2012
DOI: 10.1002/ddr.21026
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The Role of Chemogenomics in the Pharmaceutical Industry

Abstract: Preclinical Research The goal of chemogenomics is the exploration of all possible interactions between compounds from the chemical space and targets from the biological space. This huge interaction matrix is only sparsely filled with experimental data but can be complemented by predicted values for selected ligand–target pairs. The prediction by computational chemogenomics uses the similarity principle that states that similar compounds have similar properties and that targets with similar binding sites bind… Show more

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Cited by 6 publications
(3 citation statements)
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“…4 In silico approaches have been proven to be successful in many phases of this process. 5,6 It has been recently demonstrated that drugs exert their therapeutic effect by modulating more than one target, 7 extending the notion of the one drug one target premise. 8 While drug discovery efforts have been long focussed on single target potency optimization, 9 the rapid growth of bioactivity databases sparks novel methods to use the data for addressing ligand selectivity and polypharmacology.…”
Section: Introductionmentioning
confidence: 97%
“…4 In silico approaches have been proven to be successful in many phases of this process. 5,6 It has been recently demonstrated that drugs exert their therapeutic effect by modulating more than one target, 7 extending the notion of the one drug one target premise. 8 While drug discovery efforts have been long focussed on single target potency optimization, 9 the rapid growth of bioactivity databases sparks novel methods to use the data for addressing ligand selectivity and polypharmacology.…”
Section: Introductionmentioning
confidence: 97%
“…11 Hence, only the simultaneous modelling of both the chemical and the target domain, across a series of protein targets, permits the meaningful mining of the compound-target interaction space. 12 The term chemogenomics comprises techniques capable to capitalize on this huge amount of bioactivity data by considering compound and target information, in order to nd unknown interactions between (new) compounds and their (new) targets. 13,14 Proteochemometrics (PCM) modelling describes methods where a computational description from the ligand side of the system is combined with a description of the biological side being studied and both are related to a particular readout of interest.…”
Section: Introductionmentioning
confidence: 99%
“…Evidently, drug design is no longer restricted to one‐compound – one‐target scenarios. Explicit consideration of ligand selectivity toward desired targets, avoidance of anti‐target effects, and the inclusion of potential additive effects through the interaction with biochemical networks have enabled “polypharmacological” drug design 4. Computational approaches play an important part in this context, specifically for target affinity prediction and the early recognition of certain compound liabilities, e.g.…”
Section: Introductionmentioning
confidence: 99%