Literature DB >> 20538496

Understanding the stereospecific interactions of 3-deoxyphosphatidylinositol derivatives with the PTEN phosphatase domain.

Qin Wang1, Yang Wei, Madhusoodanan Mottamal, Mary F Roberts, Goran Krilov.   

Abstract

PTEN is an important control element of PI3K/AKT signaling involved in controlling the processes of embryonic development, cell migration and apoptosis. While its dysfunction is implicated in a large fraction of cancers, PTEN activity in the same pathway may also contribute to metabolic syndromes such as diabetes. In those cases, selective inhibitors of PTEN may be useful. A new class of chiral PTEN inhibitors based on the 3-deoxy-phosphatidylinositol derivatives was recently identified (Wang et al. [17]). However, lack of detailed understanding of protein-ligand interactions has hampered efforts to develop effective agonists or antagonists of PTEN. Here, we use computational modeling to characterize the interactions of the diverse 3-deoxyphosphatidylinositol inhibitors with the PTEN protein. We show that, while each of the compounds binds with the inositol headgroup inserting into the proposed active site of the PTEN phosphatase domain, hydrogen bonding restrictions lead to distinct binding geometries for ligand pairs of opposite chirality. We furthermore demonstrate that the binding modes differ primarily in the orientation of acyl tails of the ligands and that the activity of the compounds is primarily controlled by the effectiveness of tail-protein contacts. These findings are confirmed by binding affinity calculations which are in good agreement with experiment. Finally, we show that while more potent d-series ligands bind in a manner similar to that of the native substrate, an alternate hydrophobic pocket suitable for binding the opposite chirality l-series inhibitors exists, offering the possibility of designing highly selective PTEN-targeting compounds.

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Year:  2010        PMID: 20538496      PMCID: PMC3072415          DOI: 10.1016/j.jmgm.2010.05.004

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN: 1093-3263            Impact factor:   2.518


  41 in total

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