Abstract
Well-tempered metadynamics (wT-metaD) simulations using path collective variables (CVs) have been successfully applied in recent years to explore conformational transitions in protein kinases and other biomolecular systems. While this methodology has the advantage of describing the transitions with a limited number of predefined path CVs, it requires as an input a reference path connecting the initial and target states of the system. It is desirable to automate the path generation using approaches that do not rely on the choice of geometric CVs to describe the transition of interest. To this end, we developed an approach that couples essential dynamics sampling with wT-metaD simulations. We used this newly developed procedure to explore the activation mechanism of Abl1 kinase and compute the associated free energy barriers. Through these simulations, we identified a three-step mechanism for the activation that involved two metastable intermediates that possessed a partially open activation loop and differed primarily in the “in” or “out” conformation of the aspartate residue of the DFG motif. One of these states is similar to a conformation that was detected in previous spectroscopic studies of Abl1 kinase, albeit its mechanistic role in the activation was hitherto not well understood. The present study establishes its intermediary role in the activation and predicts a rate-determining free energy barrier of 13.8 kcal/mol that is in good agreement with previous experimental and computational estimates. Overall, our study demonstrates the usability of essential dynamics sampling as a path CV in wT-metaD to conveniently study conformational transitions and accurately calculate the associated barriers.
Highlights
Some of the key challenges in the targeted therapy of cancer include identifying protein targets that can be selectively inhibited, accounting for the conformational variability in the protein targets and understanding the molecular basis for treatment-induced drug resistance
By employing a path sampled from a short essential dynamics sampling (EDS) as one path CV24 and the distance from the input EDS path as another in wT-metaD simulations, this method offers enhanced variational flexibility by allowing for the possibility of exploring activation pathways that could be more favorable than the input EDS path
In order to identify the essential subspace of the protein that spans large amplitude collective motions associated with the inactive → active transition, the normalized cumulative variance was plotted against the number of principal components (PCs) of the target active state for one of the trajectories
Summary
Some of the key challenges in the targeted therapy of cancer include identifying protein targets that can be selectively inhibited, accounting for the conformational variability in the protein targets and understanding the molecular basis for treatment-induced drug resistance. Addressing these challenges requires detailed mechanistic insights into the conformational transitions of proteins in their native and mutant forms by means of experimental and computational methodologies. A hybrid model, which employed explicit solvent to propagate conformational dynamics and implicit solvent to compute free energies, coupled with a pH replica exchange scheme was used recently to map the conformational landscape of a tyrosine kinase protein.[12]
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