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Details for the selection of physicochemical properties from AAIndex database. (DOC 31 kb

Expression of the Ufm1 system was induced by ER stress.

<p><b>A.</b> RT-PCR results of HCT116 and HepG2 cells treated with TG (1 µM for 16 hours) and TM (10 µM for 16 hours). The results represented mean ± SEM, p value <0.01 (marked by *). The inserts in Fig. 2A showed the results of Xbp-1 splicing assays. “u” indicated the unspliced form of Xbp-1, while “s” is the spliced form. <b>B.</b> Immunoblotting of the cell lysates of HCT116 and HepG2 treated with TG and TM. Specific Ufm1 conjugates were marked by arrowheads, and the non-specific 70 kD band was indicated by a star. “Long exp.” was long exposure of the blot, while “Short exp.” was short exposure of the blot in Enhanced Chemiluminescence (ECL).</p

Enhancing the Enrichment of Pharmacophore-Based Target Prediction for the Polypharmacological Profiles of Drugs

PharmMapper is a web server for drug target identification by reversed pharmacophore matching the query compound against an annotated pharmacophore model database, which provides a computational polypharmacology prediction approach for drug repurposing and side effect risk evaluation. But due to the inherent nondiscriminative feature of the simple fit scores used for prediction results ranking, the signal/noise ratio of the prediction results is high, posing a challenge for predictive reliability. In this paper, we improved the predictive accuracy of PharmMapper by generating a ligand–target pairwise fit score matrix from profiling all the annotated pharmacophore models against corresponding ligands in the original complex structures that were used to extract these pharmacophore models. The matrix reflects the noise baseline of fit score distribution of the background database, thus enabling estimation of the probability of finding a given target randomly with the calculated ligand–pharmacophore fit score. Two retrospective tests were performed which confirmed that the probability-based ranking score outperformed the simple fit score in terms of identification of both known drug targets and adverse drug reaction related off-targets

Knockdown of the Ufm1 system resulted in activation of UPR.

<p><b>A.</b> Up-regulation of ER chaperone proteins and CHOP in U2OS cells with knockdown of the Ufm1 system. U2OS cells were infected with lentiviral shRNAs, selected with puromycin (1.5 µg/ml). Cell lysates were collected after 6-day incubation and subject to immunoblotting with indicated antibodies. Knockdown of the Ufm1 components were confirmed by immunoblotting. <b>B.</b> Immunostaining of PDI in Uba5 and Ufc1 knockdown cells. C. Immunostaining of PDI in C53/LZAP and RCAD/Ufl1 knockdown cells. U2OS cells were subjected to immunostaining of PDI,. Knockdown of Uba5 was confirmed by Uba5 staining, while knockdown of RCAD/Ufl1 and C53/LZAP was confirmed by C53 staining. The images were acquired by Zeiss Axio Observer D1 and Axiovision software.</p

The effect of the UPR pathways on the expression of the Ufm1 system.

<p><b>A.</b> Immunoblotting of MEF cell lysates using Ufm1, Uba5, RCAD/Ufl1 and C53/LZAP antibodies. GAPDH was used as a loading control. Relative ratios of proteins were measured against GAPDH using Image J software. <b>B.</b> The mRNA levels of Ufm1, Uba5, RCAD/Ufl1 and C53/LZAP in wild-type and Xbp-1^−/− MEF cells that were treated with ER stress-inducing agents (TG, 0.5 µM for 16 hour; TM, 10 µM for 16 hours; and BFA, 0.5 µg/ml for 16 hours). <b>C.</b> The mRNA levels of Ufm1, Uba5, RCAD/Ufl1 and C53/LZAP in wild-type and PERK^−/− MEF cells that were treated with ER stress-inducing agents. The results represented mean ± SD. *p value <0.01.</p

SimG: An Alignment Based Method for Evaluating the Similarity of Small Molecules and Binding Sites

In this study, a Gaussian volume overlap and chemical feature based molecular similarity metric was devised, and a downhill simplex searching was carried out to evaluate the corresponding similarity. By representing the shapes of both the candidate small molecules and the binding site with chemical features and comparing the corresponding Gaussian volumes overlaps, the active compounds could be identified. These two aspects compose the proposed method named SimG which supports both structure-based and ligand-based strategies. The validity of the proposed method was examined by analyzing the similarity score variation between actives and decoys as well as correlation among distinct reference methods. A retrospective virtual screening test was carried out on DUD data sets, demonstrating that the performance of structure-based shape matching virtual screening in DUD data sets is substantially dependent on some physical properties, especially the solvent-exposure extent of the binding site: The enrichments of targets with less solvent-exposed binding sites generally exceeds that of the one with more solvent-exposed binding sites and even surpasses the corresponding ligand-based virtual screening

Enhancing the Enrichment of Pharmacophore-Based Target Prediction for the Polypharmacological Profiles of Drugs

