PMID- 38185034
OWN - NLM
STAT- MEDLINE
DCOM- 20240208
LR  - 20240208
IS  - 1878-1705 (Electronic)
IS  - 1567-5769 (Linking)
VI  - 128
DP  - 2024 Feb 15
TI  - Artificial intelligence-driven design of the assembled major cat allergen Fel d 1 
      to improve its spatial folding and IgE-reactivity.
PG  - 111488
LID - S1567-5769(24)00005-5 [pii]
LID - 10.1016/j.intimp.2024.111488 [doi]
AB  - 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 x GGGGS got 
      the highest scores, with an overall quality factor of 100. The error value of the 
      residues around the junction of 2 x 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. CONCLUSION: 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.
CI  - Copyright (c) 2024 Elsevier B.V. All rights reserved.
FAU - Zheng, Wei
AU  - Zheng W
AD  - Department of Pharmacy, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer 
      Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 
      China.
FAU - Xu, Yi-Fei
AU  - Xu YF
AD  - Department of Pharmacy, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer 
      Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 
      China.
FAU - Hu, Zhi-Ming
AU  - Hu ZM
AD  - Department of Pharmacy, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer 
      Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 
      China.
FAU - Li, Ke
AU  - Li K
AD  - Department of Pharmacy, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer 
      Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 
      China.
FAU - Xu, Zhi-Qiang
AU  - Xu ZQ
AD  - Research Division of Clinical Pharmacology, The First Affiliated Hospital of 
      Nanjing Medical University, Nanjing, China; National Vaccine Innovation Platform, 
      Nanjing Medical University, Nanjing 211166, China. Electronic address: 
      xu.zhiqiang@outlook.com.
FAU - Sun, Jin-Lyu
AU  - Sun JL
AD  - Department of Allergy, State Key Laboratory of Complex Severe and Rare Diseases, 
      Peking Union Medical College Hospital, Chinese Academy of Medical Science and 
      Peking Union Medical College, Beijing, China. Electronic address: 
      sunjinlv@pumch.cn.
FAU - Wei, Ji-Fu
AU  - Wei JF
AD  - Department of Pharmacy, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer 
      Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 
      China; Research Division of Clinical Pharmacology, The First Affiliated Hospital 
      of Nanjing Medical University, Nanjing, China; National Vaccine Innovation 
      Platform, Nanjing Medical University, Nanjing 211166, China. Electronic address: 
      weijifu@njmu.edu.cn.
LA  - eng
PT  - Journal Article
DEP - 20240106
PL  - Netherlands
TA  - Int Immunopharmacol
JT  - International immunopharmacology
JID - 100965259
RN  - 37341-29-0 (Immunoglobulin E)
RN  - 0 (Allergens)
SB  - IM
MH  - Humans
MH  - *Immunoglobulin E/metabolism
MH  - Amino Acid Sequence
MH  - Artificial Intelligence
MH  - *Hypersensitivity
MH  - Allergens/chemistry
OTO - NOTNLM
OT  - Allergen
OT  - Artificial intelligence
OT  - Escherichia coli
OT  - Fel d 1
OT  - Immunoglobulin E (IgE)
COIS- 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.
EDAT- 2024/01/08 00:42
MHDA- 2024/02/08 06:42
CRDT- 2024/01/07 18:11
PHST- 2023/10/16 00:00 [received]
PHST- 2023/12/31 00:00 [revised]
PHST- 2024/01/02 00:00 [accepted]
PHST- 2024/02/08 06:42 [medline]
PHST- 2024/01/08 00:42 [pubmed]
PHST- 2024/01/07 18:11 [entrez]
AID - S1567-5769(24)00005-5 [pii]
AID - 10.1016/j.intimp.2024.111488 [doi]
PST - ppublish
SO  - Int Immunopharmacol. 2024 Feb 15;128:111488. doi: 10.1016/j.intimp.2024.111488. 
      Epub 2024 Jan 6.