Gianluca Mondillo, Alessandra Perrotta, Simone Colosimo, Vittoria Frattolillo
{"title":"ChatGPT as a bioinformatic partner.","authors":"Gianluca Mondillo, Alessandra Perrotta, Simone Colosimo, Vittoria Frattolillo","doi":"10.1101/2024.08.20.24312291","DOIUrl":null,"url":null,"abstract":"The advanced Large Language Model ChatGPT4o, developed by OpenAI, can be used in the field of bioinformatics to analyze and understand cross-reactive allergic reactions. This study explores the use of ChatGPT4o to support research on allergens, particularly in the cross-reactivity syndrome between cat and pork. Using a hypothetical clinical case of a child with a confirmed allergy to Fel d 2 (cat albumin) and Sus s 1 (pork albumin), the model guided data collection, protein sequence analysis, and three-dimensional structure visualization. Through the use of bioinformatics tools like SDAP 2.0 and BepiPRED, the epitope regions of the allergenic proteins were predicted, con-firming their accessibility to immunoglobulin E (IgE) and probability of cross-reactivity. The results show that regions with high epitope probability exhibit high surface accessibility and predominantly coil and helical structures. The construction of a phylogenetic tree further sup-ported the evolutionary relationships among the studied allergens. ChatGPT4o has demonstrated its usefulness in guiding non-specialist researchers through complex bioinformatics processes, making advanced science accessible and improving analytical and innovation capabilities.","PeriodicalId":501454,"journal":{"name":"medRxiv - Health Informatics","volume":"53 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Health Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.08.20.24312291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The advanced Large Language Model ChatGPT4o, developed by OpenAI, can be used in the field of bioinformatics to analyze and understand cross-reactive allergic reactions. This study explores the use of ChatGPT4o to support research on allergens, particularly in the cross-reactivity syndrome between cat and pork. Using a hypothetical clinical case of a child with a confirmed allergy to Fel d 2 (cat albumin) and Sus s 1 (pork albumin), the model guided data collection, protein sequence analysis, and three-dimensional structure visualization. Through the use of bioinformatics tools like SDAP 2.0 and BepiPRED, the epitope regions of the allergenic proteins were predicted, con-firming their accessibility to immunoglobulin E (IgE) and probability of cross-reactivity. The results show that regions with high epitope probability exhibit high surface accessibility and predominantly coil and helical structures. The construction of a phylogenetic tree further sup-ported the evolutionary relationships among the studied allergens. ChatGPT4o has demonstrated its usefulness in guiding non-specialist researchers through complex bioinformatics processes, making advanced science accessible and improving analytical and innovation capabilities.
由 OpenAI 开发的高级大型语言模型 ChatGPT4o 可用于生物信息学领域,以分析和理解交叉反应性过敏反应。本研究探讨了如何利用 ChatGPT4o 支持过敏原研究,尤其是猫和猪肉之间的交叉反应综合征。该模型使用了一个假定的临床病例,即一个对 Fel d 2(猫白蛋白)和 Sus s 1(猪白蛋白)确诊过敏的儿童,该模型指导了数据收集、蛋白质序列分析和三维结构可视化。通过使用 SDAP 2.0 和 BepiPRED 等生物信息学工具,预测了过敏原蛋白的表位区,确认了它们与免疫球蛋白 E (IgE) 的可及性和交叉反应的可能性。结果表明,表位概率高的区域具有较高的表面可及性,且主要为螺旋结构。系统发生树的构建进一步证实了所研究过敏原之间的进化关系。ChatGPT4o 在指导非专业研究人员完成复杂的生物信息学过程、普及先进科学知识以及提高分析和创新能力方面证明了它的实用性。