Modeling MEK4 Kinase Inhibitors through Perturbed Electrostatic Potential (ESP) Charges

Rama K. Mishra*, Kristine K. Deibler, Matthew R. Clutter, Purav Pankaj Vagadia, Matthew O'Connor, Gary E. Schiltz, Raymond Bergan, Karl A. Scheidt

*Corresponding author for this work

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

MEK4, mitogen-activated protein kinase kinase 4, is overexpressed and induces metastasis in advanced prostate cancer lesions. However, the value of MEK4 as an oncology target has not been pharmacologically validated because selective chemical probes targeting MEK4 have not been developed. With advances in both computer and biological high-throughput screening selective chemical entities can be discovered. Structure-based quantitative structure activity relationship (QSAR) modeling often fails to generate accurate models due to poor alignment of training sets containing highly diverse compounds. Here we describe a highly predictive, non-alignment based robust QSAR model based on a dataset of strikingly diverse MEK4 inhibitors. We computed the electrostatic potential (ESP) charges using DFT formalism of the donor and acceptor atoms of the ligands and hinge residues. Novel descriptors were then generated from the perturbation of the charge densities of the donor and acceptor atoms and were used to model a diverse set of 84 compounds, from which we built a robust predictive model.

Original languageEnglish (US)
JournalJournal of Chemical Information and Modeling
DOIs
StateAccepted/In press - Jan 1 2019

Keywords

  • Charge Perturbation
  • CoMFA
  • DFT
  • ESP Charges
  • EVA
  • HQSAR
  • MEK4
  • MLR

ASJC Scopus subject areas

  • Chemistry(all)
  • Chemical Engineering(all)
  • Computer Science Applications
  • Library and Information Sciences

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