In this research, we employed a deep reinforcement learning (RL)-based molecule design platform to generate a diverse set of compounds targeting the neuraminidase (NA) of influenza A and B viruses. A total of 60,291 compounds were generated, of which 86.5 % displayed superior physicochemical properties compared to oseltamivir. After narrowing down the selection through computational filters, nine compounds with non-sialic acid-like structures were selected for in vitro experiments. We identified two compounds, DS-22-inf-009 and DS-22-inf-021 that effectively inhibited the NAs of both influenza A and B viruses (IAV and IBV), including H275Y mutant strains at low micromolar concentrations. Molecular dynamics simulations revealed a similar pattern of interaction with amino acid residues as oseltamivir. In cell-based assays, DS-22-inf-009 and DS-22-inf-021 inhibited IAV and IBV in a dose-dependent manner with EC values ranging from 0.29 μM to 2.31 μM. Furthermore, animal experiments showed that both DS-22-inf-009 and DS-22-inf-021 exerted antiviral activity in mice, conferring 65 % and 85 % protection from IAV (H1N1 pdm09), and 65 % and 100 % protection from IBV (Yamagata lineage), respectively. Thus, these findings demonstrate the potential of RL to generate compounds with promising antiviral properties.

中文翻译：

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通过人工智能发现新的抗病毒药物：体外和体内结果


在这项研究中，我们采用了基于深度强化学习（RL）的分子设计平台来生成针对甲型和乙型流感病毒的神经氨酸酶（NA）的多种化合物。总共生成了 60,291 种化合物，其中 86.5% 与奥司他韦相比表现出更优异的理化性质。通过计算过滤器缩小选择范围后，选择了九种具有非唾液酸样结构的化合物进行体外实验。我们鉴定出两种化合物 DS-22-inf-009 和 DS-22-inf-021，它们可以在低微摩尔浓度下有效抑制甲型和乙型流感病毒（IAV 和 IBV）的 NA，包括 H275Y 突变株。分子动力学模拟揭示了与奥司他韦类似的与氨基酸残基的相互作用模式。在基于细胞的测定中，DS-22-inf-009 和 DS-22-inf-021 以剂量依赖性方式抑制 IAV 和 IBV，EC 值范围为 0.29 μM 至 2.31 μM。此外，动物实验表明，DS-22-inf-009 和 DS-22-inf-021 对小鼠均具有抗病毒活性，对 IAV (H1N1 pdm09) 具有 65% 和 85% 的保护作用，对 IAV (H1N1 pdm09) 具有 65% 和 100% 的保护作用。分别是IBV（山形血统）。因此，这些发现证明了 RL 产生具有良好抗病毒特性的化合物的潜力。