Huntington's disease (HD) symptoms are driven to a large extent by dysfunction of the basal ganglia circuitry. HD patients exhibit reduced striatal phoshodiesterase 10 (PDE10) levels. Using HD mouse models that exhibit reduced PDE10, we demonstrate the benefit of pharmacologic PDE10 inhibition to acutely correct basal ganglia circuitry deficits. PDE10 inhibition restored corticostriatal input and boosted cortically driven indirect pathway activity. Cyclic nucleotide signaling is impaired in HD models, and PDE10 loss may represent a homeostatic adaptation to maintain signaling. Elevation of both cAMP and cGMP by PDE10 inhibition was required for rescue. Phosphoproteomic profiling of striatum in response to PDE10 inhibition highlighted plausible neural substrates responsible for the improvement. Early chronic PDE10 inhibition in Q175 mice showed improvements beyond those seen with acute administration after symptom onset, including partial reversal of striatal deregulated transcripts and the prevention of the emergence of HD neurophysiological deficits. VIDEO ABSTRACT.

Human Immunodeficiency Virus 1 uses for entry into host cells a receptor (CD4) and one of two co-receptors (CCR5 or CXCR4). Recently, a new class of antiretroviral drugs has entered clinical practice that specifically bind to the co-receptor CCR5, and thus inhibit virus entry. Accurate prediction of the co-receptor used by the virus in the patient is important as it allows for personalized selection of effective drugs and prognosis of disease progression. We have investigated whether it is possible to predict co-receptor usage accurately by analyzing the amino acid sequence of the main determinant of co-receptor usage, i.e., the third variable loop V3 of the gp120 protein. We developed a two-level machine learning approach that in the first level considers two different properties important for protein-protein binding derived from structural models of V3 and V3 sequences. The second level combines the two predictions of the first level. The two-level method predicts usage of CXCR4 co-receptor for new V3 sequences within seconds, with an area under the ROC curve of 0.937±0.004. Moreover, it is relatively robust against insertions and deletions, which frequently occur in V3. The approach could help clinicians to find optimal personalized treatments, and it offers new insights into the molecular basis of co-receptor usage. For instance, it quantifies the importance for co-receptor usage of a pocket that probably is responsible for binding sulfated tyrosine.

Boundaries between euchromatic and heterochromatic regions until now have been associated with chromatin-opening activities. Here, we identified an unexpected role for histone deacetylation in this process. Significantly, the histone deacetylase (HDAC) Rpd3 was necessary for boundary formation in Saccharomyces cerevisiae . rpd3 Δ led to silent information regulator (SIR) spreading and repression of subtelomeric genes. In the absence of a known boundary factor, the histone acetyltransferase complex SAS-I, rpd3 Δ caused inappropriate SIR spreading that was lethal to yeast cells. Notably, Rpd3 was capable of creating a boundary when targeted to heterochromatin. Our data suggest a mechanism for boundary formation whereby histone deacetylation by Rpd3 removes the substrate for the HDAC Sir2, so that Sir2 no longer can produce O-acetyl-ADP ribose (OAADPR) by consumption of NAD + in the deacetylation reaction. In essence, OAADPR therefore is unavailable for binding to Sir3, preventing SIR propagation.

The mitotic regulator Pin1 plays an important role in protein quality control and age-related medical conditions such as Alzheimer disease and Parkinson disease. Although its cellular role has been thoroughly investigated during the past decade, the molecular mechanisms underlying its function remain elusive. We provide evidence for interactions between the two domains of Pin1. Several residues displayed unequivocal peak splits in nuclear magnetic resonance spectra, indicative of two different conformational states in equilibrium. Pareto analysis of paramagnetic relaxation enhancement data demonstrates that the two domains approach each other upon addition of a nonpeptidic ligand. Titration experiments with phosphorylated peptides monitored by fluorescence anisotropy and chemical shift perturbation indicate that domain interactions increase Pin1's affinity toward peptide ligands. We propose this interplay of the domains and ligands to be a general mechanism for a large class of two-domain proteins.

BackgroundHuman Immunodeficiency Virus 1 enters host cells through interaction of its V3 loop (which is part of the gp120 protein) with the host cell receptor CD4 and one of two co-receptors, namely CCR5 or CXCR4. Entry inhibitors binding the CCR5 co-receptor can prevent viral entry. As these drugs are only available for CCR5-using viruses, accurate prediction of this so-called co-receptor tropism is important in order to ensure an effective personalized therapy. With the development of next-generation sequencing technologies, it is now possible to sequence representative subpopulations of the viral quasispecies.ResultsHere we present T-CUP 2.0, a model for predicting co-receptor tropism. Based on our recently published T-CUP model, we developed a more accurate and even faster solution. Similarly to its predecessor, T-CUP 2.0 models co-receptor tropism using information of the electrostatic potential and hydrophobicity of V3-loops. However, extracting this information from a simplified structural vacuum-model leads to more accurate and faster predictions. The area-under-the-ROC-curve (AUC) achieved with T-CUP 2.0 on the training set is 0.968±0.005 in a leave-one-patient-out cross-validation. When applied to an independent dataset, T-CUP 2.0 has an improved prediction accuracy of around 3% when compared to the original T-CUP.ConclusionsWe found that it is possible to model co-receptor tropism in HIV-1 based on a simplified structure-based model of the V3 loop. In this way, genotypic prediction of co-receptor tropism is very accurate, fast and can be applied to large datasets derived from next-generation sequencing technologies. The reduced complexity of the electrostatic modeling makes T-CUP 2.0 independent from third-party software, making it easy to install and use.