论文标题
深度学习用于药物重新利用：方法，数据库和应用程序
Deep learning for drug repurposing: methods, databases, and applications
论文作者
论文摘要
药物开发既费时又昂贵。重新利用现有的新疗法药物是一种有吸引力的解决方案，可在降低的实验成本以降低的药物开发加速，特别是针对2019年冠状病毒病（Covid-19），这是一种由严重的急性急性呼吸综合症冠状病毒2（SARS-COV-2）引起的传染病（SARS-COV-2）。但是，全面地获得并有效地整合可用的知识和大型生物医学数据以有效地推进深度学习模型，对于其他复杂疾病中的药物重新利用仍然具有挑战性。在这篇综述中，我们介绍了有关如何利用深度学习方法和药物重新使用的工具的指南。我们首先总结了常用的生物信息学和药物基因组学数据库，以重新利用药物。接下来，我们讨论了最近开发的基于序列和基于图的表示方法以及最先进的基于深度学习的方法。最后，我们介绍了与19次大流行有关的药物重新利用的应用，并概述了其未来的挑战。
Drug development is time-consuming and expensive. Repurposing existing drugs for new therapies is an attractive solution that accelerates drug development at reduced experimental costs, specifically for Coronavirus Disease 2019 (COVID-19), an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, comprehensively obtaining and productively integrating available knowledge and big biomedical data to effectively advance deep learning models is still challenging for drug repurposing in other complex diseases. In this review, we introduce guidelines on how to utilize deep learning methodologies and tools for drug repurposing. We first summarized the commonly used bioinformatics and pharmacogenomics databases for drug repurposing. Next, we discuss recently developed sequence-based and graph-based representation approaches as well as state-of-the-art deep learning-based methods. Finally, we present applications of drug repurposing to fight the COVID-19 pandemic, and outline its future challenges.
