ZINC: a free tool to discover chemistry for biology. J Chem Inf Model

Department of Pharmaceutical Chemistry, Byers Hall, University of California San Francisco , 1700 Fourth St, Box 2550, San Francisco California 94158-2330, United States.
Journal of Chemical Information and Modeling (Impact Factor: 3.74). 05/2012; 52(7). DOI: 10.1021/ci3001277
Source: PubMed


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Available from: John J Irwin,
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    • "Retrieval of the ligands' 3D structures The ligands' 3D structures used for this analysis were obtained from our research group, containing derivatives of benzoxazole (XT2B) and benzamide (XT5). For a comparative study, we also use structures of Vorapaxar, Atopaxar and Artesunate retrieved from Zinc databases [27] (Table 1). "
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    ABSTRACT: Protease-activated receptor 1 (PAR1) has been established as a promising target in many diseases, including various cancers. Strong evidence also suggests its role in metastasis. It is proved experimentally that PAR1 can induce numerous cell phenotypes, i.e. proliferation and differentiation. A strong link between PAR1 gene overexpression and high levels of ß-catenin was suggested by a study of the PAR1-Gα(13)-DVL axis in ß-catenin stabilization in cancers. An in vitro study was carried out to analyze PAR1 expression by flow cytometry on CD38+138+ plasma cells obtained from patients either at diagnosis (n: 46) (newly diagnosed multiple myeloma (NDMM)) or at relapse (n: 45) (relapsed/refractory multiple myeloma (RRMM)) and compared with the controls. Our previously synthesized benzoxazole (XT2B) and benzamide (XT5) derivatives were tested with in vitro 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays, which revealed significant inhibitory activity on PAR1. We provide docking studies using Autodock Vina of these newly tested compounds to compare with the known PAR1 inhibitors in order to examine the binding mechanisms. In addition, the docking results are validated using HYDE binding assessment and a neural network (NN) scoring function.
    SAR and QSAR in environmental research 10/2015; DOI:10.1080/1062936X.2015.1095799 · 1.60 Impact Factor
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    • "The series of drug candidates from ZINC database (Irwin et al., 2012) were docked against the target PBP2a using Dock blaster server (Irwin et al., 2009). The mutant residues along with the surrounding residues were used to set the grid for calculation. "
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    ABSTRACT: World Health Organization reports that methicillin-resistant Staphylococcus aureus (MRSA) is the origin of higher proportion of hospital acquired infections. In order to combat the effect of MRSA infection, an ideal drug should stimulate the allosteric exposure of active site, prompting penicillin binding proteins (PBP2a) to bind with that particular compound. Ceftaroline shows high binding affinity towards PBP2a and also confers resistance against degrading enzymes. Recently, two amino acid alterations in the allosteric site of PBP2a, asparagine (N) to lysine (K) at position 146 and glutamic acid (E) to lysine at position 150 are reported to confer resistance against ceftaroline resulting in the rise of ceftaroline-resistant MRSA strains. The present study focuses on the identification of potential ligands that can effectively bind with allosteric site of PBP2a, that leads to the access of active site and entry of a β-lactam antibiotic for effective inhibition. The results obtained from our study will be useful for designing effective compounds with potential therapeutic effects against ceftaroline resistant MRSA strains. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
    Journal of Cellular Biochemistry 08/2015; DOI:10.1002/jcb.25307 · 3.26 Impact Factor
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    • "The sequence of GADL1 was aligned with that of CSAD in DeepView (Guex and Peitsch, 1997) and submitted to the Swiss-Model server (Schwede et al., 2003) to prepare a homology model of GADL1 (see Fig. 2). A virtual library of 8 million commercially available compounds was obtained from the ZINC database (Irwin et al., 2012) and docked into the active site of CSAD with the Glide software (Friesner et al., 2004) from Schrodinger ® . A grid centered on the PLP cofactor in the CSAD binding site was defined with dimensions 17 Å in all three dimensions. "
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    ABSTRACT: Variants in the gene encoding the enzyme glutamic acid decarboxylase like 1 (GADL1) have been associated with response to lithium therapy. Both GADL1 and the related enzyme cysteine sulfinic acid decarboxylase (CSAD) have been proposed to be involved in the pyridoxal-5'-phosphate (PLP)-dependent biosynthesis of taurine. In the present study, we compared the catalytic properties, inhibitor sensitivity and expression profiles of GADL1 and CSAD in brain tissue. In mouse and human brain we observed distinct patterns of expression of the PLP-dependent decarboxylases CSAD, GADL1 and glutamic acid decarboxylase 67 (GAD67). CSAD levels were highest during prenatal and early postnatal development; GADL1 peaked early in prenatal development, while GAD67 increased rapidly after birth. Both CSAD and GADL1 are being expressed in neurons, whereas only CSAD mRNA was detected in astrocytes. Cysteine sulfinic acid was the preferred substrate for both mouse CSAD and GADL1, although both enzymes also decarboxylated cysteic acid and aspartate. In silico screening and molecular docking using the crystal structure of CSAD and in vitro assays led to the discovery of eight new enzyme inhibitors with partial selectivity for either CSAD or GADL1. Lithium had minimal effect on their enzyme activities. In conclusion, taurine biosynthesis in vertebrates involves two structurally related PLP-dependent decarboxylases (CSAD and GADL1) that have partially overlapping catalytic properties but different tissue distribution, indicating divergent physiological roles. Development of selective enzyme inhibitors targeting these enzymes is important to further dissect their (patho)physiological roles. Copyright © 2015. Published by Elsevier Ltd.
    Neurochemistry International 08/2015; DOI:10.1016/j.neuint.2015.08.013 · 3.09 Impact Factor
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