African swine fever virus (ASFV), an extremely contagious virus with high mortality rates, causes severe hemorrhagic viral disease in both domestic and wild pigs. Fortunately, ASFV cannot be transmitted from pigs to humans. However, ongoing ASFV outbreaks could have severe economic consequences for global food security. Although ASFV was discovered several years ago, no vaccines or treatments are commercially available yet; therefore, the identification of new anti-ASFV drugs is urgently warranted. Using molecular docking and machine learning, we have previously identified pentagastrin, cangrelor, and fostamatinib as potential antiviral drugs against ASFV. Here, using machine learning combined with docking simulations, we identified natural products with a high affinity for AsfvPolX proteins. We selected five natural products (NPs) that are located close in chemical space to the six known natural flavonoids that possess anti-ASFV activity. Polygalic acid markedly reduced AsfvPolX polymerase activity in a dose-dependent manner. We propose an efficient protocol for identifying NPs as potential antiviral drugs by identifying chemical spaces containing high-affinity binders against ASFV in NP databases.

非洲猪瘟病毒（ASFV）是一种传染性极强、死亡率高的病毒，可导致家猪和野猪严重的出血性病毒性疾病。幸运的是，非洲猪瘟病毒不会从猪传播给人类。然而，非洲猪瘟病毒的持续爆发可能会给全球粮食安全带来严重的经济后果。尽管非洲猪瘟病毒几年前就被发现，但目前还没有商业化的疫苗或治疗方法；因此，迫切需要鉴定新的抗 ASFV 药物。通过分子对接和机器学习，我们之前已经确定五肽胃泌素、坎格瑞洛和福斯塔替尼是潜在的抗非洲猪瘟病毒药物。在这里，利用机器学习与对接模拟相结合，我们鉴定了对Asfv PolX 蛋白具有高亲和力的天然产物。我们选择了五种天然产物 (NP)，它们的化学空间与六种已知的具有抗 ASFV 活性的天然黄酮类化合物接近。聚没食子酸以剂量依赖性方式显着降低Asfv PolX 聚合酶活性。我们提出了一种有效的方案，通过识别 NP 数据库中含有针对 ASFV 的高亲和力粘合剂的化学空间，将 NP 识别为潜在的抗病毒药物。