摘要
蛋白质与适配体间的相互作用广泛存在于生物体,且在各种生命活动中发挥着重要作用。核酸适配体(简称适配体)是与靶标具有高亲和力的、长度大约在30~80 nt的核苷酸链,其与蛋白质的特异性结合对于疾病的靶向治疗研究具有重要意义。随着大数据和人工智能的发展,基于生物信息学的蛋白质-适配体相互作用预测及适配体筛选的计算方法的实现能有效解决传统实验方法的周期长、费用高等问题。本文就蛋白质-适配体相互作用预测实现方法和以蛋白质为靶标的适配体的筛选方法作一综述,以期为临床选择适合的预测方法提供参考。
The interaction between proteins and aptamers is widespread in organisms and plays an important role in various life activities. Nucleic acid aptamers(abbreviation form of aptamers) are high-affinity nucleotide chains with a length of about 30~80 nt, and their specific binding to proteins is of great significance for the targeted treatment of diseases. With the development of big data and artificial intelligence, the implementation of calculation methods for protein-aptamer interaction prediction and aptamer selection based on bioinformatics can effectively solve the problems of long cycle and high cost of traditional experimental methods. This article reviews the realization methods of protein-aptamer interaction prediction and the selection methods of protein-targeted aptamers, in order to provide a reference for clinical selection of suitable prediction methods.
作者
马晓玉
岳欣蕾
韩佳玲
李建伟
MA Xiao-yu;YUE Xin-lei;HAN Jia-ling;LI Jian-wei(Institute of Computational Medicine,School of Artificial Intelligence and Data Science,Hebei University of Technology,Tianjin 300401,China)
出处
《医学信息》
2020年第10期27-29,共3页
Journal of Medical Information
基金
国家自然科学基金项目(编号:81672113)。
