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https://www.arca.fiocruz.br/handle/icict/12710
PKCSM: PREDICTING SMALL-MOLECULE PHARMACOKINETIC AND TOXICITY PROPERTIES USING GRAPH-BASED SIGNATURES
Drug-Related Side Effects and Adverse Reactions
Models/Theoretical
Small Molecule Libraries/chemistry
Small Molecule Libraries/pharmacokinetics
Small Molecule Libraries/toxicity
Tetrahymena pyriformis/drug effects
Affilliation
University of Cambridge. Department of Biochemistry. Cambridge, Cambridgshire, U.K/Fundação Oswaldo Cruz. Centro de Pesquisas René Rachou. Belo Horizonte, MG, Brazil.
University of Cambridge. Department of Biochemistry. Cambridge, Cambridgshire, U.K.
University of Cambridge. Department of Biochemistry. Cambridge, Cambridgshire, U.K.
University of Cambridge. Department of Biochemistry. Cambridge, Cambridgshire, U.K.
University of Cambridge. Department of Biochemistry. Cambridge, Cambridgshire, U.K.
Abstract
Drug development has a high attrition rate, with poor pharmacokinetic and safety properties a significant hurdle. Computational approaches may help minimize these risks. We have developed a novel approach (pkCSM) which uses graph-based signatures to develop predictive models of central ADMET properties for drug development. pkCSM performs as well or better than current methods. A freely accessible web server (http://structure.bioc.cam.ac.uk/pkcsm), which retains no information submitted to it, provides an integrated platform to rapidly evaluate pharmacokinetic and toxicity properties.
Keywords
Databases/PharmaceuticalDrug-Related Side Effects and Adverse Reactions
Models/Theoretical
Small Molecule Libraries/chemistry
Small Molecule Libraries/pharmacokinetics
Small Molecule Libraries/toxicity
Tetrahymena pyriformis/drug effects
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