دورية أكاديمية
أعرض في EDS

CryptoSite: Expanding the Druggable Proteome by Characterization and Prediction of Cryptic Binding Sites.

التفاصيل البيبلوغرافية
العنوان: CryptoSite: Expanding the Druggable Proteome by Characterization and Prediction of Cryptic Binding Sites.
المؤلفون: Cimermancic P; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Graduate Group in Biological and Medical Informatics,University of California, San Francisco, San Francisco, CA 94158, USA. Electronic address: peter.cimermancic@ucsf.edu., Weinkam P; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA., Rettenmaier TJ; Graduate Group in Chemistry and Chemical Biology, University of California, San Francisco, San Francisco, CA 94158, USA; Pharmaceutical Chemistry and California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, CA 94158, USA., Bichmann L; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA., Keedy DA; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA., Woldeyes RA; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Graduate Group in Chemistry and Chemical Biology, University of California, San Francisco, San Francisco, CA 94158, USA., Schneidman-Duhovny D; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA., Demerdash ON; Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720, USA., Mitchell JC; Departments of Biochemistry and Mathematics, University of Wisconsin-Madison, Madison, WI 53706, USA., Wells JA; Pharmaceutical Chemistry and California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, CA 94158, USA; Cellular and Molecular Pharmacology and California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, CA 94158, USA., Fraser JS; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA., Sali A; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA; Pharmaceutical Chemistry and California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, CA 94158, USA. Electronic address: http://salilab.org.
المصدر: Journal of molecular biology [J Mol Biol] 2016 Feb 22; Vol. 428 (4), pp. 709-719. Date of Electronic Publication: 2016 Feb 05.
نوع المنشور: Journal Article; Research Support, Non-U.S. Gov't
اللغة: English
بيانات الدورية: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 2985088R Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1089-8638 (Electronic) Linking ISSN: 00222836 NLM ISO Abbreviation: J Mol Biol Subsets: MEDLINE
أسماء مطبوعة: Publication: Amsterdam : Elsevier
Original Publication: 1959- : London : Academic Press
مواضيع طبية MeSH: Computational Biology/*methods , Proteins/*chemistry , Proteins/*metabolism , Proteome/*analysis, Binding Sites ; Humans ; Machine Learning ; Protein Conformation
مستخلص: Many proteins have small-molecule binding pockets that are not easily detectable in the ligand-free structures. These cryptic sites require a conformational change to become apparent; a cryptic site can therefore be defined as a site that forms a pocket in a holo structure, but not in the apo structure. Because many proteins appear to lack druggable pockets, understanding and accurately identifying cryptic sites could expand the set of drug targets. Previously, cryptic sites were identified experimentally by fragment-based ligand discovery and computationally by long molecular dynamics simulations and fragment docking. Here, we begin by constructing a set of structurally defined apo-holo pairs with cryptic sites. Next, we comprehensively characterize the cryptic sites in terms of their sequence, structure, and dynamics attributes. We find that cryptic sites tend to be as conserved in evolution as traditional binding pockets but are less hydrophobic and more flexible. Relying on this characterization, we use machine learning to predict cryptic sites with relatively high accuracy (for our benchmark, the true positive and false positive rates are 73% and 29%, respectively). We then predict cryptic sites in the entire structurally characterized human proteome (11,201 structures, covering 23% of all residues in the proteome). CryptoSite increases the size of the potentially "druggable" human proteome from ~40% to ~78% of disease-associated proteins. Finally, to demonstrate the utility of our approach in practice, we experimentally validate a cryptic site in protein tyrosine phosphatase 1B using a covalent ligand and NMR spectroscopy. The CryptoSite Web server is available at http://salilab.org/cryptosite.
(Published by Elsevier Ltd.)
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معلومات مُعتمدة: R21 GM110580 United States GM NIGMS NIH HHS; P30 DK063720 United States DK NIDDK NIH HHS; R01 GM083960 United States GM NIGMS NIH HHS; T32 GM008692 United States GM NIGMS NIH HHS; U54 RR022220 United States RR NCRR NIH HHS; United States Howard Hughes Medical Institute; DP5 OD009180 United States OD NIH HHS; U54 GM094662 United States GM NIGMS NIH HHS; T32 GM064337 United States GM NIGMS NIH HHS; F31 CA180378 United States CA NCI NIH HHS; P41 GM109824 United States GM NIGMS NIH HHS; P01 AI091575 United States AI NIAID NIH HHS; U01 GM098256 United States GM NIGMS NIH HHS
فهرسة مساهمة: Keywords: cryptic binding sites; machine learning; protein dynamics; undruggable proteins
المشرفين على المادة: 0 (Proteins)
0 (Proteome)
تواريخ الأحداث: Date Created: 20160209 Date Completed: 20160722 Latest Revision: 20181113
رمز التحديث: 20231215
مُعرف محوري في PubMed: PMC4794384
DOI: 10.1016/j.jmb.2016.01.029
PMID: 26854760
قاعدة البيانات: MEDLINE
الوصف
تدمد:1089-8638
DOI:10.1016/j.jmb.2016.01.029