural language processing (NLP) algorithm to identify the patient's caregiver availability and place of residence. Using note-level data, we compared the results of the NLP algorithm with human-conducted chart abstraction for both training (749/976, 77%) and test sets (227/976, 23%) for a total of 223 adults aged 65 years and older diagnosed with dementia. Our outcomes included determining whether the patients (1) reside at home or in an institution, (2) have a formal caregiver, and (3) have an informal caregiver.ResultsTest set results indicated that our NLP algorithm had high level of accuracy and reliability for identifying whether patients had an informal caregiver (F1=0.94, accuracy=0.95, sensitivity=0.97, and specificity=0.93), but was relatively less able to identify whether the patient lived at an institution (F1=0.64, accuracy=0.90, sensitivity=0.51, and specificity=0.98). The most common explanations for NLP misclassifications across all categories were (1) incomplete or misspelled facility names; (2) past, uncertain, or undecided status; (3) uncommon abbreviations; and (4) irregular use of templates.ConclusionsThis innovative work was the first to use medical notes to pragmatically determine caregiver availability. Our NLP algorithm identified whether hospitalized patients with dementia have a formal or informal caregiver and, to a lesser extent, whether they lived at home or in an institutional setting. There is merit in using NLP to identify caregivers. This study serves as a proof of concept. Future work can use other approaches and further identify caregivers and the extent of their availability.

Dataset Information

Identifying natural substrates for chaperonins using a sequence-based approach.

Publications

Identifying natural substrates for chaperonins using a sequence-based approach.

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