STUDY OF INHIBITOR BINDING TO BIOLOGICAL MACROMOLECULES USING ATOMISTIC MODELING AND SIMULATION

Abstract

Mammalian target of rapamycin (mTOR) is a large (-250 kDa) naturally occurring biological molecule that plays a critical role in controlling cell growth. Using adenosine triphosphate (ATP) as a substrate, mTOR tags target proteins with phosphate groups (phosphorylation) to turn on their activity. Deregulation of mTOR has been linked to diseases such as cancer and diabetes, therefore in recent times a lot of attention has been paid to developing mTOR inhibitors having high efficacy and specificity. While ATPcompetitive inhibitors have shown promising results in experimental studies, a high resolution picture of ligand binding to mTOR that can guide design of better drugs has been missing. Recently, a low resolution (3.5 A) crystal structure of the mTOR protein complex was captured 1, which might provide a starting point to study ligand binding in mTOR. However, major challenges remain in providing a structural basis for the binding and action of various ligands to mTOR. These include the lack of suitable techniques for quantitatively studying structural changes in such a large protein complex (- 1500 amino acids), and the lack of information on protein conformation changes and flexibility in the presence and absence of ligands. Further, the recently solved low resolution crystal structure has many unresolved (missing atoms) protein segments. In this study, we complete the missing structural information in the low resolution crystal structure and set up a high resolution fully solvated atomistic model of the mTOR protein. Further, as a step towards incorporating thermally induced conformational changes, we have created a molecular dynamics model for the solvated mTOR complex in the absence and presence of its natural ATP substrate. Finally, we report a novel analysis technique which we have developed to quantify the conformational and dynamic changes taking place in mTOR during ATP binding. We have successfully validated this technique by testing on amyloid beta for which deformation path is well-known.