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Updated: Jan 25, 2026

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
Published on: January 26, 2024
Computational insights into the binding of IN17 inhibitors to MELK
Matthew Harger1, Ju-Hyeon Lee2, Brandon Walker1
1Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, 78712, USA.
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.
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