通过机器学习和分子动力学模拟发现潜在的 RIPK1 抑制剂,Physical Chemistry Chemical Physics

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通过机器学习和分子动力学模拟发现潜在的 RIPK1 抑制剂
Physical Chemistry Chemical Physics ( IF 2.9 ) Pub Date : 2023-11-14 , DOI: 10.1039/d3cp03755j
Ji-Xiang Liu ₁ , Ri-Song Na ₂ , Lian-Juan Yang ₃ , Xu-Ri Huang ₁ , Xi Zhao ₁

Affiliation

受体相互作用丝氨酸/苏氨酸蛋白激酶 1 (RIPK1) 在炎症和细胞死亡中发挥着至关重要的作用，因此它是治疗自身免疫、炎症、神经退行性和缺血性疾病的有希望的候选者。到目前为止，还没有批准的 RIPK1 抑制剂。在这项研究中，采用了四种机器学习算法（随机森林、额外树、极端梯度提升机和光梯度提升机）来预测 RIPK1 的小分子抑制剂。统计指标显示了所有四个模型相似的性能并展示了出色的预测能力。采用分子对接和聚类分析来确认六种化合物在结构上与现有的 RIPK1 抑制剂不同。随后进行分子动力学模拟以评估这些化合物的结合能力。利用 Shapley 附加解释 (SHAP) 方法，1855 位已被确定为最重要的分子指纹片段。研究结果表明，这六种小分子在相关疾病中针对 RIPK1 表现出巨大的潜力。值得注意的是，从芭蕉中鉴定出的 Cpd-1 小分子 (ZINC000085897746) 突出了其天然产物来源，值得进一步关注和研究。

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Discovery of potential RIPK1 inhibitors by machine learning and molecular dynamics simulations

Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) plays a crucial role in inflammation and cell death, so it is a promising candidate for the treatment of autoimmune, inflammatory, neurodegenerative, and ischemic diseases. So far, there are no approved RIPK1 inhibitors available. In this study, four machine learning algorithms were employed (random forest, extra trees, extreme gradient boosting and light gradient boosting machine) to predict small molecule inhibitors of RIPK1. The statistical metrics revealed similar performance and demonstrated outstanding predictive capabilities in all four models. Molecular docking and clustering analysis were employed to confirm six compounds that are structurally distinct from existing RIPK1 inhibitors. Subsequent molecular dynamics simulations were performed to evaluate the binding ability of these compounds. Utilizing the Shapley additive explanation (SHAP) method, the 1855 bit has been identified as the most significant molecular fingerprint fragment. The findings propose that these six small molecules exhibit promising potential for targeting RIPK1 in associated diseases. Notably, the identification of Cpd-1 small molecule (ZINC000085897746) from the Musa acuminate highlights its natural product origin, warranting further attention and investigation.

更新日期：2023-11-15

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