CAREER: Decoding the Code of Glycan-Collectin Interactions: Computational Engineering of Surfactant Proteins for Tailored Glycan Recognition
CAREER: Decoding the Code of Glycan-Collectin Interactions: Computational Engineering of Surfactant Proteins for Tailored Glycan Recognition
批准号:
2338401
负责人:
Mona Minkara
金额:
$82.73万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2024
资助国家:
美国
项目状态:
未结题
起止时间:
2024-02-01 至 2029-01-31
中文摘要
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英文摘要
Certain viruses and bacteria cause disease (pathogens). Pathogens attach sugars to their exterior to avoid detection by the immune system. The immune system produces proteins (collectins) that recognize and bind to foreign sugars (glycans). The overall objectives of this project are to better understand and improve the binding of collectins to glycans. This could drive the development of improved vaccines and therapies. Artificial intelligence tools will be employed to help develop design rules for the improved collectins. Enhanced binding of the Influenza A virus will be the test case. The results of the project will also provide material for the Blind Scientist Toolkit that the investigator has developed that teaches non-visual approaches to scientific exploration.The primary goals of this project are to elucidate and optimize the binding affinity between collectins, a class of C-type lectins, and glycans, the sugar structures found on the surface of pathogens such as viruses. This research aims to enhance the early detection and response of the mammalian immune system to viral infections. An interdisciplinary approach integrating computational and experimental methodologies will be utilized. The structural variations and amino acid sequences within the Carbohydrate Recognition Domains of Surfactant Proteins A and D (SP-D) will be investigated. Detailing the analysis of the interactions at the molecular level will be used to develop a set of rational design rules. These rules will guide the engineering of SP-D variants with enhanced capabilities for glycan binding, particularly tailored to target Influenza A structures. The methodology includes comprehensive computational analyses, molecular dynamics simulations, docking studies, and in vitro binding assays.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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