Quantitative Structure−Activity Relationships of Mutagenic and Carcinogenic Aromatic Amines

Benigni, Romualdo; Giuliani, Alessandro; Franke, R.; Gruska, Andreas

doi:10.1021/cr9901079

Cited by 182 publications

(135 citation statements)

References 66 publications

(144 reference statements)

Supporting

Mentioning

124

Contrasting

Order By: Relevance

“…Consequently, in this example, the molecular size is important for binding to the CYP2E active site. Moreover, the "hardness" factor is also apparent in this correlation, and this is the energy gap between HOMO and LUMO frontier orbitals [15].…”

Section: P450-mediated Catalysismentioning

confidence: 84%

Structural Models for Cytochrome P450�Mediated Catalysis

Lewis

2003

The Scientific World JOURNAL

View full text Add to dashboard Cite

This review focuses on the structural models for cytochrome P450 that are improving our knowledge and understanding of the P450 catalytic cycle, and the way in which substrates bind to the enzyme leading to catalytic conversion and subsequent formation of mono-oxygenated metabolites. Various stages in the P450 reaction cycle have now been investigated using X-ray crystallography and electronic structure calculations, whereas homology modelling of mammalian P450s is currently revealing important aspects of pharmaceutical and other xenobiotic metabolism mediated by P450 involvement. These features are explored in the current review on P450-based catalysis, which emphasises the importance of structural modelling to our understanding of this enzyme's function. In addition, the results of various QSAR analyses on series of chemicals, which are metabolised via P450 enzymes, are presented such that the importance of electronic and other structural factors in explaining variations in rates of metabolism can be appreciated.

show abstract

Section: P450-mediated Catalysismentioning

confidence: 84%

Structural Models for Cytochrome P450�Mediated Catalysis

Lewis

2003

The Scientific World JOURNAL

View full text Add to dashboard Cite

show abstract

“…Moreover, TIC-ASA interactions generate hydrophilic (DPs) and lipophilic (IPs) products, which alter the pharmacokinetics and pharmacodynamics of the drug and hence reduce the potency [35]. Furthermore, ASA induced degradation of TIC generates primary arylaminethrough the N-dealkylation process, which are reported to participatein the metabolic activation by cytochrome P450, which may generate mutagenic and carcinogenic metabolites [36][37][38].…”

Section: Evaporation and Its Effect On Tic-asa Mixturesmentioning

confidence: 99%

Investigating therapeutic usage of combined Ticagrelor and Aspirin through solid-state and analytical studies

Yayé

Rietveld

Secrétan

et al. 2017

European Journal of Pharmaceutical Sciences

View full text Add to dashboard Cite

show abstract

“…It is commonly accepted that the internal validation of QSAR models built from training sets is sufficient to confirm their predictive power [34][35][36][37][38] . However, previous studies in this as well as several other laboratories demonstrated that no correlation exists between leave-one-out (LOO) cross-validated R 2 (q 2 ) for the training set and the correlation coefficient R 2 between the predicted and observed activities for the test set 29;39 .…”

Section: Dataset Division Into Training and Test Setsmentioning

confidence: 99%

“…34 Table 4 presents 10 best models obtained from multiple kNN analyses. In order to estimate the statistical significance of the models, the original dataset of 52 compounds was divided into 50 training and test sets.…”

Section: Knn Qsar Model Validationmentioning

confidence: 99%

Antitumor Agents 252. Application of validated QSAR models to database mining: discovery of novel tylophorine derivatives as potential anticancer agents

Zhang

Wei

Bastow

et al. 2007

J Comput Aided Mol Des

View full text Add to dashboard Cite

A combined approach of validated QSAR modeling and virtual screening was successfully applied to the discovery of novel tylophrine derivatives as anticancer agents. QSAR models have been initially developed for 52 chemically diverse phenanthrine-based tylophrine derivatives (PBTs) with known experimental EC 50 using chemical topological descriptors (calculated with the MolConnZ program) and variable selection k nearest neighbor (kNN) method. Several validation protocols have been applied to achieve robust QSAR models. The original dataset was divided into multiple training and test sets, and the models were considered acceptable only if the leave-one-out cross-validated R 2 (q 2 ) values were greater than 0.5 for the training sets and the correlation coefficient R 2 values were greater than 0.6 for the test sets. Furthermore, the q 2 values for the actual dataset were shown to be significantly higher than those obtained for the same dataset with randomized target properties (Y-randomization test), indicating that models were statistically significant. Ten best models were then employed to mine a commercially available ChemDiv Database (ca. 500K compounds) resulting in 34 consensus hits with moderate to high predicted activities. Ten structurally diverse hits were experimentally tested and eight were confirmed active with the highest experimental EC 50 of 1.8µM implying an exceptionally high hit rate (80%). The same ten models were further applied to predict EC50 for four new PBTs, and the correlation coefficient (R 2 ) between the experimental and predicted EC 50 for these compounds plus eight active consensus hits was shown to be as high as 0.57. Our studies suggest that the approach combining validated QSAR modeling and virtual screening could be successfully used as a general tool for the discovery of novel biologically active compounds.

show abstract

Quantitative Structure−Activity Relationships of Mutagenic and Carcinogenic Aromatic Amines

Cited by 182 publications

References 66 publications

Structural Models for Cytochrome P450�Mediated Catalysis

Structural Models for Cytochrome P450�Mediated Catalysis

Investigating therapeutic usage of combined Ticagrelor and Aspirin through solid-state and analytical studies

Antitumor Agents 252. Application of validated QSAR models to database mining: discovery of novel tylophorine derivatives as potential anticancer agents

Contact Info

Product

Resources

About