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Bioactivity databases | Chemical informatics data analysis

Bioactivity databases | Chemical informatics data analysis

A wealth of information on the activity of small molecules and biotherapeutics exists in the literature, and access to this information can enable many types of drug discovery analysis and decision making. For example: selection of tool compounds for probing targets or pathways of interest; identification of potential off-target activities of compounds which may pose safety concerns, explain existing side effects or suggest new applications for old compounds; analysis of structure–activity relationships (SAR) for a compound series of interest; assessment of in vivo absorption, distribution, metabolism, excretion and toxicity (ADMET) properties; or construction of predictive models for use in selection of compounds potentially active against a new target (Paolini et al., 2006; Mestres et al., 2009; Wassermann and Bajorath, 2011; Papadatos et al., 2010; Keiser et al., 2009). Access to this information is especially important due to the continuing shift in fundamental research on disease mechanisms from the private to public sectors.

References:
(Paolini et al., 2006) Global mapping of pharmacological space. Nat Biotechnol.
(Mestres et al., 2009) The topology of drug-target interaction networks: implicit dependence on drug properties and target families. Mol Biosyst.
(Wassermann and Bajorath, 2011) Large-scale exploration of bioisosteric replacements on the basis of matched molecular pairs. Future Med Chem.
(Papadatos et al., 2010) Lead optimization using matched molecular pairs: inclusion of contextual information for enhanced prediction of HERG inhibition, solubility, and lipophilicity. J Chem Inf Model.
(Keiser et al., 2009) Predicting new molecular targets for known drugs. Nature.

Source text:
(Gaulton et al., 2012) ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res.

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