Computational hybrid framework integrating clinical-mutation profiling and physics-based simulations to predict...

Bruton tyrosine kinase (BTK) is a non-receptor tyrosine kinase crucial for relaying signals from the B cell antigen receptor (BCR) in cancerous B lymphocytes. It has been reported that mutations in this protein cause resistance to various covalent and non-covalent drugs. Therefore, we employed a computational genomic mutation screening strategy, combined with molecular simulation, to assess the impact of clinical substitutions on the structure and binding of ARQ 531(Nemtabrutinib), the most potent BTK inhibitor. Using various machine learning algorithms, 62 clinical mutations were identified as deleterious among the 82, while 11 were classified as highly destabilizing using graph signature-based methods. We selected the top mutations that are deleterious and highly destabilizing, which include L408P, Y476D, M477R, C481R, C481Y, and L542P. Molecular docking analysis revealed no significant variations in the bonding network, while molecular simulation results revealed local changes only in the dynamic behavior. The resemblance to the wild type and mutants in certain PCs (principal components) implies that specific structural aspects or dynamics remain preserved despite the mutation, and the single energetic minimum indicates a robust and dominant structural state, reinforcing that these mutations affect the protein locally but not globally. Finally, the total binding free energy (TBE) calculations revealed that ARQ531 exhibits broadly conserved binding energetics across clinically observed BTK mutants, with select variants (notably C481 substitutions) showing moderately enhanced stabilization relative to the wild type. These findings confirm that ARQ 531 remains a significant investigational therapy specifically for overcoming drug resistance in multiple leukemias and B-cell malignancies and can serve as a starting point for designing more robust and effective BTK inhibitors.