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Protocols

SMARTCyp specifications

Information


Unique identifier OMICS_07390
Name SMARTCyp
Interface Web user interface
Restrictions to use None
Computer skills Basic
Version 2.4.2
Stability Stable
Maintained No

Publications for SMARTCyp

SMARTCyp citations

 (11)
library_books

RD Metabolizer: an integrated and reaction types extensive approach to predict metabolic sites and metabolites of drug like molecules

2017
Chem Cent J
PMCID: 5515729
PMID: 29086838
DOI: 10.1186/s13065-017-0290-4

[…] s to estimate the likelihood of metabolic reaction at a certain atom position, with a success rate of 85% for tagging a known SOM among the top-2 ranked atom positions. Rydberg et al. [–] implemented SMARTCyp as a fast SOMs predictor. The predictor contains a reactivity lookup table of pre-calculated density functional theory (DFT) activation energies for plenty of ligand fragments that are underg […]

library_books

Predicting the Metabolic Sites by Flavin Containing Monooxygenase on Drug Molecules Using SVM Classification on Computed Quantum Mechanics and Circular Fingerprints Molecular Descriptors

2017
PLoS One
PMCID: 5224990
PMID: 28072829
DOI: 10.1371/journal.pone.0169910

[…] ized by CYP450 have been developed. These approaches can be roughly divided into the following two categories namely, the ligand (substrate) based and the structure (enzyme) based ones. For examples, SMARTCyp [] is a method that using a database of activation energies computed from quantum mechanics for a variety of ligand fragments and an accessibility descriptor computed to rank all the possible […]

library_books

Construction of Metabolism Prediction Models for CYP450 3A4, 2D6, and 2C9 Based on Microsomal Metabolic Reaction System

2016
Int J Mol Sci
PMCID: 5085718
PMID: 27735849
DOI: 10.3390/ijms17101686

[…] g it is a substrate of certain metabolic enzyme []. The proposed of MMRS made it possible to determine the metabolism of drugs and give information about metabolic enzyme simultaneously.We concur the SMARTCyp authors’ view that false negatives (which are inevitable in the experimental data) always lead to minor signal-to-noise []. We believe this is not a secret in the domain of metabolism predict […]

call_split

Forced Degradation Studies of Ivabradine and In Silico Toxicology Predictions for Its New Designated Impurities

2016
Front Pharmacol
PMCID: 4855699
PMID: 27199759
DOI: 10.3389/fphar.2016.00117
call_split See protocol

[…] Ivabradine is metabolized by cytochrome P450. To calculate the probable metabolites, Toxtree program was used (), applying SMARTCyp method to predict the fragments in the molecule, which are the most susceptible to activity of cytochrome P450.For the calculation of toxicity (CYP3A4, CYP2D6, CYP2C9, CYP2C19, and CYP1A2), l […]

library_books

Modeling Epoxidation of Drug like Molecules with a Deep Machine Learning Network

2015
PMCID: 4827534
PMID: 27162970
DOI: 10.1021/acscentsci.5b00131

[…] x is the initial intermediate formed during epoxidation by cytochromes P450.,, While reasonable, πp occupancy has never been proposed as a way to identify SOE.The second most important descriptor was SMARTCyp reactivity, with a performance drop of 2.5%. The relevance of SMARTCyp reactivity is readily understandable, because it predicts the sites of cytochromes P450 metabolism of drug-like molecule […]

library_books

Antihypertensive Drugs Metabolism: An Update to Pharmacokinetic Profiles and Computational Approaches

2015
Curr Pharm Des
PMCID: 4435036
PMID: 25341854
DOI: 10.2174/1381612820666141024151119

[…] likely significant feature for making predictions of novel pharmaceutics compounds metabolism. Liu et al., based on a 2D substructure structure-based site of metabolism (SOM) prediction method called SMARTCyp [] were able to predict the SOM of major drug metabolism enzymes belonging to the superfamily of P450 such as CYP1A2, CYP2C9 and CYP2C19 []. SMARTCyp is an alternative method that is able to […]


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SMARTCyp institution(s)
Biostructural Research, Department of Medicinal Chemistry, Faculty of Pharmaceutical Sciences, University of Copenhagen, Copenhagen, Denmark; Universitetsparken 2, Copenhagen, Denmark; Center for Biotechnology and Interdisciplinary Studies, Department of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute, Troy, New York, NY, USA

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