Discovery and Development of ATP-Competitive mTOR Inhibitors Using Computational Approaches

Title:Discovery and Development of ATP-Competitive mTOR Inhibitors Using Computational Approaches

Volume: 23 Issue: 29

Author(s): Yao Luo and Ling Wang*

Affiliation:

• Pre-Incubator for Innovative Drugs & Medicine, School of Bioscience and Bioengineering, South China University of Technology, Guangzhou 510006,China

Keywords: Molecular docking, drug discovery, homology modeling, molecular dynamics, pharmacophore, machine learning, virtual screening.

Abstract: The mammalian target of rapamycin (mTOR) is a central controller of cell growth, proliferation, metabolism, and angiogenesis. This protein is an attractive target for new anticancer drug development. Significant progress has been made in hit discovery, lead optimization, drug candidate development and determination of the three-dimensional (3D) structure of mTOR. Computational methods have been applied to accelerate the discovery and development of mTOR inhibitors helping to model the structure of mTOR, screen compound databases, uncover structure-activity relationship (SAR) and optimize the hits, mine the privileged fragments and design focused libraries. Besides, computational approaches were also applied to study protein-ligand interactions mechanisms and in natural product-driven drug discovery. Herein, we survey the most recent progress on the application of computational approaches to advance the discovery and development of compounds targeting mTOR. Future directions in the discovery of new mTOR inhibitors using computational methods are also discussed.

Cite this article as:

Luo Yao and Wang Ling*, Discovery and Development of ATP-Competitive mTOR Inhibitors Using Computational Approaches, Current Pharmaceutical Design 2017; 23 (29) . https://dx.doi.org/10.2174/1381612823666170710150604