Statistical variation in progressive scrambling

Using generated conformations from docking analysis by Gold algorithm, some 3D-QSAR models; CoMFA and CoMSIA have been created on 39 N-benzoylated phenoxazines and phenothiazines, including their Soxidized analogues. These molecules inhibit the polymerization of tubulin into microtubules and thus they have been studied for the development of antitumor drugs. Training set for the CoMFA and CoMSIA models using 30 docked conformations gives q 2 Leave one out (LOO) values of 0.756 and 0.617, and r 2 ncv values of 0.988 and 0.956, respectively. The ability of prediction and robustness of the models were evaluated by test set, cross validation (leave-one-out and leave-ten-out), bootstrapping, and progressive scrambling approaches. The allorientation search (AOS) was used to achieve the best orientation to minimize the effect of initial orientation of the structures. The docking results confirmed CoMFA and CoMSIA contour maps. The docking and 3D-QSAR studies were thoroughly interpreted and discussed and confirmed the experimental pIC 50 values.

Section: Resultsmentioning

confidence: 92%

Docking, CoMFA and CoMSIA Studies of a Series of N-Benzoylated Phenoxazines and Phenothiazines Derivatives as Antiproliferative Agents

Ghasemi¹,

Aghaee²,

Jabbari³

2013

“…The complete details of the progressive scrambling can be find in the reference. 16 In this approach, small random perturbations are introduced into a data set and the statistical results, the perturbation prediction /dr 2 yy' ), are summarized in Table 3. Specifically, in case of five components, the sensitivity to the perturbation d q 2' /dr 2 yy' = 0.994 and the prediction q 2 = 0.487 produced by a progressive scrambling analyses were not dependent on chance correlation.…”

Section: Resultsmentioning

confidence: 99%

3D-QSAR Studies of 2-Arylbenzoxazoles as Novel Cholesteryl Ester Transfer Protein Inhibitors

Ghasemi¹,

Pirhadi²,

Ayati³

2011

The 3D-QSAR study of 2-arylbenzoxazoles as novel cholesteryl ester transfer protein inhibitors was performed by comparative molecular field analysis (CoMFA), CoMFA region focusing (CoMFA-RF) for optimizing the region for the final PLS analysis, and comparative molecular similarity indices analysis (CoMSIA) methods to determine the factors required for the activity of these compounds. The best orientation was searched by all-orientation search strategy using AOS, to minimize the effect of the initial orientation of the structures. The predictive ability of CoMFA-RF and CoMSIA were determined using a test set of twelve compounds giving predictive correlation coefficients of 0.886, and 0.754 respectively indicating good predictive power. Further, the robustness and sensitivity to chance correlation of the models were verified by bootstrapping and progressive scrambling analyses respectively. Based upon the information derived from CoMFA(RF) and CoMSIA, identified some key features that may be used to design new inhibitors for cholesteryl ester transfer protein.

“…uated with progressive scrambling analyses. 28 Thirty scrambling were carried with the conditions (maximum = 8 bins, minimum = 2 bins and critical point = 0.85). The susceptibility of the model to chance correlation can be gauged by the slope (dq 2' / dr 2 yy') of q 2 with respect to correlation of the original biological activity versus the scrambled biological activity.…”

Section: Methodsmentioning

confidence: 99%

Synthesis and Ligand Based 3D-QSAR of 2,3-Bis-benzylidenesuccinaldehyde Derivatives as New Class Potent FPTase Inhibitor, and Prediction of Active Molecules

Soung¹,

Kim²,

Kwon³

et al. 2010

In order to search new inhibitors against farnesyl protein transferase (FPTase), a series of 2,3-bis-benzylidenesuccinaldehyde derivatives (1-29) were synthesized and their inhibition activities (pI50) against FPTase were measured. From based on the reported results that the inhibitory activities of dimers 2,3-bis-benzylidenesuccinaldehydes were higher than those of monomers cinnamaldehydes, 3D-QSARs on FPTase inhibitory activities of the dimers (1-29) were studied quantitatively using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis ( The dependence of CoMFA models on chance correlations was evaluated with progressive scrambling analyses. And the inhibitory activity exhibited a strong correlation with steric factors of the substrate molecules. Therefore, from the results of graphical analyses on the contour maps and of predicted higher inhibitory active compounds, it is suggested that the structural distinctions and descriptors that contribute to inhibitory activities (pI50) against FPTase will be able to applied new inhibitor design.