Computational insights into the binding of IN17 inhibitors to MELK

Matthew Harger, Ju Hyeon Lee, Brandon Walker, Juliana M. Taliaferro, Ramakrishna Edupuganti, Kevin N. Dalby, Pengyu Ren

Research output: Contribution to journalArticle

Abstract

The protein kinase MELK is an important kinase in cell signaling and has shown to be a promising anti-cancer target. Recent work has resulted in a novel small molecule scaffold targeting MELK, IN17. However, there has been little structural information or physical understanding of MELK-IN17 interactions. Using Tinker-OpenMM on GPUs, we have performed free energy simulations on MELK binding with IN17 and 11 derivatives. This series of studies provides structural insights into how substitution on IN17 leads to differences in complex structure and binding thermodynamics. In addition, this study serves as an assessment of the current capabilities of the AMOEBA forcefield, accelerated by GPU computing, to serve as a molecular-dynamics-based free energy simulation platform for lead optimization.

Original languageEnglish (US)
Article number151
JournalJournal of Molecular Modeling
Volume25
Issue number6
DOIs
StatePublished - Jun 1 2019

Fingerprint

inhibitors
Free energy
free energy
Cell signaling
Scaffolds
Protein Kinases
Molecular dynamics
Substitution reactions
Phosphotransferases
platforms
simulation
Lead
cancer
Thermodynamics
substitutes
molecular dynamics
Derivatives
proteins
Proteins
thermodynamics

Keywords

  • Free energy calculation
  • Kinase inhibitor
  • MELK
  • Molecular dynamics

ASJC Scopus subject areas

  • Catalysis
  • Computer Science Applications
  • Physical and Theoretical Chemistry
  • Organic Chemistry
  • Computational Theory and Mathematics
  • Inorganic Chemistry

Cite this

Harger, M., Lee, J. H., Walker, B., Taliaferro, J. M., Edupuganti, R., Dalby, K. N., & Ren, P. (2019). Computational insights into the binding of IN17 inhibitors to MELK. Journal of Molecular Modeling, 25(6), [151]. https://doi.org/10.1007/s00894-019-4036-1

Computational insights into the binding of IN17 inhibitors to MELK. / Harger, Matthew; Lee, Ju Hyeon; Walker, Brandon; Taliaferro, Juliana M.; Edupuganti, Ramakrishna; Dalby, Kevin N.; Ren, Pengyu.

In: Journal of Molecular Modeling, Vol. 25, No. 6, 151, 01.06.2019.

Research output: Contribution to journalArticle

Harger, M, Lee, JH, Walker, B, Taliaferro, JM, Edupuganti, R, Dalby, KN & Ren, P 2019, 'Computational insights into the binding of IN17 inhibitors to MELK', Journal of Molecular Modeling, vol. 25, no. 6, 151. https://doi.org/10.1007/s00894-019-4036-1
Harger, Matthew ; Lee, Ju Hyeon ; Walker, Brandon ; Taliaferro, Juliana M. ; Edupuganti, Ramakrishna ; Dalby, Kevin N. ; Ren, Pengyu. / Computational insights into the binding of IN17 inhibitors to MELK. In: Journal of Molecular Modeling. 2019 ; Vol. 25, No. 6.
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