中文版 | English
Title

一个全面的抗菌肽数据库以及基于此数据库的生成模型

Alternative Title
ACOMPREHENSIVE ANTIMICROBIAL PEPTIDES DATABASE AND THE GENERATIVE MODEL BASED ON THIS DATABASE
Author
Name pinyin
GUAN Shenghui
School number
11930163
Degree
硕士
Discipline
0710 生物学
Subject category of dissertation
07 理学
Supervisor
王冠宇
Mentor unit
生物系
Publication Years
2022-04-28
Submission date
2022-06-24
University
南方科技大学
Place of Publication
深圳
Abstract

在过去几十年中,主要受到滥用和过度使用传统抗生素的驱动,抗菌素耐药性一直是公共健康领域的重大问题之一,威胁到微生物病原体和寄生虫的有效预防和治疗。如果没有妥善的应对方法,抗菌素耐药性将给全球带来巨大的经济损失和严重的健康卫生问题。抗菌肽因其对抗菌素耐药性发展的低倾向性、快速和广谱的抗菌活性而备受关注。抗菌肽是一种结构多变的天然短肽,广泛存在于自然界,作为宿主防御分子,在宿主的先天免疫系统中起着至关重要的作用,并有着多靶点、非特异性作用机制的特点。

本文从12个数据库中收集抗菌肽数据,并根据抗菌肽的氨基酸序列计算了多种描述符和预测了三维空间结构。我们结合了蛋白质数据集和抗菌肽数据集,使用预训练加微调的方法,融合了长短时记忆网络和变换器模型,得到了一个能够生成候选抗菌肽氨基酸序列的模型AMPTrans-lstm。同时,我们训练了两个基于构效关系的抗菌肽活性预测模型来作为我们的生成模型中的识别部分。我们的分析表明模型生成的序列既与真实序列有相似性,也有一定的新颖性。此外,生成的多肽序列在其他预测模型中也有较高的得分。

本研究表明,长短时记忆和变换器模型的串联变种,可以有效生成有抗菌活性的氨基酸序列,从而提供一些潜在的先导分子,用于后续开发潜在的抗菌肽药物。

Keywords
Language
Chinese
Training classes
独立培养
Enrollment Year
2019
Year of Degree Awarded
2022-06
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Academic Degree Assessment Sub committee
生物系
Domestic book classification number
TQ4
Data Source
人工提交
Document TypeThesis
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/342794
DepartmentDepartment of Biology
Recommended Citation
GB/T 7714
官盛晖. 一个全面的抗菌肽数据库以及基于此数据库的生成模型[D]. 深圳. 南方科技大学,2022.
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