دورية أكاديمية

SAFoldNet: A Novel Tool for Discovering and Aligning Three-Dimensional Protein Structures Based on a Neural Network.

التفاصيل البيبلوغرافية
العنوان: SAFoldNet: A Novel Tool for Discovering and Aligning Three-Dimensional Protein Structures Based on a Neural Network.
المؤلفون: Petrovskiy DV; Institute of Biomedical Chemistry, 119121 Moscow, Russia., Nikolsky KS; Institute of Biomedical Chemistry, 119121 Moscow, Russia., Rudnev VR; Institute of Biomedical Chemistry, 119121 Moscow, Russia., Kulikova LI; Institute of Biomedical Chemistry, 119121 Moscow, Russia., Butkova TV; Institute of Biomedical Chemistry, 119121 Moscow, Russia., Malsagova KA; Institute of Biomedical Chemistry, 119121 Moscow, Russia., Kopylov AT; Institute of Biomedical Chemistry, 119121 Moscow, Russia., Kaysheva AL; Institute of Biomedical Chemistry, 119121 Moscow, Russia.
المصدر: International journal of molecular sciences [Int J Mol Sci] 2023 Sep 22; Vol. 24 (19). Date of Electronic Publication: 2023 Sep 22.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101092791 Publication Model: Electronic Cited Medium: Internet ISSN: 1422-0067 (Electronic) Linking ISSN: 14220067 NLM ISO Abbreviation: Int J Mol Sci Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Basel, Switzerland : MDPI, [2000-
مواضيع طبية MeSH: Proteins*/chemistry , Algorithms*, Sequence Alignment ; Neural Networks, Computer ; Mathematics ; Databases, Protein ; Software
مستخلص: The development and improvement of methods for comparing and searching for three-dimensional protein structures remain urgent tasks in modern structural biology. To solve this problem, we developed a new tool, SAFoldNet, which allows for searching, aligning, superimposing, and determining the exact coordinates of fragments of protein structures. The proposed search and alignment tool was built using neural networking. Specifically, we implemented the integrative synergy of neural network predictions and the well-known BLAST algorithm for searching and aligning sequences. The proposed method involves multistage processing, comprising a stage for converting the geometry of protein structures into sequences of a structural alphabet using a neural network, a search stage for forming a set of candidate structures, and a refinement stage for calculating the structural alignment and overlap and evaluating the similarity with the starting structure of the search. The effectiveness and practical applicability of the proposed tool were compared with those of several widely used services for searching and aligning protein structures. The results of the comparisons confirmed that the proposed method is effective and competitive relative to the available modern services. Furthermore, using the proposed approach, a service with a user-friendly web interface was developed, which allows for searching, aligning, and superimposing protein structures; determining the location of protein fragments; mapping onto a protein molecule chain; and providing structural similarity metrices (expected value and root mean square deviation).
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معلومات مُعتمدة: 122092200056-9 Russian Federation Fundamental Research Program
فهرسة مساهمة: Keywords: neural network; protein conformation; protein domain; protein motif; protein structure; structural alphabet
المشرفين على المادة: 0 (Proteins)
تواريخ الأحداث: Date Created: 20231014 Date Completed: 20231101 Latest Revision: 20231101
رمز التحديث: 20240628
مُعرف محوري في PubMed: PMC10572457
DOI: 10.3390/ijms241914439
PMID: 37833886
قاعدة البيانات: MEDLINE
الوصف
تدمد:1422-0067
DOI:10.3390/ijms241914439