Sampling Performance of Multiple Independent Molecular Dynamics Simulations of an RNA Aptamer

Using multiple independent simulations instead of one long simulation has been shown to improve the sampling performance attained with the molecular dynamics (MD) simulation method. However, it is generally not known how long each independent simulation should be, how many independent simulations should be used, or to what extent either of these factors affects the overall sampling performance achieved for a given system. The goal of the present study was to assess the sampling performance of multiple independent MD simulations, where each independent simulation begins from a different initial molecular conformation. For this purpose, we used an RNA aptamer that is 25 nucleotides long as a case study. The initial conformations of the aptamer are derived from six de novo predicted 3D structures. Each of the six de novo predicted structures is energy minimized in solution and equilibrated with MD simulations at high temperature. Ten conformations from these six high-temperature equilibration runs are selected as initial conformations for further simulations at ambient temperature. In total, we conducted 60 independent MD simulations, each with a duration of 100 ns, to study the conformation and dynamics of the aptamer. For each group of 10 independent simulations that originated from a particular de novo predicted structure, we evaluated the potential energy distribution of the RNA and used recurrence quantification analysis to examine the sampling of RNA conformational transitions. To assess the impact of starting from different de novo predicted structures, we computed the density of structure projection on principal components to compare the regions sampled by the different groups of ten independent simulations. The recurrence rate and dependence of initial conformation among the groups were also compared. We stress the necessity of using different initial configurations as simulation starting points by showing long simulations from different initial structures suffer from being trapped in different states. Finally, we summarized the sampling efficiency for the complete set of 60 independent simulations and determined regions of under-sampling on the potential energy landscape. The results suggest that conducting multiple independent simulations using a diverse set of de novo predicted structures is a promising approach to achieve sufficient sampling. This approach avoids undesirable outcomes, such as the problem of the RNA aptamer being trapped in a local minimum. For others wishing to conduct multiple independent simulations, the analysis protocol presented in this study is a guide for examining overall sampling and determining if more simulations are necessary for sufficient sampling

Structural basis for amino acid transport by the CAT family of SLC7 transporters

Amino acids play essential roles in cell biology as regulators of metabolic pathways. Arginine in particular is a major signalling molecule inside the cell, being a precursor for both l-ornithine and nitric oxide (NO) synthesis and a key regulator of the mTORC1 pathway. In mammals, cellular arginine availability is determined by members of the solute carrier (SLC) 7 family of cationic amino acid transporters. Whereas CAT-1 functions to supply cationic amino acids for cellular metabolism, CAT-2A and -2B are required for macrophage activation and play important roles in regulating inflammation. Here, we present the crystal structure of a close homologue of the mammalian CAT transporters that reveals how these proteins specifically recognise arginine. Our structural and functional data provide a model for cationic amino acid transport in mammalian cells and reveals mechanistic insights into proton-coupled, sodium-independent amino acid transport in the wider APC superfamily