Functional features defining the efficacy of cholesterol-conjugated, self-deliverable, chemically modified siRNAs.

Progress in oligonucleotide chemistry has produced a shift in the nature of siRNA used, from formulated, minimally modified siRNAs, to unformulated, heavily modified siRNA conjugates. The introduction of extensive chemical modifications is essential for conjugate-mediated delivery. Modifications have a significant impact on siRNA efficacy through interference with recognition and processing by RNAi enzymatic machinery, severely restricting the sequence space available for siRNA design. Many algorithms available publicly can successfully predict the activity of non-modified siRNAs, but the efficiency of the algorithms for designing heavily modified siRNAs has never been systematically evaluated experimentally. Here we screened 356 cholesterol-conjugated siRNAs with extensive modifications and developed a linear regression-based algorithm that effectively predicts siRNA activity using two independent datasets. We further demonstrate that predictive determinants for modified and non-modified siRNAs differ substantially. The algorithm developed from the non-modified siRNAs dataset has no predictive power for modified siRNAs and vice versa. In the context of heavily modified siRNAs, the introduction of chemical asymmetry fully eliminates the requirement for thermodynamic bias, the major determinant for non-modified siRNA efficacy. Finally, we demonstrate that in addition to the sequence of the target site, the accessibility of the neighboring 3' region significantly contributes to siRNA efficacy.

SIRT2- and NRF2-Targeting Thiazole-Containing Compound with Therapeutic Activity in Huntington's Disease Models.

There are currently no disease-modifying therapies for the neurodegenerative disorder Huntington's disease (HD). This study identified novel thiazole-containing inhibitors of the deacetylase sirtuin-2 (SIRT2) with neuroprotective activity in ex vivo brain slice and Drosophila models of HD. A systems biology approach revealed an additional SIRT2-independent property of the lead-compound, MIND4, as an inducer of cytoprotective NRF2 (nuclear factor-erythroid 2 p45-derived factor 2) activity. Structure-activity relationship studies further identified a potent NRF2 activator (MIND4-17) lacking SIRT2 inhibitory activity. MIND compounds induced NRF2 activation responses in neuronal and non-neuronal cells and reduced production of reactive oxygen species and nitrogen intermediates. These drug-like thiazole-containing compounds represent an exciting opportunity for development of multi-targeted agents with potentially synergistic therapeutic benefits in HD and related disorders.

Genome-wide decoding of hierarchical modular structure of transcriptional regulation by cis-element and expression clustering.

MOTIVATION: A holistic approach to the study of cellular processes is identifying both gene-expression changes and regulatory elements promoting such changes. Cellular regulatory processes can be viewed as transcriptional modules (TMs), groups of coexpressed genes regulated by groups of transcription factors (TFs). We set out to devise a method that would identify TMs while avoiding arbitrary thresholds on TM sizes and number. METHOD: Assuming that gene expression is determined by TFs that bind to the gene's promoter, clustering of genes based on TF binding sites (cis-elements) should create gene groups similar to those obtained by gene expression clustering. Intersections between the expression and cis-element-based gene clusters reveal TMs. Statistical significance assigned to each TM allows identification of regulatory units of any size. RESULTS: Our method correctly identifies the number and sizes of TMs on simulated datasets. We demonstrate that yeast experimental TMs are biologically relevant by comparing them with MIPS and GO categories. Our modules are in statistically significant agreement with TMs from other research groups. This work suggests that there is no preferential division of biological processes into regulatory units; each degree of partitioning exhibits a slice of biological network revealing hierarchical modular organization of transcriptional regulation.

PromoSer: A large-scale mammalian promoter and transcription start site identification service.

Proximal promoters have a major impact on transcriptional regulation. Studies of the sequence-based nature of this regulation usually require collection of proximal promoter sequences for large sets of co-regulated genes. We report a newly implemented web service that facilitates extraction of user specified regions around the transcription start site of all annotated human, mouse or rat genes. The transcription start sites have been identified computationally by considering alignments of a large number of partial and full-length mRNA sequences to genomic DNA, with provision for alternative promoters. The service is publicly available at http://biowulf.bu.edu/zlab/PromoSer/.