PDF(Pubmed)
Abstract：
COVID 19 pandemic is still ongoing, having taken more than 6 million human lives with it, and it seems that the world will have to learn how to live with the virus around. In consequence, there is a need to develop different treatments against it, not only with vaccines, but also new medicines. To do this, human-virus protein-protein interactions (PPIs) play a key part in drug-target discovery, but finding them experimentally can be either costly or sometimes unreliable. Therefore, computational methods arose as a powerful alternative to predict these interactions, reducing costs and helping researchers confirm only certain interactions instead of trying all possible combinations in the laboratory. Malivhu is a tool that predicts human-virus PPIs through a 4-phase process using machine learning models, where phase 1 filters ssRNA(+) class virus proteins, phase 2 filters Coronaviridae family proteins and phase 3 filters severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) species proteins, and phase 4 predicts human-SARS-CoV/SARS-CoV-2/MERS protein-protein interactions. The performance of the models was measured with Matthews correlation coefficient, F1-score, specificity, sensitivity, and accuracy scores, getting accuracies of 99.07%, 99.83%, and 100% for the first 3 phases, respectively, and 94.24% for human-SARS-CoV PPI, 94.50% for human-SARS-CoV-2 PPI, and 95.45% for human-MERS PPI on independent testing. All the prediction models developed for each of the 4 phases were implemented as web server which is freely available at https://kaabil.net/malivhu/.
摘要：
COVID19仍在流行，用它夺走了600多万人的生命，似乎世界将不得不学习如何与病毒共存。因此，有必要针对它开发不同的治疗方法，不仅仅是疫苗，还有新药。要做到这一点，人-病毒蛋白-蛋白相互作用（PPI）在药物靶标发现中起着关键作用，但是通过实验找到它们可能是昂贵的，或者有时是不可靠的。因此,计算方法作为预测这些相互作用的强大替代方案而出现，降低成本，帮助研究人员只确认某些相互作用，而不是在实验室中尝试所有可能的组合。Malivhu是一种使用机器学习模型通过4阶段过程预测人类病毒PPI的工具，第一阶段过滤ssRNA(+)类病毒蛋白，2期过滤冠状病毒科蛋白，3期过滤严重急性呼吸综合征（SARS）和中东呼吸综合征（MERS）物种蛋白，4期预测人-SARS-CoV/SARS-CoV-2/MERS蛋白-蛋白相互作用。模型的性能用马修斯相关系数测量，F1分数，特异性，灵敏度,和准确度得分，准确率为99.07%，99.83%,前三个阶段100%，分别,人-SARS-CoVPPI为94.24%，人-SARS-CoV-2PPI为94.50%，在独立测试中，人类MERSPPI为95.45%。为四个阶段中的每个阶段开发的所有预测模型都作为Web服务器实现，该服务器可在https://kaabil.net/malivhu/上免费获得。
