基于多维度生物信息学方法对lncRNA编码跨膜小肽的预测及其多聚体机制和功能的探索

Long non-coding RNA (lncRNA) is an important functional RNA that closely related to various kinds of diseases such as cancer, inflammation and neuromuscular disorders. Recently, some Small Open Reading Frames (smORFs) have been found in the lncRNA, and some of them can be encoded transmembrane small peptides and play many biological functions. There are evidences that the small peptides can self-assembled to oligomers which could participate in specific regulations. This study based on multi-dimensional bioinformatics for exploring four aspects (1) Determine the molecular mechanism of self-assembly of these small peptides to form oligomers (2) The existence of oligomers and the mechanisms of ions and water permeation (3) The effect of amino acid modification on the structure of oligomers (4) prediction of key lncRNA encoded transmembrane small peptides and study their function. Through this study, we will help to understand the molecular mechanisms of the transmembrane small peptide oligomers which encoded by lncRNAs as well as deepen understand their functions. At the same time, it will provide theoretical support for the scientific research, drug design, detection and diagnosis of related small peptides.

长链非编码RNA(lncRNA) 是一类重要的的功能性RNA分子，它与许多疾病发生发展密切相关。最近发现lncRNA上存在许多小开放阅读框（smORF），其中一部分可以编码成跨膜小肽发挥生物学功能，受到国内外研究人员的重视。研究显示，一些小肽可以自组装形成多聚体，参与特定调控。本课题基于生物信息数据分析、分子动力学模拟、结构生物学等多维生物信息学方法，以小肽结构和功能作为切入点，着重从四个方面探索 (1) 预测并构建lncRNA编码的跨膜小肽（2）确定这些小肽在膜上自组装形成多聚体的分子机制（3）探索多聚体存在方式及功能（4）小肽氨基酸修饰后对多聚体结构和功能的影响。通过本课题的研究，将有助于加深我们对lncRNA编码跨膜小肽形成多聚体分子机理和多聚体功能的理解和认知。同时，也将为针对相关小肽的科学研究、药物设计、检测诊断等提供分子结构层面的理论支持。

长链非编码RNA(lncRNA)是一类重要的RNA分子，它与癌症、炎症、神经肌肉等疾病发生发展密切相关。lncRNA上存在许多小开放阅读框（smORF）其中一部分可以编码成跨膜小肽并发挥生物学功能。有证据显示，一些小肽可以自组装形成多聚体，参与特定细胞中的离子和水的调控。本课题基于长时间分子模拟、生物信息学分析等方法，以跨膜小肽多聚体作为切入点，主要探索了五个方面：（1）确定这些小肽在膜上自组装形成多聚体的分子机制（2）多聚体存在方式及对离子和水通透作用的机理（3）氨基酸经过修饰后对多聚体结构和功能的影响（4）预测关键lncRNA编码的跨膜小肽，并基于物质结构基础进行研究（5）探索复杂细胞膜成分对小肽自组装与多聚体结构相互作用的分子机制。通过本研究，将帮助我们理解lncRNAs编码的跨膜小肽多聚体的形成的分子机理、加深对它们功能的认识。同时，本研究也将为相似结构跨膜小肽（如新冠病毒E蛋白）的疾病机理、药物设计、检测诊断等提供结构层面的理论支持。

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