Abstract |
Quantitative structure-activity relationship of the 2-(1-propylpiperidin-4-yl)-1H-benzimidazole-4-carboxamide as a potent inhibitor of poly(ADP-ribose) polymerase for cancer treatment was studied. A suitable set of molecular descriptors was calculated and the genetic algorithm was employed to select those descriptors that resulted in the best fitted models. Excellent results were obtained employing multiple linear regressions and critically discussed using a variety of statistical parameters. Furthermore, the model was validated using leave-one-out and leave-group-out cross-validation, external test set and chance correlation. A genetic algorithm-multiple linear regression model with seven selected descriptors was obtained. This model, with high statistical significance (R(2) = 0.935, Q(2)_(LOO)= 0.894, Q(2)_(LGO)= 0.875, F = 53.481), could be used to predict poly(ADP-ribose) polymerase inhibitor activity of the molecules.
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Authors | Siavash Riahi, Eslam Pourbasheer, Rassoul Dinarvand, Mohammad Reza Ganjali, Parviz Norouzi |
Journal | Chemical biology & drug design
(Chem Biol Drug Des)
Vol. 72
Issue 6
Pg. 575-84
(Dec 2008)
ISSN: 1747-0285 [Electronic] England |
PMID | 19090924
(Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
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Chemical References |
- 2-(1-propylpiperidin-4-yl)-1H-benzimidazole-4-carboxamide
- Antineoplastic Agents
- Benzimidazoles
- Piperidines
- Poly(ADP-ribose) Polymerase Inhibitors
- Poly(ADP-ribose) Polymerases
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Topics |
- Algorithms
- Antineoplastic Agents
(chemistry, pharmacology, therapeutic use)
- Benzimidazoles
(chemistry, pharmacology)
- Databases, Genetic
- Least-Squares Analysis
- Models, Chemical
- Neoplasms
(drug therapy)
- Piperidines
(chemistry, pharmacology)
- Poly(ADP-ribose) Polymerase Inhibitors
- Poly(ADP-ribose) Polymerases
(chemistry)
- Predictive Value of Tests
- Quantitative Structure-Activity Relationship
- Regression Analysis
- Software
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