Modeling and subtleties of K-Ras and Calmodulin interaction

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Abstract

K-Ras, one of the most common small GTPases of the cell, still presents many riddles, despite the intense efforts to unveil its mysteries. Such is the case of its interaction with Calmodulin, a small acidic protein known for its role as a calcium ion sensor. Although the interaction between these two proteins and its biological implications have been widely studied, a model of their interaction has not been performed. In the present work we analyse this intriguing interaction by computational means. To do so, both conventional molecular dynamics and scaled molecular dynamics have been used. Our simulations suggest a model in which Calmodulin would interact with both the hypervariable region and the globular domain of K-Ras, using a lobe to interact with each of them. According to the presented model, the interface of helixes α4 and α5 of the globular domain of K-Ras would be relevant for the interaction with a lobe of Calmodulin. These results were also obtained when bringing the proteins together in a step wise manner with the umbrella sampling methodology. The computational results have been validated using SPR to determine the relevance of certain residues. Our results demonstrate that, when mutating residues of the α4-α5 interface described to be relevant for the interaction with Calmodulin, the interaction of the globular domain of K-Ras with Calmodulin diminishes. However, it is to be considered that our simulations indicate that the bulk of the interaction would fall on the hypervariable region of K-Ras, as many more interactions are identified in said region. All in all our simulations present a suitable model in which K-Ras could interact with Calmodulin at membrane level using both its globular domain and its hypervariable region to stablish an interaction that leads to an altered signalling.

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Garrido, E., Lázaro, J., Jaumot, M., Agell, N., & Rubio-Martinez, J. (2018). Modeling and subtleties of K-Ras and Calmodulin interaction. PLoS Computational Biology, 14(10). https://doi.org/10.1371/journal.pcbi.1006552

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