Abstract：
Identification of compounds to modulate NADPH metabolism is crucial for understanding complex diseases and developing effective therapies. However, the complex nature of NADPH metabolism poses challenges in achieving this goal. In this study, we proposed a novel strategy named NADPHnet to predict key proteins and drug-target interactions related to NADPH metabolism via network-based methods. Different from traditional approaches only focusing on one single protein, NADPHnet could screen compounds to modulate NADPH metabolism from a comprehensive view. Specifically, NADPHnet identified key proteins involved in regulation of NADPH metabolism using network-based methods, and characterized the impact of natural products on NADPH metabolism using a combined score, NADPH-Score. NADPHnet demonstrated a broader applicability domain and improved accuracy in the external validation set. This approach was further employed along with molecular docking to identify 27 compounds from a natural product library, 6 of which exhibited concentration-dependent changes of cellular NADPH level within 100 μM, with Oxyberberine showing promising effects even at 10 μM. Mechanistic and pathological analyses of Oxyberberine suggest potential novel mechanisms to affect diabetes and cancer. Overall, NADPHnet offers a promising method for prediction of NADPH metabolism modulation and advances drug discovery for complex diseases.
摘要：
鉴定调节NADPH代谢的化合物对于理解复杂疾病和开发有效疗法至关重要。然而,NADPH代谢的复杂性对实现这一目标提出了挑战。在这项研究中,我们提出了一种名为NADPHnet的新策略,通过基于网络的方法预测与NADPH代谢相关的关键蛋白和药物-靶标相互作用.不同于传统的方法只关注一种单一的蛋白质，NADPHnet可以从全面的角度筛选调节NADPH代谢的化合物。具体来说,NADPHnet使用基于网络的方法鉴定了参与调节NADPH代谢的关键蛋白，并使用组合评分表征天然产物对NADPH代谢的影响，NADPH评分。NADPHnet在外部验证集中展示了更广泛的适用性领域和改进的准确性。该方法与分子对接一起进一步用于从天然产品库中鉴定27种化合物，其中6个在100μM内表现出细胞NADPH水平的浓度依赖性变化，即使在10μM时，氧连素也显示出有希望的效果。氧连素的机制和病理分析提示了影响糖尿病和癌症的潜在新机制。总的来说,NADPHnet为预测NADPH代谢调节提供了一种有前途的方法，并促进了复杂疾病的药物发现。
