Direct prediction of intrinsically disordered protein conformational properties from sequence.

التفاصيل البيبلوغرافية
العنوان:	Direct prediction of intrinsically disordered protein conformational properties from sequence.
المؤلفون:	Lotthammer JM; Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA.; Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA., Ginell GM; Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA.; Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA., Griffith D; Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA.; Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA., Emenecker RJ; Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA.; Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA., Holehouse AS; Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA. alex.holehouse@wustl.edu.; Center for Biomolecular Condensates, Washington University in St. Louis, St. Louis, MO, USA. alex.holehouse@wustl.edu.
المصدر:	Nature methods [Nat Methods] 2024 Mar; Vol. 21 (3), pp. 465-476. Date of Electronic Publication: 2024 Jan 31.
نوع المنشور:	Journal Article
اللغة:	English
بيانات الدورية:	Publisher: Nature Pub. Group Country of Publication: United States NLM ID: 101215604 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1548-7105 (Electronic) Linking ISSN: 15487091 NLM ISO Abbreviation: Nat Methods Subsets: MEDLINE
أسماء مطبوعة:	Original Publication: New York, NY : Nature Pub. Group, c2004-
مواضيع طبية MeSH:	Intrinsically Disordered Proteins*/chemistry, Protein Conformation ; Polymers
مستخلص:	Intrinsically disordered regions (IDRs) are ubiquitous across all domains of life and play a range of functional roles. While folded domains are generally well described by a stable three-dimensional structure, IDRs exist in a collection of interconverting states known as an ensemble. This structural heterogeneity means that IDRs are largely absent from the Protein Data Bank, contributing to a lack of computational approaches to predict ensemble conformational properties from sequence. Here we combine rational sequence design, large-scale molecular simulations and deep learning to develop ALBATROSS, a deep-learning model for predicting ensemble dimensions of IDRs, including the radius of gyration, end-to-end distance, polymer-scaling exponent and ensemble asphericity, directly from sequences at a proteome-wide scale. ALBATROSS is lightweight, easy to use and accessible as both a locally installable software package and a point-and-click-style interface via Google Colab notebooks. We first demonstrate the applicability of our predictors by examining the generalizability of sequence-ensemble relationships in IDRs. Then, we leverage the high-throughput nature of ALBATROSS to characterize the sequence-specific biophysical behavior of IDRs within and between proteomes. (© 2024. The Author(s).)
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معلومات مُعتمدة:	RGP0015/2022 Human Frontier Science Program (HFSP); 2128068 NSF \| BIO \| Division of Molecular and Cellular Biosciences (MCB); 2139839 NSF \| BIO \| Division of Molecular and Cellular Biosciences (MCB); 2213983 NSF \| BIO \| Division of Biological Infrastructure (DBI)
المشرفين على المادة:	0 (Intrinsically Disordered Proteins) 0 (Polymers)
تواريخ الأحداث:	Date Created: 20240131 Date Completed: 20240313 Latest Revision: 20240318
رمز التحديث:	20240318
مُعرف محوري في PubMed:	PMC10927563
DOI:	10.1038/s41592-023-02159-5
PMID:	38297184
قاعدة البيانات:	MEDLINE

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تدمد:	1548-7105
DOI:	10.1038/s41592-023-02159-5