An understanding of protein-protein interactions is crucial in order to explain the cellular functions of living systems. However, the long timescales and high dimensionality of biological processes lead to insufficient conformational sampling and present major challenges in studying these systems. In principle, Markov state models (MSM) could provide a powerful tool to study these protein-protein interactions. Since an MSM is a master equation model, it can describe the entire dynamics of a system. There are, however, many possible issues that could arise due to lack of sampling that could undermine the quality of the information extracted from MSMs in the case of protein-protein complexation. For this work, MSMs are utilized to characterize the association and dissociation of the barnase-barstar protein complex. In particular, dimensionality reduction using the time-lagged independent component analysis (TICA) and reweighting of multi-thermodynamic ensembles such as with the transition-based reweighting analysis method (TRAM) enables us to overcome sampling challenges and to efficiently extract kinetically relevant information in order to study binding interactions.

Markov state model analysis of the protein binding interactions of the Barnase-Barstar complex

2019 Spring National Meeting

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.