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Open Access Publications from the University of California

Molecular Recognition Modeling: Free Energy, Protein Dynamics and Unbinding Pathways

  • Author(s): You, Wanli
  • Advisor(s): Chang, Chia-en A
  • et al.

Molecular recognition is fundamentally important in biological chemistry. Nowadays, with the rapid development of computational technology and algorithm, molecular modeling has become a powerful tool in studying molecular recognition, such as exploring molecular interactions and understanding biological dynamic processes, making significant contributions to modern biology and drug discovery. The state-of-the-art techniques of computational chemistry and molecular modeling can be applied to study a wide range of chemical and biological systems of interest. This enables us to study structural details at the atomic level and obtain chemical/biological information which is not available by experimental measurements. This dissertation project focused on modeling the recognition mechanisms of biomolecules and their conjugated ligands. Multiple computational techniques, such as molecular dynamics simulation, enhanced sampling methods and free energy calculation were applied. The model systems included signaling domains (BRCT domain), kinase (p38 kinase), enzyme system (TRPS) and small biomolecular system (cyclodextrin). The details of protein-ligand interactions, including both enthalpic and entropic contribution within protein domain-phosphopeptide systems were investigated, based on which new inhibitors were proposed. Several enhanced sampling methods like accelerated molecular dynamics simulation, pathway search guided by internal motions (PSIM) and umbrella sampling, were applied to explore the dissociation pathway of kinase-ligand systems and the motions of kinase during dissociation process were studied both thermodynamically and kinetically, protein conformational rearrangement was found to differentiate slow and fast unbinding inhibitors, casting light on high efficacy inhibitor design. Furthermore, using full structural molecular modeling, we explored how the position of a single proton can change the overall protein dynamics and further activate or inactivate enzyme catalysis, elucidating the catalytic mechanism of TRPS. In addition, we performed systematically evaluation to the performance of umbrella sampling, investigated the influence of subtle changes in the dissociation pathways and conformational sampling methods that provide the initial conformations, paving way for future improvement of umbrella sampling. This project studies the details of receptor-ligand interaction and provides a more complete picture of molecular recognition.

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