Energetics, pathways and dynamics in Src tyrosine kinase protein conformational changes.

摘要

Advanced computational methods are applied to study the energetics, atomistic pathways and dynamics in the conformational activation of Src tyrosine kinase, an enzyme playing important roles in cellular signaling and implicated in several types of human cancer.;First, we begin by exploring the ligand binding specificity of Src Homology 2 (SH2) domains, one major regulatory domain of Src kinase activity. By applying a potential of mean force free energy simulations method with restraining potentials, we calculate the absolute binding affinities between five representative SH2 domains and five peptides. For three of the five SH2 domains, our computational results rank the native peptides as the most preferred binding motif. For the remaining two SH2 domains, high affinity binding motifs other than the native peptides are identified. This study illustrate that computational methods provide a powerful complement to experiments in trying to elucidate complex protein-protein interactions.;We then proceed to investigate a large-scale conformational change associated with the activation of c-Src tyrosine kinase: the opening of the activation loop and rotation of alpha-C helix near the catalytic site. The inactive-to-active conformational transition of the catalytic domain of human c-Src tyrosine kinase is characterized using the string method with swarms-of-trajectories with all-atom explicit solvent molecular dynamics simulations. This large conformational change is found to occur in two main steps in which the activation loop opens first, followed by the rotation of the alpha-C helix. The computed potential of mean force free energy profile along the activation pathway displays a local minimum, which allows the identification of an intermediate state. These results show that the string method with swarms-of-trajectories is an effective technique to characterize complex and slow conformational transitions in large biomolecular systems.;Next, the theoretical framework combining the string method with the Markovian milestoning method is applied to the flipping of the highly conserved and catalytically important DFG motif located in the activation loop. We obtain a reasonable atomistic pathway for Src tyrosine kinase DFG-flip which exhibits very similar features seen in the free MD simulations of the DFG-flip of related Abl kinase. Free energy profiles along pathway computed by mean force calculation and by Markovian milestoning consistently show a stepwise motion for the seemingly simple DFG-flip. We find that DFG flipping is coordinated with the rotation of the alpha-C helix, suggesting the three separate motions, namely the opening of the activation loop, the rotation of the alpha-C helix, and the flipping of DFG motif, may all be dynamically coupled. A comparison of the free energy profile with Asp404 protonated and deprotonated shows that protonation plays a role in facilitating the DFG-flip by stabilizing the DFG-out conformation.;Finally, we present our attempt to find the most probable folding path of the 35-residue villin headpiece subdomain (HP35). The converged pathway, represented by 61 discrete images, fully characterizes the mechanism of HP35 folding. The three helices in HP35 exhibit distinct patterns of formation, and each is formed at a different stage in the whole folding process. The free energy along the folding pathway is computed and roughly two major energy barriers are observed which divide the folding into three states. The biggest folding energy barrier is estimated to be 4.1 kcal/mol and the rate-limiting step of folding appears to be the formation of an aromatic core. This three-state folding mechanism is consistent with previous experimental and computational studies. Markov states model (MSM) along pathway is then built to estimate the folding transition path time and good Markovian behavior is observed in present model.;Taken together, studies presented in the thesis highlight the importance of using computer models and molecular simulations to understand the interplay between the structures, pathways, energetics and dynamics in complex biomolecular systems.