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Distinguishing allergens from non-allergenic homologues using Physical-Chemical Property (PCP) motifs.

ABSTRACT: Quantitative guidelines to distinguish allergenic proteins from related, but non-allergenic ones are urgently needed for regulatory agencies, biotech companies and physicians. In a previous study, we found that allergenic proteins populate a relatively small number of protein families, as characterized by the Pfam database. However, these families also contain non-allergenic proteins, meaning that allergenic determinants must lie within more discrete regions of the sequence. Thus, new methods are needed to discriminate allergenic proteins within those families. Physical-Chemical Properties (PCP)-motifs specific for allergens within a Pfam class were determined for 17 highly populated protein domains. A novel scoring method based on PCP-motifs that characterize known allergenic proteins within these families was developed, and validated for those domains. The motif scores distinguished sequences of allergens from a large selection of 80,000 randomly selected non-allergenic sequences. The motif scores for the birch pollen allergen (Bet v 1) family, which also contains related fruit and nut allergens, correlated better than global sequence similarities with clinically observed cross-reactivities among those allergens. Further, we demonstrated that the average scores of allergen specific motifs for allergenic profilins are significantly different from the scores of non-allergenic profilins. Several of the selective motifs coincide with experimentally determined IgE epitopes of allergenic profilins. The motifs also discriminated allergenic pectate lyases, including Jun a 1 from mountain cedar pollen, from similar proteins in the human microbiome, which can be assumed to be non-allergens. The latter lacked key motifs characteristic of the known allergens, some of which correlate with known IgE binding sites.

SUBMITTER: Lu W

PROVIDER: S-EPMC5994374 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Distinguishing allergens from non-allergenic homologues using Physical-Chemical Property (PCP) motifs.

Lu Wenzhe W Negi Surendra S SS Schein Catherine H CH Maleki Soheila J SJ Hurlburt Barry K BK Braun Werner W

Molecular immunology 20180406

Quantitative guidelines to distinguish allergenic proteins from related, but non-allergenic ones are urgently needed for regulatory agencies, biotech companies and physicians. In a previous study, we found that allergenic proteins populate a relatively small number of protein families, as characterized by the Pfam database. However, these families also contain non-allergenic proteins, meaning that allergenic determinants must lie within more discrete regions of the sequence. Thus, new methods ar ...[more]

PMID: 29627609

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Project description:BackgroundAllergenic proteins can cause IgE-mediated adverse reactions in sensitized individuals. Although the sequences of many allergenic proteins have been identified, bioinformatics data analysis with advanced computational methods and modeling is needed to identify the basis for IgE binding and cross-reactivity.ObjectiveWe aim to present the features and use of the updated Structural Database of Allergenic Proteins 2.0 (SDAP 2.0) webserver, a unique, publicly available resource to compare allergens using specially designed computational tools and new high-quality 3-D models for most known allergens.MethodsPreviously developed and novel software tools for identifying cross-reactive allergens using sequence and structure similarity are implemented in SDAP 2.0. A comprehensive set of high-quality 3-D models of most allergens was generated with the state-of-the-art AlphaFold 2 software. A graphics tool enables the interactive visualization of IgE epitopes on experimentally determined and modeled 3-D structures.ResultsA user can search for allergens similar to a given input sequence with the FASTA algorithm or the window-based World Health Organization/International Union of Immunological Societies (WHO/IUIS) guidelines on safety concerns of novel food products. Peptides similar to known IgE epitopes can be identified with the property distance tool and conformational epitopes by the Cross-React method. The updated database contains 1657 manually curated sequences including all allergens from the IUIS database, 334 experimentally determined X-ray or NMR structures, and 1565 3-D models. Each allergen/isoallergen is classified according to its protein family.ConclusionsSDAP provides access to the steadily increasing information on allergenic structures and epitopes with integrated bioinformatics tools to identify and analyze their similarities. In addition to serving the research and regulatory community, it provides clinicians with tools to identify potential coallergies in a sensitive patient and can help companies to design hypoallergenic foods and immunotherapies.

Project description:BACKGROUND:To obtain information on feasibility and acceptability, as well as preliminary data on efficacy, of an Osteoarthritis Physical activity Care Pathway (OA-PCP). METHODS:This was a single group pilot study involving 60 participants with symptomatic, physician diagnosed knee or hip OA, recruited from primary care clinics. Participants self-reported completing less than 150?min per week of moderate-to-vigorous physical activity (MVPA) at baseline. The 3-month OA-PCP intervention involved 3 physical activity (PA) coaching calls (focused on goal setting), three check-in emails and linkage with community-based or online resources to support PA. Efficacy outcomes were collected at baseline and 4-month follow-up. The primary efficacy outcome was minutes of MVPA, assessed via accelerometer. Secondary outcomes included minutes of light intensity activity, sedentary minutes, step counts, and Western Ontario and McMaster Universities (WOMAC) pain and function subscales. Participants were also asked to rate the helpfulness of the OA-PCP intervention on a scale of 0-10. Differences in efficacy outcomes between baseline and 4-month follow-up were assessed using paired t-tests. RESULTS:Among participants beginning the study, 88% completed follow-up assessments and???90% completed each of the intervention calls. Average daily minutes of MVPA was 8.0 at baseline (standard deviation (SD)?=?9.9) and 8.9 at follow-up (SD?=?12.1, p?=?0.515). There were no statistically significant changes in light intensity activity, sedentary time or step counts. The mean WOMAC pain score improved from 8.1 (SD?=?3.6) at baseline to 6.2 (SD?=?3.8) at follow-up (p?<?0.001); the mean WOMAC function score improved from 26.2 (SD?=?13.2) to 20.2 (SD?=?12.5; p?<?0.001). The mean rating of helpfulness was 7.6 (SD?=?2.5). CONCLUSIONS:Results supported the feasibility and acceptability of the study, and participants reported clinically relevant improvements in pain and function. PA metrics did not improve substantially. Based on these results and participant feedback, modifications including enhanced self-monitoring are being made to increase the impact of the OA-PCP intervention on PA behavior. TRIAL REGISTRATION:NCT03780400, December 19, 2018.

Dataset Information

Distinguishing allergens from non-allergenic homologues using Physical-Chemical Property (PCP) motifs.

Publications

Distinguishing allergens from non-allergenic homologues using Physical-Chemical Property (PCP) motifs.

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