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CoMFA and CoMSIA 3D-QSAR analysis of DMDP derivatives as anti-cancer agents.

Srivastava V, Kumar A, Mishra BN, Siddiqi MI - Bioinformation (2008)

Bottom Line: The best prediction were obtained with a CoMFA standard model (q(2) = 0.530, r(2) = 0.903) and with CoMSIA combined steric, electrostatic, hydrophobic and hydrogen bond donor fields (q(2) = 0.548, r(2) = 0.909).Both models were validated by a test set of ten compounds producing very good predictive r(2) values of 0.935 and 0.842, respectively.This study suggests that the highly electropositive substituents with low steric tolerance are required at 5 position of the pteridine ring and bulky electronegatve substituents are required at the meta-position of the phenyl ring.

View Article: PubMed Central - PubMed

Affiliation: Department of biotechnology, Institute of engineering and technology, Sitapur road, Lucknow 21.

ABSTRACT
Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on three dimensional quantitative structure-activity relationship (3D-QSAR) studies were conducted on a series (78 compounds) of 2, 4-diamino-5-methyl-5-deazapteridine (DMDP) derivatives as potent anticancer agents. The best prediction were obtained with a CoMFA standard model (q(2) = 0.530, r(2) = 0.903) and with CoMSIA combined steric, electrostatic, hydrophobic and hydrogen bond donor fields (q(2) = 0.548, r(2) = 0.909). Both models were validated by a test set of ten compounds producing very good predictive r(2) values of 0.935 and 0.842, respectively. CoMFA and CoMSIA contour maps were then used to analyze the structural features of ligands to account for the activity in terms of positively contributing physiochemical properties such as steric, electrostatic, hydrophobic and hydrogen bond donor fields. The resulting contour maps produced by the best CoMFA and CoMSIA models were used to identify the structural features relevant to the biological activity in this series of analogs. This study suggests that the highly electropositive substituents with low steric tolerance are required at 5 position of the pteridine ring and bulky electronegatve substituents are required at the meta-position of the phenyl ring. The information obtained from CoMFA and CoMSIA 3-D contour maps can be used for the design of deazapteridine-based analogs as anticancer agents.

No MeSH data available.


(a) and 1(b) are the predictive versus experimental pIC50 values derived from CoMFA and CoMSIA model for training set (black hole) and test set (white rectangle).
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Figure 1: (a) and 1(b) are the predictive versus experimental pIC50 values derived from CoMFA and CoMSIA model for training set (black hole) and test set (white rectangle).

Mentions: Thus, the difference in the parameters calculated from the original data and the average of the parameters calculated from the N(=100) runs of bootstrapping sampling is a measure of the bias of the original calculation. This yielded higher r2bootstrap value 0.939 for CoMFA with standard error value of 0.299. This further supports the statistical validity of the developed models. The predicted activities for the inhibitors versus their experimental values are listed in Table 1 (see supplementary material) and the correlation between the predicted activities and the experimental values is depicted in Figure 1. Figure 1 illustrate the predicted activities using the CoMFA model are in good agreement with the experimental data, suggesting that the CoMFA model should have a satisfactory predictive ability.


CoMFA and CoMSIA 3D-QSAR analysis of DMDP derivatives as anti-cancer agents.

Srivastava V, Kumar A, Mishra BN, Siddiqi MI - Bioinformation (2008)

(a) and 1(b) are the predictive versus experimental pIC50 values derived from CoMFA and CoMSIA model for training set (black hole) and test set (white rectangle).
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2533057&req=5

Figure 1: (a) and 1(b) are the predictive versus experimental pIC50 values derived from CoMFA and CoMSIA model for training set (black hole) and test set (white rectangle).
Mentions: Thus, the difference in the parameters calculated from the original data and the average of the parameters calculated from the N(=100) runs of bootstrapping sampling is a measure of the bias of the original calculation. This yielded higher r2bootstrap value 0.939 for CoMFA with standard error value of 0.299. This further supports the statistical validity of the developed models. The predicted activities for the inhibitors versus their experimental values are listed in Table 1 (see supplementary material) and the correlation between the predicted activities and the experimental values is depicted in Figure 1. Figure 1 illustrate the predicted activities using the CoMFA model are in good agreement with the experimental data, suggesting that the CoMFA model should have a satisfactory predictive ability.

Bottom Line: The best prediction were obtained with a CoMFA standard model (q(2) = 0.530, r(2) = 0.903) and with CoMSIA combined steric, electrostatic, hydrophobic and hydrogen bond donor fields (q(2) = 0.548, r(2) = 0.909).Both models were validated by a test set of ten compounds producing very good predictive r(2) values of 0.935 and 0.842, respectively.This study suggests that the highly electropositive substituents with low steric tolerance are required at 5 position of the pteridine ring and bulky electronegatve substituents are required at the meta-position of the phenyl ring.

View Article: PubMed Central - PubMed

Affiliation: Department of biotechnology, Institute of engineering and technology, Sitapur road, Lucknow 21.

ABSTRACT
Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on three dimensional quantitative structure-activity relationship (3D-QSAR) studies were conducted on a series (78 compounds) of 2, 4-diamino-5-methyl-5-deazapteridine (DMDP) derivatives as potent anticancer agents. The best prediction were obtained with a CoMFA standard model (q(2) = 0.530, r(2) = 0.903) and with CoMSIA combined steric, electrostatic, hydrophobic and hydrogen bond donor fields (q(2) = 0.548, r(2) = 0.909). Both models were validated by a test set of ten compounds producing very good predictive r(2) values of 0.935 and 0.842, respectively. CoMFA and CoMSIA contour maps were then used to analyze the structural features of ligands to account for the activity in terms of positively contributing physiochemical properties such as steric, electrostatic, hydrophobic and hydrogen bond donor fields. The resulting contour maps produced by the best CoMFA and CoMSIA models were used to identify the structural features relevant to the biological activity in this series of analogs. This study suggests that the highly electropositive substituents with low steric tolerance are required at 5 position of the pteridine ring and bulky electronegatve substituents are required at the meta-position of the phenyl ring. The information obtained from CoMFA and CoMSIA 3-D contour maps can be used for the design of deazapteridine-based analogs as anticancer agents.

No MeSH data available.