Literature DB >> 18685809

Molecular dynamics simulation study of PTP1B with allosteric inhibitor and its application in receptor based pharmacophore modeling.

Kavitha Bharatham1, Nagakumar Bharatham, Yong Jung Kwon, Keun Woo Lee.   

Abstract

Allosteric inhibition of protein tyrosine phosphatase 1B (PTP1B), has paved a new path to design specific inhibitors for PTP1B, which is an important drug target for the treatment of type II diabetes and obesity. The PTP1B1-282-allosteric inhibitor complex crystal structure lacks alpha7 (287-298) and moreover there is no available 3D structure of PTP1B1-298 in open form. As the interaction between alpha7 and alpha6-alpha3 helices plays a crucial role in allosteric inhibition, alpha7 was modeled to the PTP1B1-282 in open form complexed with an allosteric inhibitor (compound-2) and a 5 ns MD simulation was performed to investigate the relative orientation of the alpha7-alpha6-alpha3 helices. The simulation conformational space was statistically sampled by clustering analyses. This approach was helpful to reveal certain clues on PTP1B allosteric inhibition. The simulation was also utilized in the generation of receptor based pharmacophore models to include the conformational flexibility of the protein-inhibitor complex. Three cluster representative structures of the highly populated clusters were selected for pharmacophore model generation. The three pharmacophore models were subsequently utilized for screening databases to retrieve molecules containing the features that complement the allosteric site. The retrieved hits were filtered based on certain drug-like properties and molecular docking simulations were performed in two different conformations of protein. Thus, performing MD simulation with alpha7 to investigate the changes at the allosteric site, then developing receptor based pharmacophore models and finally docking the retrieved hits into two distinct conformations will be a reliable methodology in identifying PTP1B allosteric inhibitors.

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Year:  2008        PMID: 18685809     DOI: 10.1007/s10822-008-9229-0

Source DB:  PubMed          Journal:  J Comput Aided Mol Des        ISSN: 0920-654X            Impact factor:   3.686


  26 in total

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