Protein effects in non-heme iron enzyme catalysis: insights from multiscale models

Many non-heme iron enzymes have similar sets of ligands but still catalyze widely different reactions. A key question is, therefore, the role of the protein in controlling reactivity and selectivity. Examples from multiscale simulations, primarily QM/MM, of both mono- and binuclear non-heme iron enzymes are used to analyze the stability of these models and what they reveal about the protein effects. Consistent results from QM/MM modeling are the importance of the hydrogen bond network to control reactivity and electrostatic stabilization of electron transfer from second-sphere residues. The long-range electrostatic effects on reaction barriers are small for many systems. In the systems where large electrostatic effects have been reported, these lead to higher barriers. There is thus no evidence of any significant long-range electrostatic effects contributing to the catalytic efficiency of non-heme iron enzymes. However, the correct evaluation of electrostatic contributions is challenging, and the correlation between calculated residue contributions and the effects of mutation experiments is not very strong. The largest benefits of QM/MM models are thus the improved active-site geometries, rather than the calculation of accurate energies. Reported differences in mechanistic predictions between QM and QM/MM models can be explained by differences in hydrogen bonding patterns in and around the active site. Correctly constructed cluster models can give results with similar accuracy as those from multiscale models, but the latter reduces the risk of drawing the wrong mechanistic conclusions based on incorrect geometries and are preferable for all types of modeling, even when using very large QM parts.     

Statistical properties of the variation at linked microsatellite loci: implications for the history of human Y chromosomes [published erratum appears in Mol Biol Evol 1997 Mar;14(3):354]

It has recently been suggested that observed levels of variation at microsatellite loci can be used to infer patterns of selection in genomes and to assess demographic history. In order to evaluate the feasibility of these suggestions it is necessary to know something about how levels of variation at microsatellite loci are expected to fluctuate due simply to stochasticity in the processes of mutation and inheritance (genetic sampling). Here we use recently derived properties of the stepwise mutation model to place confidence intervals around the variance in repeat score that is expected at mutation-drift equilibrium and outline a statistical test for whether an observed value differs significantly from expectation. We also develop confidence intervals for the time course of the buildup of variation following a complete elimination of variation, such as might be caused by a selective sweep or an extreme population bottleneck. We apply these methods to the variation observed at human Y-specific microsatellites. Although a number of authors have suggested the possibility of a very recent sweep, our analyses suggest that a sweep or extreme bottleneck is unlikely to have occurred anytime during the last approximately 74,000 years. To generate this result we use a recently estimated mutation rate for microsatellite loci of 5.6 x 10(-4) along with the variation observed at autosomal microsatellite loci to estimate the human effective population size. This estimate is 18,000, implying an effective number of 4,500 Y chromosomes. One important general conclusion to emerge from this study is that in order to reject mutation-drift equilibrium at a set of linked microsatellite loci it is necessary to have an unreasonably large number of loci unless the observed variance is far below that expected at mutation-drift equilibrium.