Article

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

ABSTRACT

ZINC is a free public resource for ligand discovery.
The database contains over twenty million commercially available molecules
in biologically relevant representations that may be downloaded in
popular ready-to-dock formats and subsets. The Web site also enables
searches by structure, biological activity, physical property, vendor,
catalog number, name, and CAS number. Small custom subsets may be
created, edited, shared, docked, downloaded, and conveyed to a vendor
for purchase. The database is maintained and curated for a high purchasing
success rate and is freely available at zinc.docking.org.

Download full-text

Full-text

Available from: John J Irwin
  • Source
    • "Ligands with an inhibition constant (K i ) less than or equal to 100 nM were considered active; ligands with K i higher than 1000 nM were used as inactives. Putative inactive compounds were randomly selected from the ZINC database[28]in a ratio of 9 inactives per 1 active (Table 4)[29]. To evaluate the significance of the selected features, a 10-fold cross-validation was per- formed[30]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Fingerprints, bit representations of compound chemical structure, have been widely used in cheminformatics for many years. Although fingerprints with the highest resolution display satisfactory performance in virtual screening campaigns, the presence of a relatively high number of irrelevant bits introduces noise into data and makes their application more time-consuming. In this study, we present a new method of hybrid reduced fingerprint construction, the Average Information Content Maximization algorithm (AIC-Max algorithm), which selects the most informative bits from a collection of fingerprints. This methodology, applied to the ligands of five cognate serotonin receptors (5-HT2A, 5-HT2B, 5-HT2C, 5-HT5A, 5-HT6), proved that 100 bits selected from four non-hashed fingerprints reflect almost all structural information required for a successful in silico discrimination test. A classification experiment indicated that a reduced representation is able to achieve even slightly better performance than the state-of-the-art 10-times-longer fingerprints and in a significantly shorter time.
    Full-text · Article · Jan 2016 · PLoS ONE
  • Source
    • "It is as powerful as the docking method, and is always more efficient than docking methods. For example, the large ligands database ZINC [44] has more than 200 million ligands. By calibrating the parameters of the pharmacophore virtual screening, it is possible toFigure 3 DNA damage_ATM/ATR regulation of G1/S checkpoint. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Computer-aided drug design has a long history of being applied to discover new molecules to treat various cancers, but it has always been focused on single targets. The development of systems biology has let scientists reveal more hidden mechanisms of cancers, but attempts to apply systems biology to cancer therapies remain at preliminary stages. Our lab has successfully developed various systems biology models for several cancers. Based on these achievements, we present the first attempt to combine multiple-target therapy with systems biology. In our previous study, we identified 28 significant proteins--i.e., common core network markers--of four types of cancers as house-keeping proteins of these cancers. In this study, we ranked these proteins by summing their carcinogenesis relevance values (CRVs) across the four cancers, and then performed docking and pharmacophore modeling to do virtual screening on the NCI database for anti-cancer drugs. We also performed pathway analysis on these proteins using Panther and MetaCore to reveal more mechanisms of these cancer house-keeping proteins. We designed several approaches to discover targets for multiple-target cocktail therapies. In the first one, we identified the top 20 drugs for each of the 28 cancer house-keeping proteins, and analyzed the docking pose to further understand the interaction mechanisms of these drugs. After screening for duplicates, we found that 13 of these drugs could target 11 proteins simultaneously. In the second approach, we chose the top 5 proteins with the highest summed CRVs and used them as the drug targets. We built a pharmacophore and applied it to do virtual screening against the Life-Chemical library for anti-cancer drugs. Based on these results, wet-lab bio-scientists could freely investigate combinations of these drugs for multiple-target therapy for cancers, in contrast to the traditional single target therapy. Combination of systems biology with computer-aided drug design could help us develop novel drug cocktails with multiple targets. We believe this will enhance the efficiency of therapeutic practice and lead to new directions for cancer therapy.
    Full-text · Article · Dec 2015 · BMC Medical Genomics
  • Source
    • "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). "
    [Show abstract] [Hide abstract]
    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.
    Full-text · Article · Oct 2015 · SAR and QSAR in environmental research
Show more