Ligand-based 3-D pharmacophore generation and molecular docking of mTOR kinase inhibitors

Abstract

The 3-D structure of the human mTOR kinase domain was modeled based on the crystal structure of PI3Kγ using comparative modeling methods, and the ATP-binding site of mTOR was characterized. The mTOR kinase 3-D model structure is similar to the structure of the PI3Kγ kinase domain, and exhibits great similarity to PI3Kγ at the active site of the kinase. Pharmacophore generation, the docking of mTOR inhibitors, and molecular dynamics (MD) simulations of mTOR-inhibitor docked complexes were carried out in this work. The best pharmacophore model generated from 27 ATP-competitive mTOR inhibitors comprised two hydrogen-bond acceptors, one aromatic ring, and one hydrophobic feature. These 27 inhibitors were docked into the ATP-binding site comprising the DFG motif, and the interactions in each protein-inhibitor complex were characterized. Mapping the pharmacophore model onto the docked inhibitors explained the specificity of the features of the pharmacophore and how they were arranged inside the active site of mTOR kinase. MD studies revealed important structural features, such as the large hydrophobic pocket "HP" and hydrophilic pocket "A1," and the solvent-exposed hydrophilic pocket "A2" at the active site of mTOR. Our results provide structural models of mTOR-inhibitor complexes and clues that should aid in the design of better mTOR kinase inhibitors.

Discovering new mTOR inhibitors for cancer treatment through virtual screening methods and in vitro assays

“…Distance analyses suggest that the hydrogen bond between 13 and the side chain of Val2240 is conserved during 10 ns MD simulations ( Figure S4a ). Previous studies demonstrated the hydrogen bond between inhibitor and Val2240 was necessary for mTOR inhibitory activity 23 24 25 , which was consistent with our analysis. The hydrogen bond between 13 and the carboxyl oxygen atom of Asp2195 is maintained for the first 5 ns in our simulations and occasionally disappears after 5 ns ( Figure S4b ), suggesting this hydrogen bond is not stable in water.…”

Predicting mTOR Inhibitors with a Classifier Using Recursive Partitioning and Naïve Bayesian Approaches

“…The models exhibit potential to predict inhibitors that are not included in the training set. Similar work was also performed by Karunakar Tanneeru and coworkers, which resulted in four features pharmacophore model (two hydrogen bond acceptors, a hydrophobic center and an aromatic feature) based on 27 ATP-competitive mTOR inhibitors [21]. A disadvantage of 3D-QSAR or SAR models for mTOR inhibitors is the use of a series of compounds based on solely scaffold.…”

General Ser/Thr Kinases Pharmacophore Approach for Selective Kinase Inhibitors Search as Exemplified by Design of Potent and Selective Aurora A Inhibitors

“…A number of attempts have been done to construct a pharmacophore model for various serine–threonine kinase inhibitors. For example, pharmacophore for STPK inhibitors of tuberculosis , for mTor kinase inhibitors , for Aurora B inhibitors , for Aurora A inhibitors and for B‐Raf inhibitors was developed. All these works were devoted to selected kinase of serine–threonine family, but we surmised that there are a number of common features of all serine–threonine inhibitors so it would be possible to construct a general pharmacophore model which subsequently could be optimized for specific kinds of serine–threonine kinase.…”