Déjà Vu - Réjà Vu : on knowledge-based approaches linking ligand and target information to bioactivity

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Déjà Vu - Réjà Vu : on knowledge-based approaches linking ligand and target information to bioactivity

Title: Déjà Vu - Réjà Vu : on knowledge-based approaches linking ligand and target information to bioactivity
Author: Westen, G.J.P. van
Publisher: Department of Medicinal Chemistry, Leiden/Amsterdam Center for Drug Research (LACDR), Faculty of Science, Leiden University
Issue Date: 2013-01-08
Keywords: Proteochemometrics
Machine learning
Polypharmacology
Viral resistance
Hiv
GPCR
QSAR
Consensus structures
Chemogenomics
Cheminformatics
Ortholog
Paralog
Abstract: Over the last decades several disciplines relevant to medicinal chemistry and preclinical drug discovery have made gigantic leaps; this includes chemistry, biology and measurement of bioactivity. Better techniques have led to massive amounts of data. Moreover, sources of chemical and bioactivity data have become available in the public domain. Hence there is a need for new techniques combining and mining these data sources. This thesis focuses on computational methods combining data from these disciplines and demonstrates that the sum of these methods leads to better quality predictions than models using the individual data sources. One of the techniques central in this thesis is proteochemometric modeling, a machine learning approach linking chemical descriptors and protein descriptors to a biologically relevant output variable. This output variable describes the activity of molecules on biological macromolecules and hence proteochemometric models can make relevant predictions for both unseen molecules and unseen macromolecules (e.g. novel viral mutants). Secondly we present a novel technique that is able to combine information from multiple crystal structures in such a way that shared and unique pharmacophoric features can be isolated and visualized. Approaches presented here have been validated prospectively and have been shown to be widely applicable.
Description: Promotores: A.P. IJzerman, H.W.T. van Vlijmen, Co-Promotor: A. Bender
With Summary in Dutch
Faculty: Faculteit der Wiskunde en Natuurwetenschappen
Citation: Westen, G.J.P. van, 2013, Doctoral Thesis, Leiden University
ISBN: 9789462032613
Sponsor: Tibotec BVBA
Handle: http://hdl.handle.net/1887/20394
 

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