Conformational changes below the Tm: molecular dynamics studies of the thermal pretransition of ribonuclease A

Conserved amino acid networks modulate discrete functional properties in an enzyme superfamily

In this work, we applied the sequence-based statistical coupling analysis approach to characterize conserved amino acid networks important for biochemical function in the pancreatic-type ribonuclease (ptRNase) superfamily. This superfamily-wide analysis indicates a decomposition of the RNase tertiary structure into spatially distributed yet physically connected networks of co-evolving amino acids, termed sectors. Comparison of this statistics-based description with new NMR experiments data shows that discrete amino acid networks, termed sectors, control the tuning of distinct functional properties in different enzyme homologs. Further, experimental characterization of evolutionarily distant sequences reveals that sequence variation at sector positions can distinguish homologs with a conserved dynamic pattern and optimal catalytic activity from those with altered dynamics and diminished catalytic activities. Taken together, these results provide important insights into the mechanistic design of the ptRNase superfamily, and presents a structural basis for evolutionary tuning of function in functionally diverse enzyme homologs.

Stability and folding of amphibian ribonuclease A superfamily members in comparison with mammalian homologues

Comparative studies on homologous proteins can provide knowledge on how limited changes in the primary structure find their expression in large effects on catalytic activity, stability or the folding behavior. For more than half a century, members of the ribonuclease A superfamily have been the subject of a myriad of studies on protein folding and stability. Both the unfolding and refolding kinetics as well as the structure of several folding intermediates of ribonuclease A have been characterized in detail. Moreover, the RNA-degrading activity of these enzymes provides a basis for their cytotoxicity, which renders them potential tumor therapeutics. Because amphibian ribonuclease A homologues evade the human ribonuclease inhibitor, they emerged as particularly promising candidates. Interestingly, the amphibian ribonuclease A homologues investigated to date are more stable than the mammalian homologues. Nevertheless, despite the generation of numerous genetically engineered variants, knowledge of the folding of amphibian ribonuclease A homologues remains rather limited. An exception is onconase, a ribonuclease A homologue from Rana pipiens, which has been characterized in detail. This review summarizes the data on the unfolding and refolding kinetics and pathways, as well on the stability of amphibian ribonuclease A homologues compared with those of ribonuclease A, the best known member of this superfamily.

A temperature-dependent conformational change of NADH oxidase from Thermus thermophilus HB8

Using molecular dynamics simulations and steady-state fluorescence spectroscopy, we have identified a conformational change in the active site of a thermophilic flavoenzyme, NADH oxidase from Thermus thermophilus HB8 (NOX). The enzyme's far-UV circular dichroism spectrum, intrinsic tryptophan fluorescence, and apparent molecular weight measured by dynamic light scattering varied little between 25 and 75°C. However, the fluorescence of the tightly bound FAD cofactor increased approximately fourfold over this temperature range. This effect appears not to be due to aggregation, unfolding, cofactor dissociation, or changes in quaternary structure. We therefore attribute the change in flavin fluorescence to a temperature-dependent conformational change involving the NOX active site. Molecular dynamics simulations and the effects of mutating aromatic residues near the flavin suggest that the change in fluorescence results from a decrease in quenching by electron transfer from tyrosine 137 to the flavin.

Modeling conformational ensembles of slow functional motions in Pin1-WW

Protein-protein interactions are often mediated by flexible loops that experience conformational dynamics on the microsecond to millisecond time scales. NMR relaxation studies can map these dynamics. However, defining the network of inter-converting conformers that underlie the relaxation data remains generally challenging. Here, we combine NMR relaxation experiments with simulation to visualize networks of inter-converting conformers. We demonstrate our approach with the apo Pin1-WW domain, for which NMR has revealed conformational dynamics of a flexible loop in the millisecond range. We sample and cluster the free energy landscape using Markov State Models (MSM) with major and minor exchange states with high correlation with the NMR relaxation data and low NOE violations. These MSM are hierarchical ensembles of slowly interconverting, metastable macrostates and rapidly interconverting microstates. We found a low population state that consists primarily of holo-like conformations and is a “hub” visited by most pathways between macrostates. These results suggest that conformational equilibria between holo-like and alternative conformers pre-exist in the intrinsic dynamics of apo Pin1-WW. Analysis using MutInf, a mutual information method for quantifying correlated motions, reveals that WW dynamics not only play a role in substrate recognition, but also may help couple the substrate binding site on the WW domain to the one on the catalytic domain. Our work represents an important step towards building networks of inter-converting conformational states and is generally applicable.

Proteins in their native state can adopt a plethora of shapes, or conformations; this conformational plasticity is critical for regulation and function in many systems. However, it has remained difficult to determine what these different conformations look like at the atomic level. We present a novel way to use Nuclear Magnetic Resonance, Molecular Dynamics Simulations, and Markov State Models to uncover a map of this plethora of conformations that is consistent with the available data. We applied this method to study the intrinsic dynamics used in substrate binding by the WW domain of the Pin1 proline cis-trans isomerase and found that the NMR data were best explained by two slowly-interconverting sets of many metastable conformations rather than two distinct macrostates. Substantial value is added to the NMR data by our method since it provides a kinetic “map” of conformational changes consistent with the observed relaxation data. Such an approach, in combination with information theory, helped us to identify specific conformational changes that might couple substrate binding at the Pin1 WW domain to the catalytic subunit.