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.

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Summary Lithium‐sulfur (Li‐S) battery has been evoked increasing attention due to its creditable energy density and the abundant sulfur in nature. Nevertheless, its commercialization is still hampered in virtue of the poor conductivity of sulfur and grievous polysulfide shuttling. To address these issues, in this work, we report a cost‐efficient and facile tactic to fabricate frame‐structured neodymium‐doped bismuth vanadate (BiVO4) nanoarchitectures, which are reasonably designed as a polysulfide shield to alleviate the shuttling effects. The synthesized nanoarchitectures exhibit typical tetragonal phase with a unique frame structure. The frame structure of BiVO4 impedes polysulfide shuttling, and supplies electronic and ionic transmission routes. Furthermore, the rational doping of neodymium within the BiVO4 nanoarchitectures can improve electric conductivity, as well as efficiently alleviate the loss of sulfur and improve activity for sulfur reduction. Benefitting from the structural feature and doping strategy, the Li‐S battery performance with a neodymium‐doped BiVO4 nanoarchitecture is significantly improved. This strategy is easily adopted for fabricating other nanostructures, providing a feasible way to design cheap and efficient battery materials. This work is further available for synergistically uniting the virtues of the frame nanoarchitectures and doping protocol to develop advanced Li‐S batteries.

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