Abstract：
BACKGROUND: Cat-derived allergens are considered as one of the most common causes of allergic diseases worldwide. Fel d 1 is a major cat allergen and plays an important role in immunoglobulin E (IgE)-reaction diagnosis. However, the two separate chains of Fel d 1 exhibited lower IgE-reactivity than its complete molecule of an assembled form, which makes it difficult to efficiently prepare and limits the application of Fel d 1 in molecular diagnosis of cat allergy.
METHODS: We first applied artificial intelligence (AI) based tool AlphaFold2 to build the 3-dimensional structures of Fel d 1 with different connection modes between two chains, which were evaluated by ERRAT program and were expressed in Escherichia coli. We then calculated the expression ratios of soluble form/inclusion bodies form of optimized Fel d 1. The Circular Dichroism (CD), High Performance Liquid Chromatography-Size Exclusion Chromatography (HPLC-SEC) and reducing/non-reducing SDS-PAGE were performed to characterize the folding status and dimerization of the optimized fusion Fel d 1. The improvement of specific-IgE reactivity to optimized fusion Fel d 1 was investigated by enzyme linked immunosorbent assay (ELISA).
RESULTS: Among several linkers, 2 × GGGGS got the highest scores, with an overall quality factor of 100. The error value of the residues around the junction of 2 × GGGGS was lower than others. It exhibited highest proportion of soluble protein than other Fel d 1 constructs with ERRAT (GGGGS, KK as well as direct fusion Fel d 1). The results of CD and HPLC-SEC showed the consistent folding and dimerization of two fused subunits between the optimized fusion Fel d 1 and previously well-defined direct fusion Fel d 1. The overall IgE-binding absorbance of optimized fusion Fel d 1 tested by ELISA was improved compared with that of the direct fusion Fel d 1.
CONCLUSIONS: We firstly provided an AI-design strategy to optimize the Fel d 1, which could spontaneously fold into its native-like structure without additional refolding process or eukaryotic folding factors. The improved IgE-binding activity and simplified preparation method could greatly facilitate it to be a robust allergen material for molecular diagnosis of cat allergy.
METHODS: We first applied artificial intelligence (AI) based tool AlphaFold2 to build the 3-dimensional structures of Fel d 1 with different connection modes between two chains, which were evaluated by ERRAT program and were expressed in Escherichia coli. We then calculated the expression ratios of soluble form/inclusion bodies form of optimized Fel d 1. The Circular Dichroism (CD), High Performance Liquid Chromatography-Size Exclusion Chromatography (HPLC-SEC) and reducing/non-reducing SDS-PAGE were performed to characterize the folding status and dimerization of the optimized fusion Fel d 1. The improvement of specific-IgE reactivity to optimized fusion Fel d 1 was investigated by enzyme linked immunosorbent assay (ELISA).
RESULTS: Among several linkers, 2 × GGGGS got the highest scores, with an overall quality factor of 100. The error value of the residues around the junction of 2 × GGGGS was lower than others. It exhibited highest proportion of soluble protein than other Fel d 1 constructs with ERRAT (GGGGS, KK as well as direct fusion Fel d 1). The results of CD and HPLC-SEC showed the consistent folding and dimerization of two fused subunits between the optimized fusion Fel d 1 and previously well-defined direct fusion Fel d 1. The overall IgE-binding absorbance of optimized fusion Fel d 1 tested by ELISA was improved compared with that of the direct fusion Fel d 1.
CONCLUSIONS: We firstly provided an AI-design strategy to optimize the Fel d 1, which could spontaneously fold into its native-like structure without additional refolding process or eukaryotic folding factors. The improved IgE-binding activity and simplified preparation method could greatly facilitate it to be a robust allergen material for molecular diagnosis of cat allergy.
摘要：
背景：猫源性过敏原被认为是世界范围内过敏性疾病的最常见原因之一。Feld1是一种主要的猫过敏原，在免疫球蛋白E（IgE）反应诊断中起重要作用。然而,Feld1的两个独立链表现出比其组装形式的完整分子更低的IgE反应性，这限制了Feld1在猫过敏分子诊断中的应用。
方法：我们首先应用基于人工智能（AI）的工具AlphaFold2，以两条链之间的不同连接模式构建Feld1的3维结构，通过ERRAT程序进行评估，并在大肠杆菌中表达。然后，我们计算了优化的Feld1的可溶形式/包涵体形式的表达比率。循环二色性（CD），进行高效液相色谱-尺寸排阻色谱(HPLC-SEC)和还原/非还原SDS-PAGE以表征优化的融合Feld1的折叠状态和二聚化。通过酶联免疫吸附测定（ELISA）研究了特异性IgE反应性对优化融合Feld1的改善。
结果：在几个接头中，2×GGGGS得分最高,整体品质因数为100。2×GGGGS的接合处周围的残留物的误差值低于其他值。与其他具有ERRAT的Feld1构建体相比，它表现出最高比例的可溶性蛋白(GGGGS，KK以及直接融合Feld1)。CD和HPLC-SEC的结果表明，优化的融合Feld1和先前明确定义的直接融合Feld1之间的两个融合亚基的折叠和二聚化一致。与直接融合Feld1相比，通过ELISA检测的优化融合Feld1的总IgE结合吸光度有所提高。
结论：我们首先提供了一种AI设计策略来优化Feld1，它可以自发地折叠成其天然样结构，而无需额外的重折叠过程或真核折叠因子。IgE结合活性的提高和制备方法的简化，可以极大地促进其成为猫过敏分子诊断的可靠过敏原材料。
方法：我们首先应用基于人工智能（AI）的工具AlphaFold2，以两条链之间的不同连接模式构建Feld1的3维结构，通过ERRAT程序进行评估，并在大肠杆菌中表达。然后，我们计算了优化的Feld1的可溶形式/包涵体形式的表达比率。循环二色性（CD），进行高效液相色谱-尺寸排阻色谱(HPLC-SEC)和还原/非还原SDS-PAGE以表征优化的融合Feld1的折叠状态和二聚化。通过酶联免疫吸附测定（ELISA）研究了特异性IgE反应性对优化融合Feld1的改善。
结果：在几个接头中，2×GGGGS得分最高,整体品质因数为100。2×GGGGS的接合处周围的残留物的误差值低于其他值。与其他具有ERRAT的Feld1构建体相比，它表现出最高比例的可溶性蛋白(GGGGS，KK以及直接融合Feld1)。CD和HPLC-SEC的结果表明，优化的融合Feld1和先前明确定义的直接融合Feld1之间的两个融合亚基的折叠和二聚化一致。与直接融合Feld1相比，通过ELISA检测的优化融合Feld1的总IgE结合吸光度有所提高。
结论：我们首先提供了一种AI设计策略来优化Feld1，它可以自发地折叠成其天然样结构，而无需额外的重折叠过程或真核折叠因子。IgE结合活性的提高和制备方法的简化，可以极大地促进其成为猫过敏分子诊断的可靠过敏原材料。
