Distinct functional and conformational states of the human lymphoid tyrosine phosphatase catalytic domain can be targeted by choice of the inhibitor chemotype

  • Dušica Vidović
  • Yuli Xie
  • Alison Rinderspacher
  • Shi-Xian Deng
  • Donald W. Landry
  • Caty Chung
  • Deborah H. Smith
  • Lutz Tautz
  • Stephan C. Schürer


The lymphoid tyrosine phosphatase (LYP), encoded by the PTPN22 gene, has recently been identified as a promising drug target for human autoimmunity diseases. Like the majority of protein-tyrosine phosphatases LYP can adopt two functionally distinct forms determined by the conformation of the WPD-loop. The WPD-loop plays an important role in the catalytic dephosphorylation by protein-tyrosine phosphatases. Here we investigate the binding modes of two chemotypes of small molecule LYP inhibitors with respect to both protein conformations using computational modeling. To evaluate binding in the active form, we built a LYP protein structure model of high quality. Our results suggest that the two different compound classes investigated, bind to different conformations of the LYP phosphatase domain. Binding to the closed form is facilitated by an interaction with Asp195 in the WPD-loop, presumably stabilizing the active conformation. The analysis presented here is relevant for the design of inhibitors that specifically target either the closed or the open conformation of LYP in order to achieve better selectivity over phosphatases with similar binding sites.


Protein tyrosine phosphorylation PTPN22 LYP Drug design Docking Homology modeling 



Lymphoid tyrosine phosphatase


Protein tyrosine kinases


Protein tyrosine phosphatases


T-cell receptor


C-terminal Src tyrosine kinase


Growth factor receptor-bound protein


Molecular Library Screening Center Network


National Institutes of Health


Izothiazolidinone inhibitor


Protein tyrosine phosphatase 1B


Structure activity relationship


Standard precision


Extra precision


Induced-fit docking



This work was in part supported by the grant MLSCN U54 HG003914 and 1R21CA132121 (to L.T.) from the National Institutes of Health. We also acknowledge resources of the University of Miami Center for Computational Science (CCS).


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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Dušica Vidović
    • 1
  • Yuli Xie
    • 2
  • Alison Rinderspacher
    • 2
  • Shi-Xian Deng
    • 2
  • Donald W. Landry
    • 2
  • Caty Chung
    • 1
  • Deborah H. Smith
    • 3
  • Lutz Tautz
    • 4
  • Stephan C. Schürer
    • 1
    • 5
  1. 1.Center for Computational ScienceUniversity of MiamiMiamiUSA
  2. 2.Department of MedicineColumbia UniversityNew YorkUSA
  3. 3.Department of Physiology and Cellular BiophysicsColumbia UniversityNew YorkUSA
  4. 4.Infectious and Inflammatory Disease CenterSanford-Burnham Medical Research InstituteLa JollaUSA
  5. 5.Department of Pharmacology, Miller School of MedicineUniversity of MiamiMiamiUSA

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