Clustering and Sampling of the c-Met Conformational Space: A Computational Drug Discovery Study.

BACKGROUND: c-Met kinase plays a critical role in a myriad of human cancers, and a massive scientific work was devoted to design more potent inhibitors. OBJECTIVE: In this study, 16 molecular dynamics simulations of different complexes of potent c-Met inhibitors with U-shaped binding mode were carried out regarding the dynamic ensembles to design novel potent inhibitors. METHODS: A cluster analysis was performed, and the most representative frame of each complex was subjected to the structure-based pharmacophore screening. The GOLD docking program investigated the interaction energy and pattern of output hits from the virtual screening. The most promising hits with the highest scoring values that showed critical interactions with c-Met were presented for ADME/Tox analysis. RESULTS: The screening yielded 45,324 hits that all of them were subjected to the docking studies and 10 of them with the highest-scoring values having diverse structures were presented for ADME/Tox analyses. CONCLUSION: The results indicated that all the hits shared critical Pi-Pi stacked and hydrogen bond interactions with Tyr1230 and Met1160 respectively.

Prediction of cytotoxic activity of a series of 1H-pyrrolo[2,3-b]pyridine derivatives as possible inhibitors of c-Met using molecular fingerprints.

Cancer is a leading cause of death all over the world. HGF/MET signaling pathway is involved in many cancers and its inhibition has great potential as an effective therapeutic intervention. A series of 1H-pyrrolo [2,3-b]pyridine derivatives has recently been identified with cytotoxic activity, and most of them exhibited considerable potencies with IC50 values under 10 µM. The present study was carried out with the specific aim to shed light upon the quantitative structure activity relationship (QSAR) to design and predict the activity of new potent inhibitors using molecular fingerprints and some 2D and 3D descriptors. The built model was statistically significant in terms of R2 = 0.90 and R2pred = 0.91 values. Fingerprint PubchemFP759 (1-chloro-2-methylbenzene) was the most effective fragment in the biological activity and just appeared in the most active compound 7j with a pIC50 value of 8.0. A similarity search study was applied based on compounds 7c and 17e, with reported inhibitory activity against c-Met kinase, which showed that also other compounds could possess similar effects against c-Met enzyme. The most promising compound 7g-cl was subjected to docking and molecular dynamics simulation. Two hydrogen bonds between Lys1110, Met1160, and 7g-cl were stable during the equilibrium time range. The suggested modifications might be considered in future studies to design more efficient anticancer agents.