The H2A.B histone is a highly evolving vertebrate specific variant of the H2A histone family. It has been implicated in increased gene... Show moreThe H2A.B histone is a highly evolving vertebrate specific variant of the H2A histone family. It has been implicated in increased gene expression, and experiments have shown that incorporation of H2A.B into nucleosomes results in more extended structures with fewer wrapped DNA base pairs. To study the molecular mechanisms of H2A.B, we have performed a series of conventional and enhanced sampling molecular dynamics simulation of H2A.B and canonical H2A containing nucleosomes.Results of adaptively biased molecular simulations show that substitution of canonical H2A with H2A.B results in geometrical changes such as unwrapping of 10 to 15 base pairs of DNA on each side of the nucleosome and an increase in the diameter and radius of gyration, which is in agreement with previous AFM, FRET, and SAXS experiments. DNA unwinding is energetically favorable in H2A.B containing compared to canonical nucleosomes, while in both systems we observe a wide range of sampling over various structures of DNA. H3 histone tails excluded simulations, show the importance and effect of N-terminal residues of H3 histones on attachment of DNA at the entry/exit sites to nucleosome protein core. Clustering and hydrogen bond analysis suggest that introduction of H2A.B to nucleosome systems triggers mechanisms leading to rearrangement of hydrogen bond network which may influence the pattern and intensity of interactions between DNA-protein and protein-protein complexes. Show less
Most proteins reduce the complexity of atomic motion to stable and coherent structures. Molecular dynamics (MD) has provided swaths of... Show moreMost proteins reduce the complexity of atomic motion to stable and coherent structures. Molecular dynamics (MD) has provided swaths of trajectory data of proteins. We analyze these trajectories using classical stochastic signal analysis, well established and utilized by engineers. Linear systems analysis operates to uncover linearities given an input and output signal. The coherence function says an input and output are linearly related if and only if the coherence equals one. Analyzing protein motion in the frequency domain allows us to extract a frequency function relating the modes of motion as determined by atomic power spectra. Motivated by biochemistry, we analyze classical interactions like hydrogen bonds and salt bridges and find they act like a linear system, or effective spring. We test our analysis on two protein systems: crambin and the Mu Opioid Receptor (MOR). We extend our results to all pairwise interaction and determine coherent communities of atoms within the MOR. We present various community detection algorithms and demonstrate their validity using common metrics in MD. Identifying rigid and tightly correlated regions of the protein offers great potential in coarse graining protein structure and understanding protein motion. Show less
