Structural Basis for Inhibitor Specificity in Human Poly(ADP-ribose) Polymerase-3
doi: 10.1021/jm900052j
pmid: 19354255
Structural Basis for Inhibitor Specificity in Human Poly(ADP-ribose) Polymerase-3
Poly(ADP-ribose) polymerases (PARPs) activate DNA repair mechanisms upon stress- and cytotoxin-induced DNA damage, and inhibition of PARP activity is a lead in cancer drug therapy. We present a structural and functional analysis of the PARP domain of human PARP-3 in complex with several inhibitors. Of these, KU0058948 is the strongest inhibitor of PARP-3 activity. The presented crystal structures highlight key features for potent inhibitor binding and suggest routes for creating isoenzyme-specific PARP inhibitors.
- CRUK/MRC Oxford Institute for Radiation Oncology United Kingdom
- Cancer Research UK United Kingdom
- Medical Research Council United Kingdom
- Karolinska Institute Sweden
- Structural Genomics Consortium Canada
Models, Molecular, Protein Conformation, Biocatalysis, Humans, Enzyme Inhibitors, Poly(ADP-ribose) Polymerase Inhibitors, Poly(ADP-ribose) Polymerases, Crystallography, X-Ray, Substrate Specificity
Models, Molecular, Protein Conformation, Biocatalysis, Humans, Enzyme Inhibitors, Poly(ADP-ribose) Polymerase Inhibitors, Poly(ADP-ribose) Polymerases, Crystallography, X-Ray, Substrate Specificity
10 Research products, page 1 of 1
- 2019IsRelatedTo
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).95 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
