%0 Journal Article
%A Kontijevskis, Aleksejs
%D 2017
%T Mapping of Drug-like Chemical
Universe with Reduced
Complexity Molecular Frameworks
%U https://acs.figshare.com/articles/journal_contribution/Mapping_of_Drug-like_Chemical_Universe_with_Reduced_Complexity_Molecular_Frameworks/4869353
%R 10.1021/acs.jcim.7b00006.s005
%2 https://acs.figshare.com/ndownloader/files/8104106
%K RCMF-based searches
%K drug candidates
%K mapping Chemetics library selection outputs
%K RCMF descriptors
%K drug-like chemical universe
%K Reduced Complexity Molecular Frameworks
%K framework chemical space map
%K DNA-encoded synthesis
%K DNA-encoded chemical libraries
%K combinatorial libraries
%K DEL
%K Drug-like Chemical Universe
%K chemical space
%K cheminformatics community
%K Nuevolution Chemetics technology
%K chemical data challenge
%K chemical structures
%K drug-like chemical space
%K novel drug-like hits
%K library enumeration
%K framework map
%K multi-million-member drug-like Chemetics DNA-encoded libraries
%K LSD 1 targets
%K molecule compounds
%X The emergence of the DNA-encoded
chemical libraries (DEL) field
in the past decade has attracted the attention of the pharmaceutical
industry as a powerful mechanism for the discovery of novel drug-like
hits for various biological targets. Nuevolution Chemetics technology
enables DNA-encoded synthesis of billions of chemically diverse drug-like
small molecule compounds, and the efficient screening and optimization
of these, facilitating effective identification of drug candidates
at an unprecedented speed and scale. Although many approaches have
been developed by the cheminformatics community for the analysis and
visualization of drug-like chemical space, most of them are restricted
to the analysis of a maximum of a few millions of compounds and cannot
handle collections of 108–1012 compounds
typical for DELs. To address this big chemical data challenge, we
developed the Reduced Complexity Molecular Frameworks (RCMF) methodology
as an abstract and very general way of representing chemical structures.
By further introducing RCMF descriptors, we constructed a global framework
map of drug-like chemical space and demonstrated how chemical space
occupied by multi-million-member drug-like Chemetics DNA-encoded libraries
and virtual combinatorial libraries with >1012 members
could be analyzed and mapped without a need for library enumeration.
We further validate the approach by performing RCMF-based searches
in a drug-like chemical universe and mapping Chemetics library selection
outputs for LSD1 targets on a global framework chemical space map.
%I ACS Publications