Advancing Antibody-antigen Interface Analysis in Docking Scoring Functions for Precision Docking Analysis
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- Ratnayake Sangeetha
- Division of Bioinformatics and Bioengineering, Graduate School of Information Science and Technology, Hokkaido University
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- Martinelli Axel
- BigOmics Analytics
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- Endo Toshinori
- Faculty of Information Science and Technology, Hokkaido University
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- Osada Naoki
- Faculty of Information Science and Technology, Hokkaido University
抄録
<p>Molecular docking simulations utilizing scoring functions are pivotal for assessing the stability of complex formations. The unique biochemical characteristics of antibody-antigen interfaces, however, present challenges in applying general parameter sets of scoring functions to these molecules, necessitating the customization of the scoring function to enhance prediction accuracy for structural configurations and binding affinities. In response to this, we have developed models within the Rosetta software framework, widely recognized for its utility in predicting antigen-antibody docking, to optimize the parameters of its scoring function. Through a quantitative evaluation of the shape of decoy distribution generated by Rosetta, we have been able to refine the parameters for each antibody-antigen complex, yielding a notable improvement in the prediction accuracy of the software for a given dataset. Furthermore, we have identified a distinct parameter set that is effective for the majority of complexes in our dataset, though not universally applicable. This study introduces a novel approach to customizing scoring functions, potentially contributing to advancements in drug discovery and deepening our understanding of the complexities inherent in antibody-antigen interactions at a molecular level.</p>
収録刊行物
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- IPSJ Transactions on Bioinformatics
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IPSJ Transactions on Bioinformatics 17 (0), 40-47, 2024
一般社団法人 情報処理学会
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詳細情報 詳細情報について
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- CRID
- 1390018506586635392
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- ISSN
- 18826679
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- Crossref
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- 抄録ライセンスフラグ
- 使用不可