A distal regulatory region of a class I human histone deacetylase

Histone deacetylases (HDACs) are key enzymes in epigenetics and important drug targets in cancer biology. Whilst it has been established that HDACs regulate many cellular processes, far less is known about the regulation of these enzymes themselves. Here, we show that HDAC8 is allosterically regulated by shifts in populations between exchanging states. An inactive state is identified, which is stabilised by a range of mutations and resembles a sparsely-populated state in equilibrium with active HDAC8. Computational models show that the inactive and active states differ by small changes in a regulatory region that extends up to 28 Å from the active site. The regulatory allosteric region identified here in HDAC8 corresponds to regions in other class I HDACs known to bind regulators, thus suggesting a general mechanism. The presented results pave the way for the development of allosteric HDAC inhibitors and regulators to improve the therapy for several disease states.

The Role of Post-translational Modifications on the Energy Landscape of Huntingtin N-Terminus

Huntington disease is a neurodegenerative disease characterized by a polymorphic tract of polyglutamine repeats in exon 1 of the huntingtin protein, which is thought to be responsible for protein aggregation and neuronal death. The polyglutamine tract is preceded by a 17-residue sequence that is intrinsically disordered. This region is subject to phosphorylation, acetylation and other post-translational modifications in vivo, which modulate its secondary structure, aggregation and, subcellular localization. We used Molecular Dynamics simulations with a novel Hamiltonian-replica-exchange-based enhanced sampling method, SWISH, and an optimal combination of water and protein force fields to study the effects of phosphorylation and acetylation as well as cross-talk between these modifications on the huntingtin N-terminus. The simulations, validated by circular dichroism, were used to formulate a mechanism by which the modifications influence helical conformations. Our findings have implications for understanding the structural basis underlying the effect of PTMs in the aggregation and cellular properties of huntingtin.

Assessment of the model refinement category in CASP12

We here report on the assessment of the model refinement predictions submitted to the 12th Experiment on the Critical Assessment of Protein Structure Prediction (CASP12). This is the fifth refinement experiment since CASP8 (2008) and, as with the previous experiments, the predictors were invited to refine selected server models received in the regular (nonrefinement) stage of the CASP experiment. We assessed the submitted models using a combination of standard CASP measures. The coefficients for the linear combination of Z-scores (the CASP12 score) have been obtained by a machine learning algorithm trained on the results of visual inspection. We identified eight groups that improve both the backbone conformation and the side chain positioning for the majority of targets. Albeit the top methods adopted distinctively different approaches, their overall performance was almost indistinguishable, with each of them excelling in different scores or target subsets. What is more, there were a few novel approaches that, while doing worse than average in most cases, provided the best refinements for a few targets, showing significant latitude for further innovation in the field.