Identification of ALK5 inhibitor via structure-based virtual screening and ADMET prediction

Abstract

<div><p></p><p>TGF-β plays a critical role in the initiation and progression of fibrosis in various organ systems such as kidney, heart, lung and liver. TGF-β and its receptors (ALK5 and TβR II) are able to control the cellular growth and promote several biological responses. To date, many pharmaceutical companies have employed virtual screening to identify potent inhibitors against ALK5. Nevertheless, none of these studies had involved the <i>in silico</i> ADMET evaluation and Raccoon filtering. In our experiment, all 57423 molecules were downloaded from TCM database and were filtered and converted to PDBQT formats by Raccoon software. Then 24 189 structures were run through AutoDock Vina in PyRx 0.8, 164 molecules were selected and further evaluated by ADMET Predictor 6.5, and 56 structures were selected and docked by Glide 6.2. Finally, the top 10 hits were identified as promising oral ALK5 inhibitors according to their Glide scores. The Glide scores of the best two compounds, 40686 and 33534, were −10.75 and −10.30 kcal/mol, respectively. This research provides a set of combined and detailed virtual screening protocol and is helpful for explaining the mechanism of receptor–ligand interactions.</p></div