Small Molecule Amiloride Modulates Oncogenic RNA Alternative Splicing to Devitalize Human Cancer Cells

Alternative splicing involves differential exon selection of a gene transcript to generate mRNA and protein isoforms with structural and functional diversity. Abnormal alternative splicing has been shown to be associated with malignant phenotypes of cancer cells, such as chemo-resistance and invasive activity. Screening small molecules and drugs for modulating RNA splicing in human hepatocellular carcinoma cell line Huh-7, we discovered that amiloride, distinct from four pH-affecting amiloride analogues, could “normalize” the splicing of BCL-X, HIPK3 and RON/MISTR1 transcripts. Our proteomic analyses of amiloride-treated cells detected hypo-phosphorylation of splicing factor SF2/ASF, and decreased levels of SRp20 and two un-identified SR proteins. We further observed decreased phosphorylation of AKT, ERK1/2 and PP1, and increased phosphorylation of p38 and JNK, suggesting that amiloride treatment down-regulates kinases and up-regulates phosphatases in the signal pathways known to affect splicing factor protein phosphorylation. These amiloride effects of “normalized” oncogenic RNA splicing and splicing factor hypo-phosphorylation were both abrogated by pre-treatment with a PP1 inhibitor. Global exon array of amiloride-treated Huh-7 cells detected splicing pattern changes involving 584 exons in 551 gene transcripts, many of which encode proteins playing key roles in ion transport, cellular matrix formation, cytoskeleton remodeling, and genome maintenance. Cellular functional analyses revealed subsequent invasion and migration defects, cell cycle disruption, cytokinesis impairment, and lethal DNA degradation in amiloride-treated Huh-7 cells. Other human solid tumor and leukemic cells, but not a few normal cells, showed similar amiloride-altered RNA splicing with devitalized consequence. This study thus provides mechanistic underpinnings for exploiting small molecule modulation of RNA splicing for cancer therapeutics

A Network-Based Multi-Target Computational Estimation Scheme for Anticoagulant Activities of Compounds

BACKGROUND: Traditional virtual screening method pays more attention on predicted binding affinity between drug molecule and target related to a certain disease instead of phenotypic data of drug molecule against disease system, as is often less effective on discovery of the drug which is used to treat many types of complex diseases. Virtual screening against a complex disease by general network estimation has become feasible with the development of network biology and system biology. More effective methods of computational estimation for the whole efficacy of a compound in a complex disease system are needed, given the distinct weightiness of the different target in a biological process and the standpoint that partial inhibition of several targets can be more efficient than the complete inhibition of a single target. METHODOLOGY: We developed a novel approach by integrating the affinity predictions from multi-target docking studies with biological network efficiency analysis to estimate the anticoagulant activities of compounds. From results of network efficiency calculation for human clotting cascade, factor Xa and thrombin were identified as the two most fragile enzymes, while the catalytic reaction mediated by complex IXa:VIIIa and the formation of the complex VIIIa:IXa were recognized as the two most fragile biological matter in the human clotting cascade system. Furthermore, the method which combined network efficiency with molecular docking scores was applied to estimate the anticoagulant activities of a serial of argatroban intermediates and eight natural products respectively. The better correlation (r = 0.671) between the experimental data and the decrease of the network deficiency suggests that the approach could be a promising computational systems biology tool to aid identification of anticoagulant activities of compounds in drug discovery. CONCLUSIONS: This article proposes a network-based multi-target computational estimation method for anticoagulant activities of compounds by combining network efficiency analysis with scoring function from molecular docking

Deletion of the N-terminus of SF2/ASF Permits RS-Domain-Independent Pre-mRNA Splicing

Serine/arginine-rich (SR) proteins are essential splicing factors with one or two RNA-recognition motifs (RRMs) and a C-terminal arginine- and serine-rich (RS) domain. SR proteins bind to exonic splicing enhancers via their RRM(s), and from this position are thought to promote splicing by antagonizing splicing silencers, recruiting other components of the splicing machinery through RS-RS domain interactions, and/or promoting RNA base-pairing through their RS domains. An RS domain tethered at an exonic splicing enhancer can function as a splicing activator, and RS domains play prominent roles in current models of SR protein functions. However, we previously reported that the RS domain of the SR protein SF2/ASF is dispensable for in vitro splicing of some pre-mRNAs. We have now extended these findings via the identification of a short inhibitory domain at the SF2/ASF N-terminus; deletion of this segment permits splicing in the absence of this SR protein's RS domain of an IgM pre-mRNA substrate previously classified as RS-domain-dependent. Deletion of the N-terminal inhibitory domain increases the splicing activity of SF2/ASF lacking its RS domain, and enhances its ability to bind pre-mRNA. Splicing of the IgM pre-mRNA in S100 complementation with SF2/ASF lacking its RS domain still requires an exonic splicing enhancer, suggesting that an SR protein RS domain is not always required for ESE-dependent splicing activation. Our data provide additional evidence that the SF2/ASF RS domain is not strictly required for constitutive splicing in vitro, contrary to prevailing models for how the domains of SR proteins function to promote splicing