3D-QSAR CoMFA

D-QSAR (CoMFA, Catalyst, GRID/GOLPE,...) substrate behavior, relative rates, inhibitor behavior,...  

In Sect. 2.1, we have presented the 3D-QSAR CoMFA studies on a series of indole/benzoimidazole-5-carboxamidines as FXa inhibitors. Herein we present the 3D-QSAR/CoMFA models developed for the same series of indole/benzoimidazole-5-carboxamidines [69] as thrombin inhibitors, using 29 training set molecules and validated with seven test set molecules (Fig. 5). 

Coats, E. A. (1998) The CoMFA steroids as a benchmark dataset for development of 3D QSAR methods. Perspect. Drug Discov. Design 12/14, 199-213. 

Thaimattam, R., Daga, P., Rajjak, S.A., Banerjee, R., Iqbal, J. 3D QSAR CoMFA, CoMSIA Studies on Substituted Ureas as Raf-1 Kinase Inhibitors and its Confirmation with Stmcture-based Studies. Bioorg. Med. Chem. 2004, 12, 6415-6425. 

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. 

Dick Cramer provided insight and inspirahon that led to my interest in 3D QSAR methodology ]40] and was the impetus (the precursor of CoMFA was a lattice model [41] developed by Cramer and Milne at SKF) behind the development of CoMFA (Comparative Molecular Field Analysis) by Tripos [42], The success of CoMFA in 

Belvisi, L., Bravi, G, Catalano, G., Mabilia, M., Salimbeni, A. and Scolastico, C. (1996). A 3D QSAR CoMFA Study of Non-Peptide Angiotensin II Receptor Antagonists. J.Comput.Aid. Molec.Des., 10, 567-582. 

Molecular lipophilicity potential (MLP) has been developed as a tool in 3D-QSAR, for the visualization of lipophilicity distribution on a molecular surface and as an additional field in CoMFA studies [49]. MLP can also be used to estimate conformation-dependent log P values. 

Lopez-Rodriguez, M.L., Murda, M., Benhamu, B., Viso, A., Campdlo, M. and Pardo, L. (2002) Benzimidazole derivatives. 3. 3D-QSAR/CoMFA model and computational simulation for the recognition of 5-HT4 receptor antagonists. J. Med. Chem., 45, 4806 815. 

The variable selection methods have been also adopted for region selection in the area of 3D QSAR. For example, GOLPE [31] was developed with chemometric principles and q2-GRS [32] was developed based on independent CoMFA analyses of small areas of near-molecular space to address the issue of optimal region selection in CoMFA analysis. Both of these methods have been shown to improve the QSAR models compared to original CoMFA technique. 

Medvedev AE, Veselovsky AV, Shvedov VI, Tikhonova OV, Moskvitina TA, Fedotova OA, et al. Inhibition of monoamine oxidase by pirlindole analogues 3D-QSAR and CoMFA analysis. / Chem Inf Comput Sci 1998 38 1137-44. Miller JR, Edmondson DE. Structure-activity relationships in the oxidation of para-substituted benzylamine analogues by recombinant human liver monoamine oxidase A. Biochemistry 1999 38 13670-83. 

Imidazolinyl) derivative of 8-methyl-2,3,6,7-tetrahydro-5 f- and 8-methyl-7-methoxy-5-oxo-2,3-dihydro-5 f-pyrido[l, 2, i-de]-1,4-benzoxazines were included in a 3D-QSAR CoMFA study on imidazolinergic I2 ligands (00JMC1109). 

Moron, J.A., Campillo, M., Perez, V., Unzeta, M., Pardo, L. Molecular determinants of MAO selectivity in a series of indolylmethylamine derivatives biological activities, 3D-QSAR/CoMFA analysis, and computational simulation of ligand recognition./. Med. Chem. 2000, 43, 1684-1691. 

The popularity of commercial programs such as Comparative Molecular Field Analysis (4,12) (CoMFA) and Catalyst (13) has limited both the evaluation and use of other QSAR methodologies. Often well-known issues associated with CoMFA and Catalyst have come to be viewed as shortcomings that simply are accepted as working limitations in a 3D-QSAR analysis. In this section we challenge this position and present 3D- and nD-QSAR methods that are able to overcome some of the issues associated with current mainstream 3D-QSAR application products. 

Various endeavors have been undertaken to get insight into the 3D selector-selectand complex structures and to elucidate chiral recognition mechanisms of cinchonan carbamate selectors for a few model selectands (in particular, DNB-Leu). Such studies comprised NMR [92-94], ET-IR [94-96], X-ray diffraction [33,59,92,94], and molecular modeling investigations (the latter focusing on molecular dynamics [92,93,97], and 3D-QSAR CoMFA studies [98]). 

Note PRESS and q may relate to any property that is being modelled and not just activity , will always be smaller than r. When q > 0.3, a model is considered significant. Although cross-validation may seem a robust validation technique, some difficulties should not be overlooked. Variables that do not contribute to prediction, i.e. cause noise in the model, may have detrimental effects on CV. This may particularly play a role when many variables have to be considered, such as in a 3D-QSAR CoMFA analysis (see Chapter 25). A procedure for variable selection in the case of many variables has been developed and is named GOLPE (generating optimal linear PLS estimations).  

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