PharmMapper is a web server for drug target identification by reversed pharmacophore matching the query compound against an annotated pharmacophore model database, which provides a computational polypharmacology prediction approach for drug repurposing and side effect risk evaluation. But due to the inherent nondiscriminative feature of the simple fit scores used for prediction results ranking, the signal/noise ratio of the prediction results is high, posing a challenge for predictive reliability. In this paper, we improved the predictive accuracy of PharmMapper by generating a ligand–target pairwise fit score matrix from profiling all the annotated pharmacophore models against corresponding ligands in the original complex structures that were used to extract these pharmacophore models. The matrix reflects the noise baseline of fit score distribution of the background database, thus enabling estimation of the probability of finding a given target randomly with the calculated ligand–pharmacophore fit score. Two retrospective tests were performed which confirmed that the probability-based ranking score outperformed the simple fit score in terms of identification of both known drug targets and adverse drug reaction related off-targets

Transcriptional Regulation of the Ufm1 Conjugation System in Response to Disturbance of the Endoplasmic Reticulum Homeostasis and Inhibition of Vesicle Trafficking

<div><p>Homeostasis of the endoplasmic reticulum (ER) is essential for normal cellular functions. Disturbance of this homeostasis causes ER stress and activates the Unfolded Protein Response (UPR). The Ufm1 conjugation system is a novel Ubiquitin-like (Ubl) system whose physiological target(s) and biological functions remain largely undefined. Genetic study has demonstrated that the Ufm1-activating enzyme Uba5 is indispensible for erythroid differentiation in mice, highlighting the importance of this novel system in animal development. In this report we present the evidence for involvement of RCAD/Ufl1, a putative Ufm1-specific E3 ligase, and its binding partner C53/LZAP protein in ufmylation of endogenous Ufm1 targets. Moreover, we found that the Ufm1 system was transcriptionally up-regulated by disturbance of the ER homeostasis and inhibition of vesicle trafficking. Using luciferase reporter and ChIP assays, we dissected the Ufm1 promoter and found that Ufm1 was a potential target of Xbp-1, one of crucial transcription factors in UPR. We further examined the effect of Xbp-1 deficiency on the expression of the Ufm1 components. Interestingly, the expression of Ufm1, Uba5, RCAD/Ufl1 and C53/LZAP in wild-type mouse embryonic fibroblasts (MEFs) was significantly induced by inhibition of vesicle trafficking, but the induction was negated by Xbp-1 deficiency. Finally, we found that knockdown of the Ufm1 system in U2OS cells triggered UPR and amplification of the ER network. Taken together, our study provided critical insight into the regulatory mechanism of the Ufm1 system and established a direct link between this novel Ubl system and the ER network.</p> </div

Enhancing the Enrichment of Pharmacophore-Based Target Prediction for the Polypharmacological Profiles of Drugs

PharmMapper is a web server for drug target identification by reversed pharmacophore matching the query compound against an annotated pharmacophore model database, which provides a computational polypharmacology prediction approach for drug repurposing and side effect risk evaluation. But due to the inherent nondiscriminative feature of the simple fit scores used for prediction results ranking, the signal/noise ratio of the prediction results is high, posing a challenge for predictive reliability. In this paper, we improved the predictive accuracy of PharmMapper by generating a ligand–target pairwise fit score matrix from profiling all the annotated pharmacophore models against corresponding ligands in the original complex structures that were used to extract these pharmacophore models. The matrix reflects the noise baseline of fit score distribution of the background database, thus enabling estimation of the probability of finding a given target randomly with the calculated ligand–pharmacophore fit score. Two retrospective tests were performed which confirmed that the probability-based ranking score outperformed the simple fit score in terms of identification of both known drug targets and adverse drug reaction related off-targets

Ufm1 is a potential target of Xbp-1.

<p><b>A.</b> The constructs of the Ufm1 promoter used for luciferase reporter assays. Human Ufm1 promoter sequence was amplified from the genome of HCT116 cells. <b>B.</b> The minimal Ufm1 promoter responded to ER stresses. Various Ufm1 promoter constructs were transfected into 293T cells that were subsequently treated with TG (0.5 µM) and TM (10 µM) for 24 hours. The promoter activity was measured by dual luciferase reporter assays (Promega). <b>C.</b> The putative Xbp-1 binding site was responsible for Xbp-1-mediated induction of Ufm1. 293T cells were transfected with indicated Ufm1 promoter constructs along with Xbp-1 expression vector. The cells were subsequently treated with TG and TM, and the promoter activity was measured by dual luciferase assays. <b>D.</b> The Ufm1 promoter activity in wild-type and Xbp-1^−/− MEFs. The Ufm1 protomer reporter was transfected into wild-type and Xbp-1^−/− MEFs, and the promoter activity was measured by dual luciferase reporter assays (Promega). The results represented mean ± SD. *p value <0.01 and **p value <0.05. <b>E.</b> CHIP assay. The Xbp-1-DNA complex was immunoprecipitated with Xbp-1 antibody, and subject to PCR using the primers specific for Ufm1 and ERdj4 promoters.</p