Integrative computational pipeline for identifying binding-enhancing mutations targeting the MBD2–p66α interaction: Implications for therapeutic applications

Abstract

This study presents a comprehensive computational pipeline to identify and evaluate potential stabilizing mutations for the coiled-coil protein–protein interaction between methyl-CpG-binding domain protein 2 (MBD2) and transcriptional repressor p66-alpha (p66α). The pipeline begins with the BeAtMuSiC program, which employs statistical potentials derived from known structures to predict candidate stabilizing mutations at the protein–protein interface. Out of 565 potential mutations, 10 single-point mutations (K149I, K163I, A237F, K149L, K149M, K163L, R166M, R166W, K163F, and E155L) with the highest binding affinity were selected for further evaluation using rigorous alchemical free energy calculations. These alchemical simulations conducted using the double-system/single-box method, predicted changes in binding free energy (ΔΔG) upon mutation while maintaining charge neutrality. The Crooks–Gaussian intersection technique was employed to analyze the results, identifying K149I, K149L, and K163L as potentially enhancing binding affinity the most, while mutations like K163F, A237F, and E155L were predicted to destabilize the interaction significantly. Complementary conventional Molecular Dynamics Simulations provided further support for the alchemical predictions, revealing decreased flexibility, increased contacts, and more compact structures for the predicted stabilizing mutants compared with the wild-type complex. Additionally, Molecular Mechanics Poisson–Boltzmann Surface Area (MM/PBSA) binding free energy calculations were performed, and their results were consistent with the direction of free energy change predicted by the alchemical approach. This multifaceted computational pipeline, combining predictive methods, alchemical simulations, and conventional analyses, offers valuable insights into modulating the binding affinity of the MBD2–p66α coiled-coil interaction. The identified stabilizing mutations can create numerous opportunities across biotechnology, biomedical research, and synthetic biology.