Identification of novel PHGDH inhibitors based on computational investigation: an all-in-one combination strategy to develop potential anti-cancer candidates - Xu, Yujing; Yang, Zhe; Yang, Jinrong; Gan, Chunchun; Qin, Nan; Wei, Xiaopeng (Frontiers in Pharmacology, 2024)
Objective： Biological studies have elucidated that phosphoglycerate dehydrogenase (PHGDH) is the rate-limiting enzyme in the serine synthesis pathway in humans, which abnormally expresses in numerous cancers. The inhibition of the PHGDH activity is thought to be an attractive approach for novel anti-cancer therapy. Development of structurally diverse novel PHGDH inhibitors with highly efficient and low-toxicity is a good drug discovery strategy. Methods: A ligand-based 3D-QSAR pharmacophore model was developed using HypoGen algorithm methodology of Discovery Studio. The selected pharmacophore model was further validated by test set validation, cost analysis, Fischer randomization validation and was then used as a 3D query to screen compound libraries with various chemical scaffolds. The estimated activity, drug-likeness, molecular docking, growing scaffold and molecular dynamics simulation were applied in combination in order to further narrow the number of virtual hits. Results: The potential candidates against PHGDH were screened based on estimated activity，docking scores，predictive ADME/T properties and molecular dynamics simulation. Conclusion: Finally, an all-in-one combination was employed successfully to design and develop three potential anti-cancer candidates.