Yan Jielu, Bhadra Pratiti, Li Ang, Sethiya Pooja, Qin Longguang, Tai Hio Kuan, Wong Koon Ho, Siu Shirley W I
Department of Computer and Information Science, University of Macau, Macau, China.
Faculty of Health Sciences, University of Macau, Macau, China.
Mol Ther Nucleic Acids. 2020 Jun 5;20:882-894. doi: 10.1016/j.omtn.2020.05.006. Epub 2020 May 12.
Antimicrobial peptides (AMPs) are a valuable source of antimicrobial agents and a potential solution to the multi-drug resistance problem. In particular, short-length AMPs have been shown to have enhanced antimicrobial activities, higher stability, and lower toxicity to human cells. We present a short-length (≤30 aa) AMP prediction method, Deep-AmPEP30, developed based on an optimal feature set of PseKRAAC reduced amino acids composition and convolutional neural network. On a balanced benchmark dataset of 188 samples, Deep-AmPEP30 yields an improved performance of 77% in accuracy, 85% in the area under the receiver operating characteristic curve (AUC-ROC), and 85% in area under the precision-recall curve (AUC-PR) over existing machine learning-based methods. To demonstrate its power, we screened the genome sequence of Candida glabrata-a gut commensal fungus expected to interact with and/or inhibit other microbes in the gut-for potential AMPs and identified a peptide of 20 aa (P3, FWELWKFLKSLWSIFPRRRP) with strong anti-bacteria activity against Bacillus subtilis and Vibrio parahaemolyticus. The potency of the peptide is remarkably comparable to that of ampicillin. Therefore, Deep-AmPEP30 is a promising prediction tool to identify short-length AMPs from genomic sequences for drug discovery. Our method is available at https://cbbio.cis.um.edu.mo/AxPEP for both individual sequence prediction and genome screening for AMPs.
抗菌肽（AMPs）是抗菌剂的宝贵来源，也是解决多重耐药问题的潜在方案。特别是，短长度抗菌肽已被证明具有增强的抗菌活性、更高的稳定性以及对人体细胞更低的毒性。我们提出了一种基于PseKRAAC简化氨基酸组成的最优特征集和卷积神经网络开发的短长度（≤30个氨基酸）抗菌肽预测方法Deep-AmPEP30。在一个由188个样本组成的平衡基准数据集上，与现有的基于机器学习的方法相比，Deep-AmPEP30在准确率上提高到77%，在受试者工作特征曲线下面积（AUC-ROC）上达到85%，在精确召回率曲线下面积（AUC-PR）上达到85%。为了展示其能力，我们筛选了光滑念珠菌（一种预计会与肠道中的其他微生物相互作用和/或抑制其他微生物的肠道共生真菌）的基因组序列以寻找潜在的抗菌肽，并鉴定出一种20个氨基酸的肽（P3，FWELWKFLKSLWSIFPRRRP），它对枯草芽孢杆菌和副溶血性弧菌具有很强的抗菌活性。该肽的效力与氨苄青霉素相当显著。因此，Deep-AmPEP30是一种很有前景的预测工具，可用于从基因组序列中识别短长度抗菌肽以进行药物发现。我们的方法可在https://cbbio.cis.um.edu.mo/AxPEP上获取，用于单个序列预测和抗菌肽的基因组筛选。
