Biologically Active Ligands for Yersinia Outer Protein H (YopH): Feature Based Pharmacophore Screening, Docking and Molecular Dynamics Studies

Title:Biologically Active Ligands for Yersinia Outer Protein H (YopH): Feature Based Pharmacophore Screening, Docking and Molecular Dynamics Studies

Volume: 17 Issue: 7

Author(s): Thangaraju Tamilvanan and Waheeta Hopper

Affiliation:

Keywords: Induced fit docking, MM-GBSA, molecular dynamics, pharmacophore, Yersinia pestis, YopH.

Abstract: Yersinia pestis, a Gram negative bacillus, spreads via lymphatic to lymph nodes and to all organs through the bloodstream, causing plague. Yersinia outer protein H (YopH) is one of the important effector proteins, which paralyzes lymphocytes and macrophages by dephosphorylating critical tyrosine kinases and signal transduction molecules. The purpose of the study is to generate a three-dimensional (3D) pharmacophore model by using diverse sets of YopH inhibitors, which would be useful for designing of potential antitoxin. In this study, we have selected 60 biologically active inhibitors of YopH to perform Ligand based pharmacophore study to elucidate the important structural features responsible for biological activity. Pharmacophore model demonstrated the importance of two acceptors, one hydrophobic and two aromatic features toward the biological activity. Based on these features, different databases were screened to identify novel compounds and these ligands were subjected for docking, ADME properties and Binding energy prediction. Post docking validation was performed using molecular dynamics simulation for selected ligands to calculate the Root Mean Square Deviation (RMSD) and Root Mean Square Fluctuation (RMSF). The ligands, ASN03270114, Mol_252138, Mol_31073 and ZINC04237078 may act as inhibitors against YopH of Y. pestis.

Cite this article as:

Tamilvanan Thangaraju and Hopper Waheeta, Biologically Active Ligands for Yersinia Outer Protein H (YopH): Feature Based Pharmacophore Screening, Docking and Molecular Dynamics Studies, Combinatorial Chemistry & High Throughput Screening 2014; 17 (7) . https://dx.doi.org/10.2174/1386207317666140211095137