We have characterized the structural dynamics of a chloroplast signal recognition particle (SRP) and its stability under various conditions using atomistic molecular dynamics simulations. The chloroplast signal recognition pathway provides a method whereby light-harvesting proteins (LHCPs) can be inserted into the thylakoid membrane. In a photosynthetic organism, most proteins are synthesized outside of the thylakoids. Consequently, these light harvesting proteins must possess a “flag”, usually an N-terminal amino acid sequence, which can help aid targeting to the thylakoids. The particular proteins that can recognize these amino acid signal sequence are called signal recognition proteins or SRPs. One of the particular SRPs associated with targeting in the chloroplast is the cpSRP43. Additionally, cpSRP54 is a GTPase that has the capacity to increase the targeting efficiency of cpSRP43 when bound to the cpSRP43 peptide. To observe their movements at the atomic level, we used modeling techniques and molecular dynamics to simulate the structural dynamics of the cpSRP43 and the cpSRP43/cpSRP54 complex. These computational models allow us to obtain a highly detailed perspective on the conformational landscape of these proteins. The models are generated by employing a novel combination of multiple techniques of molecular modeling, docking, and all-atom molecular dynamics. The models are both atomistic and dynamic, so we can observe how a protein changes its conformation over time at an unprecedented level of details. Particularly, we were able to induce the movement of particular domains to observe how the conformation changes over time due to changes in the environment. We use a collective variable based technique to pick particular protein domains and move these domains towards or away from each other. The observations made from these equilibrium and nonequilibrium simulations are not only important in gaining a unique perspective on photosynthetic pathways, but can also be applied to a number of analogous biological systems.<br/>

Modeling the atomistic structure and dynamics of the chloroplast signal recognition particles

254th National Meeting (2017)

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