Rongfeng Liu

TL;DR: DC-S100, which was discovered by pharmacophore- and docking-based virtual screening, was identified as the hit compound of SET7 inhibitor and can serve as leads for further investigation as SET7 inhibitors and the chemical toolkits for functional biology studies ofSET7.

TL;DR: A novel, structure-based VS approach that uses machine-learning algorithms trained on the priori structure and activity knowledge to predict the likelihood that a compound is aBRD4i based on its binding pattern with BRD4 is demonstrated.

TL;DR: This study demonstrates the development of potent DOT1L inhibitors with novel scaffolds by combining structure-based virtual screening with biochemical analyses and predicted the binding modes of DC_L115 through molecular docking analysis and found that the inhibitor competitively occupies the binding site of S-adenosylmethionine.

TL;DR: This work aims to discover novel inhibitors targeting the menin-MLL interface with virtual screening and establishes structure-based molecular docking and ligand-based pharmacophore models that show a remarkable ability to retrieve known active ligands from decoy molecules.

TL;DR: Zhang et al. as discussed by the authors investigated the role of protein arginine methyltransferase 1 (PRMT1) expression level and its correlations to clinicopathological factors and prognosis in clear cell renal cell carcinoma (ccRCC) patients.