دورية أكاديمية
A benchmark for evaluation of structure-based online tools for antibody-antigen binding affinity.
| العنوان: | A benchmark for evaluation of structure-based online tools for antibody-antigen binding affinity. |
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| المؤلفون: | Xu J; College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China., Gong J; Institute of Health Service and Transfusion Medicine, Beijing 100850, China., Bo X; Institute of Health Service and Transfusion Medicine, Beijing 100850, China., Tong Y; College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China; Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China. Electronic address: tong.yigang@gmail.com., Ren Z; School of Information Science and Technology, Northeast Normal University, Changchun 130117, China; Changchun Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Changchun 130122, China. Electronic address: zilin.ren@outlook.com., Ni M; Institute of Health Service and Transfusion Medicine, Beijing 100850, China. Electronic address: niming@bmi.ac.cn. |
| المصدر: | Biophysical chemistry [Biophys Chem] 2024 Aug; Vol. 311, pp. 107253. Date of Electronic Publication: 2024 Apr 30. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Elsevier Science B.V Country of Publication: Netherlands NLM ID: 0403171 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-4200 (Electronic) Linking ISSN: 03014622 NLM ISO Abbreviation: Biophys Chem Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: Amsterdam : Elsevier Science B.V Original Publication: Amsterdam, North-Holland Pub. Co. |
| مواضيع طبية MeSH: | Spike Glycoprotein, Coronavirus*/chemistry , Spike Glycoprotein, Coronavirus*/immunology , Spike Glycoprotein, Coronavirus*/metabolism , Spike Glycoprotein, Coronavirus*/genetics , SARS-CoV-2*/immunology , SARS-CoV-2*/chemistry , SARS-CoV-2*/metabolism , Antibodies, Monoclonal*/chemistry , Antibodies, Monoclonal*/immunology , Antibodies, Monoclonal*/metabolism, Humans ; Benchmarking ; Software ; Antigen-Antibody Reactions ; Protein Binding ; Antibodies, Viral/immunology ; Antibodies, Viral/chemistry ; COVID-19/virology ; COVID-19/immunology ; Antibody Affinity |
| مستخلص: | The prediction of binding affinity changes caused by missense mutations can elucidate antigen-antibody interactions. A few accessible structure-based online computational tools have been proposed. However, selecting suitable software for particular research is challenging, especially research on the SARS-CoV-2 spike protein with antibodies. Therefore, benchmarking of the mutation-diverse SARS-CoV-2 datasets is critical. Here, we collected the datasets including 1216 variants about the changes in binding affinity of antigens from 22 complexes for SARS-CoV-2 S proteins and 22 monoclonal antibodies as well as applied them to evaluate the performance of seven binding affinity prediction tools. The tested tools' Pearson correlations between predicted and measured changes in binding affinity were between -0.158 and 0.657, while accuracy in classification tasks on predicting increasing or decreasing affinity ranged from 0.444 to 0.834. These tools performed relatively better on predicting single mutations, especially at epitope sites, whereas poor performance on extremely decreasing affinity. The tested tools were relatively insensitive to the experimental techniques used to obtain structures of complexes. In summary, we constructed a list of datasets and evaluated a range of structure-based online prediction tools that will explicate relevant processes of antigen-antibody interactions and enhance the computational design of therapeutic monoclonal antibodies. Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (Copyright © 2023. Published by Elsevier B.V.) |
| فهرسة مساهمة: | Keywords: Affinity change; Antigen-antibody binding affinity; Mutation; Performance evaluation; SARS-CoV-2 |
| المشرفين على المادة: | 0 (Spike Glycoprotein, Coronavirus) 0 (spike protein, SARS-CoV-2) 0 (Antibodies, Monoclonal) 0 (Antibodies, Viral) |
| تواريخ الأحداث: | Date Created: 20240520 Date Completed: 20240609 Latest Revision: 20240609 |
| رمز التحديث: | 20240610 |
| DOI: | 10.1016/j.bpc.2024.107253 |
| PMID: | 38768531 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1873-4200 |
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| DOI: | 10.1016/j.bpc.2024.107253 |