A selectivity study on mTOR/PI3Kα inhibitors by homology modeling and 3D-QSAR

Area of Science:

• Biochemistry and Molecular Biology
• Cancer Research
• Computational Chemistry

Background:

• The PI3K/Akt/mTOR pathway is crucial for cell growth, survival, and proliferation.
• mTOR and PI3K are significant targets in cancer therapy due to their roles in cellular regulation.
• These kinases share homology in their active sites, posing challenges for selective inhibitor development.

Purpose of the Study:

• To accelerate the discovery of selective inhibitors targeting mTOR and PI3K for cancer treatment.
• To identify structural divergences in the active sites of mTOR and PI3Kα.
• To build predictive computational models for guiding inhibitor design.

Main Methods:

• Development of a homology model for mTOR.
• Identification of structural differences in active sites between mTOR and PI3Kα.
• Construction of two comparative molecular similarity index analyses (CoMSIA) models using 304 selective inhibitors.

Main Results:

• The homology model revealed structural divergence in the active sites of mTOR and PI3Kα.
• CoMSIA models demonstrated high predictive power for mTOR (q(2) = 0.658, r(pre)(2) = 0.839) and PI3Kα (q(2) = 0.540, r(pre)(2) = 0.719).
• Steric and electrostatic factors significantly influence selectivity towards mTOR versus PI3Kα, correlating with active site structural differences.

Conclusions:

• Structural divergence in active sites is key to achieving selectivity between mTOR and PI3Kα.
• Computational models provide a basis for designing selective mTOR/PI3Kα inhibitors.
• These findings support the development of targeted cancer therapies.