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PPAI: a web server for predicting protein-aptamer interactions.
BMC Bioinformatics ( IF 3 ) Pub Date : 2020-06-09 , DOI: 10.1186/s12859-020-03574-7
Jianwei Li 1, 2 , Xiaoyu Ma 1 , Xichuan Li 3 , Junhua Gu 1
Affiliation  

The interactions between proteins and aptamers are prevalent in organisms and play an important role in various life activities. Thanks to the rapid accumulation of protein-aptamer interaction data, it is necessary and feasible to construct an accurate and effective computational model to predict aptamers binding to certain interested proteins and protein-aptamer interactions, which is beneficial for understanding mechanisms of protein-aptamer interactions and improving aptamer-based therapies. In this study, a novel web server named PPAI is developed to predict aptamers and protein-aptamer interactions with key sequence features of proteins/aptamers and a machine learning framework integrated adaboost and random forest. A new method for extracting several key sequence features of both proteins and aptamers is presented, where the features for proteins are extracted from amino acid composition, pseudo-amino acid composition, grouped amino acid composition, C/T/D composition and sequence-order-coupling number, while the features for aptamers are extracted from nucleotide composition, pseudo-nucleotide composition (PseKNC) and normalized Moreau-Broto autocorrelation coefficient. On the basis of these feature sets and balanced the samples with SMOTE algorithm, we validate the performance of PPAI by the independent test set. The results demonstrate that the Area Under Curve (AUC) is 0.907 for prediction of aptamer, while the AUC reaches 0.871 for prediction of protein-aptamer interactions. These results indicate that PPAI can query aptamers and proteins, predict aptamers and predict protein-aptamer interactions in batch mode precisely and efficiently, which would be a novel bioinformatics tool for the research of protein-aptamer interactions. PPAI web-server is freely available at http://39.96.85.9/PPAI.

中文翻译:

PPAI:用于预测蛋白质与适体相互作用的Web服务器。

蛋白质和适体之间的相互作用在生物体中很普遍,并在各种生命活动中发挥重要作用。由于蛋白质-适体相互作用数据的快速积累,构建准确有效的计算模型来预测与某些感兴趣的蛋白质结合的适体和蛋白质-适体相互作用是必要且可行的,这有助于理解蛋白质-适体相互作用的机理。并改进基于适体的疗法。在这项研究中,开发了一种名为PPAI的新型Web服务器,以预测适体和蛋白质-适体与蛋白质/适体的关键序列特征以及集成了adaboost和随机森林的机器学习框架的相互作用。提出了一种提取蛋白质和适体的几个关键序列特征的新方法,其中蛋白质的特征是从氨基酸组成,假氨基酸组成,成组的氨基酸组成,C / T / D组成和序列顺序耦合数中提取的,而适体的特征是从核苷酸组成,伪氨基酸中提取的核苷酸组成(PseKNC)和标准化的Moreau-Broto自相关系数。基于这些特征集并使用SMOTE算法平衡样本,我们通过独立的测试集验证了PPAI的性能。结果表明,用于预测适体的曲线下面积(AUC)为0.907,而用于预测蛋白质-适体相互作用的AUC达到0.871。这些结果表明,PPAI可以准确高效地查询适体和蛋白质,预测适体和预测蛋白质与适体的相互作用,这将是用于蛋白质-适体相互作用研究的新型生物信息学工具。可从http://39.96.85.9/PPAI免费获得PPAI网络服务器。
更新日期:2020-06-09
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