Search: id:"swepub:oai:DiVA.org:umu-35576" >
Statistical molecul...
-
Linusson, AnnaUmeå universitet,Kemiska institutionen
(author)
Statistical molecular design of balanced compound libraries for QSAR modeling
- Article/chapterEnglish2010
Publisher, publication year, extent ...
-
Bentham Science Publishers Ltd.2010
-
printrdacarrier
Numbers
-
LIBRIS-ID:oai:DiVA.org:umu-35576
-
https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-35576URI
-
https://doi.org/10.2174/092986710791233661DOI
Supplementary language notes
-
Language:English
-
Summary in:English
Part of subdatabase
Classification
-
Subject category:ref swepub-contenttype
-
Subject category:for swepub-publicationtype
Notes
-
A fundamental step in preclinical drug development is the computation of quantitative structure-activity relationship (QSAR) models, i.e. models that link chemical features of compounds with activities towards a target macromolecule associated with the initiation or progression of a disease. QSAR models are computed by combining information on the physicochemical and structural features of a library of congeneric compounds, typically assembled from two or more building blocks, and biological data from one or more in vitro assays. Since the models provide information on features affecting the compounds' biological activity they can be used as guides for further optimization. However, in order for a QSAR model to be relevant to the targeted disease, and drug development in general, the compound library used must contain molecules with balanced variation of the features spanning the chemical space believed to be important for interaction with the biological target. In addition, the assays used must be robust and deliver high quality data that are directly related to the function of the biological target and the associated disease state. In this review, we discuss and exemplify the concept of statistical molecular design (SMD) in the selection of building blocks and final synthetic targets (i.e. compounds to synthesize) to generate information-rich, balanced libraries for biological testing and computation of QSAR models.
Subject headings and genre
Added entries (persons, corporate bodies, meetings, titles ...)
-
Elofsson, MikaelUmeå universitet,Kemiska institutionen(Swepub:umu)miel0001
(author)
-
Andersson, Ida EUmeå universitet,Kemiska institutionen(Swepub:umu)idaann02
(author)
-
Dahlgren, Markus KUmeå universitet,Kemiska institutionen
(author)
-
Umeå universitetKemiska institutionen
(creator_code:org_t)
Related titles
-
In:Current Medicinal Chemistry: Bentham Science Publishers Ltd.17:19, s. 2001-20160929-86731875-533X
Internet link
Find in a library
To the university's database