CoMFA models

T Kimura, K Hasegawa, K Funatsu. GA strategy for variable selection m QSAR studies GA-based region selection for CoMFA modeling. J Chem Inf Comput Sci 38 276-282, 1998. 

Among others, 11 was included in a series of drugs to study quantitative structure-activity relationships (96KFZ(6)29, 98MI7, 99BMC2437). A statistically significant CoMFA model was developed for describing the... 

DePriest SA, Mayer D, Naylor CB, Marshall GR. 3D-QSAR of angiotensinconverting enzyme and thermolysin inhibitors a comparison of CoMFA models based on deduced and experimentally determined active site geometries. J Am Chem Soc 1993 115 5372-84. 

Sipila J, Hood AM, Coughtrie MW, Taskinen J. CoMFA modeling of enzyme... 

Lopez-Rodriguez, M.L., Rosado, M.L., Benhamu, B., Morcillo, M.J., Fernandez, E. and Schaper, K.-J. (1997) Synthesis and structure-activity relationships of a new model of arylpiperazines. 2. Three-dimensional quantitative structure-activity relationships of new hydantoin-phenylpiperazine derivatives with affinity for 5-HTIA and oq receptors. A comparison of CoMFA models. Journal of Medicinal Chemistry, 40, 1648-1656. 

Gomplex field-based 3-D QSAR models have also been applied to the problem of predicting hERG activity. Gavalli ef al. [85] used a CoMFA model, as previously discussed. Pearlstein ef al. [89] modeled a set of sertindole analogs using compara-... 

Standard alignment of 202 artemisinin analogs used in the CoMFA model development. 

Structure Generation, QSAR, and CoMFA Modeling Methods. 

SD=. 243, r2 =. 942, ancF = 146. The contribution of each parameter in the two CoMFA models is listed in Table 3.5. The experimental and calculated mole fraction solubilities by model 2 using CoMFA, mp, and IHB as predictors are listed in Table 3.6. 

To test the applicability of this approach, eight compounds were randomly removed. The remaining 52 compounds were used to develop a CoMFA model. The resultant model was then used to predict the solubility of the removed compounds. Results (Table 3.7) show that predicted values agree well with the experimental values. 

The q2 value of a CoMFA model, together with other statistical information from the pis analysis, provides information on the predictive capability of the model. In this study we have generated CoMFA models that describe the pharmacophore either with or without the involvement of hemin, both of which provide good q2 values. Selection of the model that most accurately depicts reality is not trivial since many variables are inherent in the cell-culture bioassay results. However, it may be... 

We chose to design and then synthesize a class of compounds heretofore unknown in the artemisinin area 8,8-disubstituted-D-norartemisinins. While the parent molecule 421 was not predicted in the CoMFA models to be highly active, homologues of 421 were.155... 

The predictions from the achiral CoMFA model 199 (2 A/C.3), which includes the racemates, best reflects experimentally derived antimalarial activities. The predicted value for the natural enantiomer of 421 was 110% of artemisinin and 12%... 

Table 20. Prediction Values for 421 and 422 in Different CoMFA Models...

In 1993, Martin and colleagues performed a follow-up study on the same 15 compounds using CoMFA. CoMFA does not produce a simple equation in the manner of Hansch analysis, but CoMFA does calculate activities for the training set compounds. Comparing the predicted and experimental activities allows determination of the model s correlation coefficient. The CoMFA performed by Martin gave an r-value of 0.96. Martin s CoMFA model accounted... 

To continue the comparison, Martin prepared an additional set of 12 analogues of 12.18 and determined their activity against the 5-HT2 receptor. Both Nelson s Hansch equation and Martin s CoMFA model were used to generate calculated activities of the 12 new compounds. The summary of the findings is shown in Table 12.8. 

The data in Table 12.8 do not represent a resounding victory for CoMFA over Hansch analysis. However, a significant advantage of CoMFA is its flexibility. Martin continued his study by including an additional 30 compounds in his CoMFA model. The additional compounds are analogous to 12,18 but contain significantly more structural variability with R-group modifications at C-2,... 

Martin s expanded CoMFA model gave an r-value of 0.92. Six new analogues of 12.18 were prepared, and their activities were predicted with the new model. The RMS of the experimental and calculated activity differences was only 0.36. 

In the Case Study at the end of the chapter, a CoMFA model based on a 15-compound training set had an r-value of 0.96. When the model was expanded to a much more diverse collection of 45 compounds, the r-value dropped to 0.92. Explain why the second CoMFA model is impressive despite the decrease in the r-value. 

Family Target No. of Biophore model CoMFA model... 

Additionally, computational chemists often use the resulting output alignment of the molecules as input for 3D-QSAR modeling. As already stated, most field-based 3D-QSAR approaches (such as CoMFA) need a pre-aligned set of molecules and the pharmacophore method is certainly one of the best ways to obtain an objective alignment of the compounds. Klabunde et al., for instance, have recently reported the use of a pharmacophore model of human liver glycogen phosphorylase inhibitors together with 3D information from inhibitor-enzyme complexes to derive a predictive CoMFA model [98]. 

Chart 3 General structure of 2-phenyl-4-quinolones (X=CH) and 2-phenyl-1,8-naphthyridin-4-ones (X=N) used by Weigt and Weise to generate their CoMFA model... 

M. Fan et al., Comparison of CoMFA models for Salmonella typhimurium TA98, TA100, TA98+S9 and TA100+S9 mutagenicity of nitroaromatics. SAR QSAR Environ. Res. 9, 187-215 (1998)... 

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