Effect of steric molecular field settings on CoMFA predictivity

Mittal, Ruchi; Sorich, Michael J.

doi:10.1007/s00894-007-0252-1

Cited by 14 publications

(11 citation statements)

References 41 publications

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“…Mittal et al previously concluded that the CoMFA steric field calculated using the steeper Lennard-Jones potential tends to perform better than CoMSIA steric field calculated with Gaussian version, which has a slower and smoother decrease [31]. Indeed, this is true when comparing predictive ability of CoMSIA Model SE with the related In terms of the statistical results, the CoMSIA EH model was found to be the best, except for predictive correlation coefficient r pred 2 that, still, remains statistically significant.…”

Section: Comsia Model and Its Predictive Powermentioning

confidence: 99%

Molecular docking and 3D-quantitative structure activity relationship analyses of peptidyl vinyl sulfones: Plasmodium Falciparum cysteine proteases inhibitors

Teixeira

Gomes

Couesnon

et al. 2011

J Comput Aided Mol Des

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Comparative molecular field analysis (CoM-FA) and comparative molecular similarity indices analysis (CoMSIA) based on three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were conducted on a series (39 molecules) of peptidyl vinyl sulfone derivatives as potential Plasmodium Falciparum cysteine proteases inhibitors. Two different methods of alignment were employed: (i) a receptor-docked alignment derived from the structure-based docking algorithm GOLD and (ii) a ligand-based alignment using the structure of one of the ligands derived from a crystal structure from the PDB databank. The best predictions were obtained for the receptor-docked alignment with a CoMFA standard model (q 2 = 0.696 and r 2 = 0.980) and with CoMSIA combined electrostatic, and hydrophobic fields (q 2 = 0.711 and r 2 = 0.992). Both models were validated by a test set of nine compounds and gave satisfactory predictive r 2 pred values of 0.76 and 0.74, respectively. CoMFA and CoM-SIA contour maps were used to identify critical regions where any change in the steric, electrostatic, and hydrophobic fields may affect the inhibitory activity, and to highlight the key structural features required for biological activity. Moreover, the results obtained from 3D-QSAR analyses were superimposed on the Plasmodium Falciparum cysteine proteases active site and the main interactions were studied. The present work provides extremely useful guidelines for future structural modifications of this class of compounds towards the development of superior antimalarials.

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Section: Comsia Model and Its Predictive Powermentioning

confidence: 99%

Molecular docking and 3D-quantitative structure activity relationship analyses of peptidyl vinyl sulfones: Plasmodium Falciparum cysteine proteases inhibitors

Teixeira

Gomes

Couesnon

et al. 2011

J Comput Aided Mol Des

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“…An explanation of these results may be traced back to the performance of individual molecular fields. It was previously concluded, that the CoMFA steric field calculated using the steeper Lennard Jones potential performs statistically significantly better than CoMSIA steric fields calculated using the smoother Gaussian potential [18]. When electrostatic fields calculated using the Coulomb and Gaussian potentials were compared in a similar fashion, no statistical significant difference was observed.…”

Section: Comparison Of Comfa and Comsia Using Steric And Electrostatimentioning

confidence: 81%

“…Although there was a general trend for improved predictive ability with smaller grid spacing, the effect was not statistically significant and hence the results presented here are in concordance with most of the literature. This is different, however, from a previous study that indicated that increased sampling density resulted in increased predictive performance [65]. The previous study was based on CoMFA models that were generated using only the steric molecular field as compared to the more realistic scenario in the current study in which standard combinations of molecular fields are used.…”

Section: Effect Of Lattice Spacingmentioning

confidence: 89%

“…These studies, however, were limited by the small number of datasets used in the comparison and thus the generalizabililty of these results is difficult to determine. Recently, it has been demonstrated that when comparing the predictive ability of 3D-QSAR models based on the Lennard Jones steric molecular field or the Gaussian steric molecular field alone, the Lennard Jones steric molecular field resulted in models with statistically significantly better predictivity [18]. Whether this is important when multiple molecular fields are used together for a 3D-QSAR model is unknown.…”

Section: Introductionmentioning

confidence: 96%

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The Effect of Molecular Fields, Lattice Spacing and Analysis Options on CoMFA Predictive Ability

Mittal

Sorich

2009

QSAR Comb. Sci.

