Adhish Mazumder, Manjubala I
School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Mol Divers. 2025 Jul 22. doi: 10.1007/s11030-025-11297-1.
The Wnt/β-catenin signaling pathway is a key regulator of cellular activities and has implications for various diseases. This study explored the ability to predict the bioactivities of compounds against the peroxisome proliferator-activated receptor γ (PPARγ), paving the way to develop PPGBioPred, a user-friendly webserver to modulate this pathway. The research employs computational methodologies, particularly quantitative structure-activity relationship (QSAR) models, to understand the bioactivity of compounds. The study evaluated the efficacy of twelve categories of fingerprint descriptors for model development and used the Gini index to reveal the molecular features crucial for the studied bioactivity of PPARγ. The resulting high-performing models - achieving external R values of 0.57 (IC) and 0.62 (EC), and classification MCCs of 0.74 (IC) and 0.70 (EC) - are deployed on PPGBioPred, providing a robust and translational tool for virtual screening. These models contribute significantly to the understanding of the structure‒activity relationship of PPARγ and the ability to predict the bioactivities of certain chemical compounds against the aforementioned target. This study underscores the potential of computational methodologies in supplementing experimental research in drug discovery. These findings pave the way for the development of effective drugs targeting PPARγ, highlighting the potential of these proteins in the treatment of diseases affecting multiple organs.
Wnt/β-连环蛋白信号通路是细胞活动的关键调节因子,与多种疾病相关。本研究探索了预测化合物对过氧化物酶体增殖物激活受体γ(PPARγ)生物活性的能力,为开发PPGBioPred这一便于用户使用的网络服务器来调节该信号通路铺平了道路。该研究采用计算方法,特别是定量构效关系(QSAR)模型,来了解化合物的生物活性。研究评估了十二类指纹描述符在模型开发中的有效性,并使用基尼指数揭示对PPARγ所研究生物活性至关重要的分子特征。所得出的高性能模型(外部R值在抑制浓度(IC)方面达到0.57,在半数效应浓度(EC)方面达到0.62;分类马修斯相关系数(MCC)在IC方面为0.74,在EC方面为0.70)被应用于PPGBioPred,为虚拟筛选提供了一个强大且具有转化性的工具。这些模型对理解PPARγ的构效关系以及预测某些化合物针对上述靶点的生物活性能力有显著贡献。本研究强调了计算方法在补充药物发现实验研究方面的潜力。这些发现为开发针对PPARγ的有效药物铺平了道路,突出了这些蛋白质在治疗影响多个器官的疾病方面的潜力。