Identification of STAT1 and STAT3 specific inhibitors using comparative virtual screening and docking validation

PLoS One. 2015 Feb 24;10(2):e0116688. doi: 10.1371/journal.pone.0116688. eCollection 2015.


Signal transducers and activators of transcription (STATs) facilitate action of cytokines, growth factors and pathogens. STAT activation is mediated by a highly conserved SH2 domain, which interacts with phosphotyrosine motifs for specific STAT-receptor contacts and STAT dimerization. The active dimers induce gene transcription in the nucleus by binding to a specific DNA-response element in the promoter of target genes. Abnormal activation of STAT signaling pathways is implicated in many human diseases, like cancer, inflammation and auto-immunity. Searches for STAT-targeting compounds, exploring the phosphotyrosine (pTyr)-SH2 interaction site, yielded many small molecules for STAT3 but sparsely for other STATs. However, many of these inhibitors seem not STAT3-specific, thereby questioning the present modeling and selection strategies of SH2 domain-based STAT inhibitors. We generated new 3D structure models for all human (h)STATs and developed a comparative in silico docking strategy to obtain further insight into STAT-SH2 cross-binding specificity of a selection of previously identified STAT3 inhibitors. Indeed, by primarily targeting the highly conserved pTyr-SH2 binding pocket the majority of these compounds exhibited similar binding affinity and tendency scores for all STATs. By comparative screening of a natural product library we provided initial proof for the possibility to identify STAT1 as well as STAT3-specific inhibitors, introducing the 'STAT-comparative binding affinity value' and 'ligand binding pose variation' as selection criteria. In silico screening of a multi-million clean leads (CL) compound library for binding of all STATs, likewise identified potential specific inhibitors for STAT1 and STAT3 after docking validation. Based on comparative virtual screening and docking validation, we developed a novel STAT inhibitor screening tool that allows identification of specific STAT1 and STAT3 inhibitory compounds. This could increase our understanding of the functional role of these STATs in different diseases and benefit the clinical need for more drugable STAT inhibitors with high specificity, potency and excellent bioavailability.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Amino Acid Sequence
  • Binding Sites
  • Biological Products / chemistry
  • Biological Products / pharmacology
  • High-Throughput Screening Assays
  • Humans
  • Molecular Docking Simulation*
  • Molecular Sequence Data
  • Protein Binding
  • STAT1 Transcription Factor / antagonists & inhibitors*
  • STAT1 Transcription Factor / chemistry
  • STAT3 Transcription Factor / antagonists & inhibitors*
  • STAT3 Transcription Factor / chemistry
  • Small Molecule Libraries / chemistry
  • Small Molecule Libraries / pharmacology*


  • Biological Products
  • STAT1 Transcription Factor
  • STAT1 protein, human
  • STAT3 Transcription Factor
  • STAT3 protein, human
  • Small Molecule Libraries

Grant support

This publication was supported by grants UMO-2012/07/B/NZ1/02710 (to HB), UMO-2012/07/N/NZ2/01359 (to MS) from National Science Centre Poland, and No 128 from the Poznan Supercomputer Centre (PCSS) (to MS). This work was supported by the KNOW RNA Research Centre in Poznań (No. 01/KNOW2/2014) and in part by PL-Grid Infrastructure. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.