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Comparative Molecular Field Analysis (CoMFA) is a popular Three-Dimensional Quantitative Structure -Activity Relationship (3D-QSAR) method. The effect of varying molecular fields [CoMFA vs. Comparative Molecular Similarity Indices Analysis (CoMSIA)], lattice spacing and analysis options on predictive performance was assessed based on cross validated R 2 values of 30 datasets taken from the literature. The CoMFA method results in statistically significantly higher cross validated R 2 values compared to CoMSIA when only steric and electrostatic fields are used. When the hydrophobic molecular field is included in the CoMSIA analysis (as is most commonly the case) the difference between CoMFA and CoMSIA is no longer statistically significant. Addition of hydrogen bond field does not improve CoMFA predictivity. Although there was a trend towards increased predictivity with decreased lattice spacing, this was not statistically significant. Altering the default filtering criteria and cut-off values for Lennard Jones and Coulomb fields also did not generally result in a statistically significant effect on predictive performance.

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“…16,17 Studies have sought to enhance QSAR quality by adjusting these factors optimally. [18][19][20][21][22] In CoMFA and CoMSIA studies, molecular mechanics (MM) are widely used in calculating interactions energies because of speed. In contrast, quantum mechanics (QM) methods demand time and computational resource.…”

Section: 7mentioning

confidence: 99%

Various Partial Charge Schemes on 3D-QSAR Models for P-gp Inhibiting Adamantyl Derivatives

Gadhe¹,

Madhavan²,

Kothandan³

et al. 2011

Bulletin of the Korean Chemical Society

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We developed three-dimensional quantitative structure activity relationship (3D-QASR) models for 17 adamantyl derivatives as P-glycoprotein (P-gp) inhibitors. Eighteen different partial charge calculation methods were tested to check the feasibility of the 3D-QSAR models. Best predictive comparative molecular field analysis (CoMFA) model was obtained with the Austin Model 1-Bond Charge Correction (AM1-BCC) atomic charge. The 3D-QSAR models were derived with CoMFA and comparative molecular similarity indices analysis (CoMSIA). The final CoMFA model (q 2 = 0.764, r 2 = 0.988) was calculated with an AM1-BCC charge and electrostatic parameter, whereas the CoMSIA model (q 2 = 0.655, r 2 = 0.964) was derived with an AM1-BCC charge and combined steric, electrostatic, hydrophobic and HB-acceptor parameters. Leavefive-out (LFO) cross-validation was also performed, which yielded good correlation coefficient for both CoMFA (0.801) and CoMSIA (0.656) models. Robustness of the developed models was checked further with 1000 run bootstrapping analyses, which gave an acceptable correlation coefficient for CoMFA (BS-r 2 = 0.997, BS-SD = 0.003) and CoMSIA (BS-r 2 = 0.996, BS-SD = 0.018).

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Effect of steric molecular field settings on CoMFA predictivity

Cited by 14 publications

References 41 publications

Molecular docking and 3D-quantitative structure activity relationship analyses of peptidyl vinyl sulfones: Plasmodium Falciparum cysteine proteases inhibitors

Molecular docking and 3D-quantitative structure activity relationship analyses of peptidyl vinyl sulfones: Plasmodium Falciparum cysteine proteases inhibitors

The Effect of Molecular Fields, Lattice Spacing and Analysis Options on CoMFA Predictive Ability

Various Partial Charge Schemes on 3D-QSAR Models for P-gp Inhibiting Adamantyl Derivatives

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