TY - JOUR
T1 - ChemProt-3.0
T2 - a global chemical biology diseases mapping
AU - Kringelum, Jens Vindahl
AU - Kjærulff, Sonny Kim
AU - Brunak, Søren
AU - Lund, Ole
AU - Oprea, Tudor I.
AU - Taboureau, Olivier Thierry
N1 - © The Author(s) 2016. Published by Oxford University Press.
PY - 2016
Y1 - 2016
N2 - ChemProt is a publicly available compilation of chemical-protein-disease annotation resources that enables the study of systems pharmacology for a small molecule across multiple layers of complexity from molecular to clinical levels. In this third version, ChemProt has been updated to more than 1.7 million compounds with 7.8 million bioactivity measurements for 19 504 proteins. Here, we report the implementation of global pharmacological heatmap, supporting a user-friendly navigation of chemogenomics space. This facilitates the visualization and selection of chemicals that share similar structural properties. In addition, the user has the possibility to search by compound, target, pathway, disease and clinical effect. Genetic variations associated to target proteins were integrated, making it possible to plan pharmacogenetic studies and to suggest human response variability to drug. Finally, Quantitative Structure-Activity Relationship models for 850 proteins having sufficient data were implemented, enabling secondary pharmacological profiling predictions from molecular structure.
AB - ChemProt is a publicly available compilation of chemical-protein-disease annotation resources that enables the study of systems pharmacology for a small molecule across multiple layers of complexity from molecular to clinical levels. In this third version, ChemProt has been updated to more than 1.7 million compounds with 7.8 million bioactivity measurements for 19 504 proteins. Here, we report the implementation of global pharmacological heatmap, supporting a user-friendly navigation of chemogenomics space. This facilitates the visualization and selection of chemicals that share similar structural properties. In addition, the user has the possibility to search by compound, target, pathway, disease and clinical effect. Genetic variations associated to target proteins were integrated, making it possible to plan pharmacogenetic studies and to suggest human response variability to drug. Finally, Quantitative Structure-Activity Relationship models for 850 proteins having sufficient data were implemented, enabling secondary pharmacological profiling predictions from molecular structure.
U2 - 10.1093/database/bav123
DO - 10.1093/database/bav123
M3 - Journal article
C2 - 26876982
SN - 1758-0463
VL - 2016
JO - Database : the journal of biological databases and curation
JF - Database : the journal of biological databases and curation
M1 - bav123
ER -
