Prediction of the structural interface between fibroblast growth factor23 and Burosumab using alanine scanning and molecular docking

使用丙氨酸扫描和分子对接预测成纤维细胞生长因子 23 和 Burosumab 之间的结构界面

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作者:Karnpob Kanhasut, Kannan Tharakaraman, Mathuros Ruchirawat, Jutamaad Satayavivad, Mayuree Fuangthong, Ram Sasisekharan

Abstract

Burosumab, an FGF23 targeting monoclonal antibody, was approved by the FDA in 2018 for use in children and adults with X-linked hypophosphatemia (or XLH). While several clinical studies have demonstrated the long-term safety and efficacy of Burosumab, the molecular basis of FGF23-Burosumab interaction which underpins its mechanism of action remains unknown. In this study, we employed molecular docking combined with alanine scanning of epitope and paratope to predict a model of FGF23-Burosumab interaction. Then, we used the model to understand the species-species cross-reactivity of Burosumab and to reverse engineer mouse FGF23 with 'back to human' mutations to bind Burosumab. Finally, we redesigned the CDRs with two mutations to engineer an affinity enhanced variant of the antibody. Our study provides insights into the FGF23-Burosumab interaction and demonstrates that alanine-scanning coupled with molecular docking can be used to optimize antibody candidates (e.g., structure-guided affinity maturation) for therapeutic use.

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