Choi Jiwon, Yun Jun Seop, Song Hyeeun, Shin Yong-Keol, Kang Young-Hoon, Munashingha Palinda Ruvan, Yoon Jeongyeon, Kim Nam Hee, Kim Hyun Sil, Yook Jong In, Tark Dongseob, Lim Yun-Sook, Hwang Soon B
Department of Oral Pathology, Oral Cancer Research Institute, Yonsei University College of Dentistry, Seoul 03722, Korea.
Met Life Sciences Co. Ltd., Seoul 03722, Korea.
Molecules. 2021 Jun 11;26(12):3592. doi: 10.3390/molecules26123592.
African swine fever virus (ASFV) causes a highly contagious and severe hemorrhagic viral disease with high mortality in domestic pigs of all ages. Although the virus is harmless to humans, the ongoing ASFV epidemic could have severe economic consequences for global food security. Recent studies have found a few antiviral agents that can inhibit ASFV infections. However, currently, there are no vaccines or antiviral drugs. Hence, there is an urgent need to identify new drugs to treat ASFV. Based on the structural information data on the targets of ASFV, we used molecular docking and machine learning models to identify novel antiviral agents. We confirmed that compounds with high affinity present in the region of interest belonged to subsets in the chemical space using principal component analysis and -means clustering in molecular docking studies of FDA-approved drugs. These methods predicted pentagastrin as a potential antiviral drug against ASFVs. Finally, it was also observed that the compound had an inhibitory effect on PolX activity. Results from the present study suggest that molecular docking and machine learning models can play an important role in identifying potential antiviral drugs against ASFVs.
非洲猪瘟病毒（ASFV）可引发一种传染性极强的严重出血性病毒性疾病，所有年龄段的家猪感染后死亡率都很高。尽管该病毒对人类无害，但当前的非洲猪瘟病毒疫情可能会对全球粮食安全造成严重经济后果。最近的研究发现了一些能够抑制ASFV感染的抗病毒药物。然而，目前尚无疫苗或抗病毒药物。因此，迫切需要鉴定出治疗ASFV的新药。基于ASFV靶点的结构信息数据，我们运用分子对接和机器学习模型来鉴定新型抗病毒药物。在对FDA批准药物的分子对接研究中，我们通过主成分分析和K均值聚类，确认了在感兴趣区域存在的具有高亲和力的化合物属于化学空间中的子集。这些方法预测五肽胃泌素是一种针对非洲猪瘟病毒的潜在抗病毒药物。最后，还观察到该化合物对PolX活性具有抑制作用。本研究结果表明，分子对接和机器学习模型在鉴定针对非洲猪瘟病毒的潜在抗病毒药物方面可发挥重要作用。
