3D-QSAR Analysis

Ekins S, Bravi G, Wikel JH, Wrighton SA. Three dimensional quantitative structure activity relationship (3D-QSAR) analysis of CYP3A4 substrates. J Pharmacol Exp Ther 1999 291 424-33. 

A 3D-QSAR analysis of in vitro binding affinity and selectivity of 3-izoxazolyl-sulfonylaminothiophenes as endothelin receptor antagonists. Quant. Struct.-Act. Relot. 1999, 18, 124-133. 

SiPPL, W. Receptor-based 3D QSAR analysis of estrogen receptor ligands — merging the accuracy of... 

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. 

Summary of the 3D-QSAR Analysis Results for the 49 HIV-1 Protease Inhibitors Using the 3D-LogP Descriptor and Statistical Comparison with the Comparative Binding Energy Analysis (50) (COMBINE)... 

Pastor, M., Cmciani, G., and Watson, K. (1997) A strategy for the incorporation of water molecules present in a ligand binding site into a 3D QSAR analysis.. /. Med. Chem. 40, 4089-4102. 

Constantino et al. used the combination of a docking-based alignment and 3D QSAR analysis to build a predictive model for 46 poly(ADP-ribose)polymer-ase (PARP) inhibitors [67]. Representative PARP inhibitors were docked into... 

Zhou, Z., Madura, J.D. 3D QSAR Analysis of HIV-1 RT Nonnucleoside Inhibitors, TIBO Derivatives Based on Docking Conformation and Alignment. /. Chem. Inf Comput. Sci. 2004, 44, 2167-2178. 

Interesting information in this context was also provided by the work of Feher and Schmidt, who proposed two possible alignments between CA4 and other important CSI, including colchicine [33], The represented a test for the newly developed MultiSEAL procedure, which allows the application of the steric and electrostatic alignment (SEAL) [34] method to multiple conformations of multiple molecules. It should be emphasized that, when robust, an alignment method can be profitably used not only to prepare compounds for a 3D-QSAR analysis, but also to identify and locate potential pharmacophoric groups in a set of structurally diverse molecules. The CSI used by Feher and Schmidt were colchicine, CA4, allocolchicine (6), 2-methoxy-5-(2, 3, 4 -trimethoxyphenyl)-tropone (MTC) (7) and 2-methoxyestradiol (8) (Chart 5). 

D-QSAR. Since compounds are active in three dimensions and their shape and surface properties are major determinants of their activity, the attractiveness of 3D-QSAR methods is intuitively clear. Here conformations of active molecules must be generated and their features captured by use of conformation-dependent descriptors. Despite its conceptual attractiveness, 3D-QSAR faces two major challenges. First, since bioactive conformations are in many cases not known from experiment, they must be predicted. This is often done by systematic conformational analysis and identification of preferred low energy conformations, which presents one of the major uncertainties in 3D-QSAR analysis. In fact, to date there is no computational method available to reliably and routinely predict bioactive molecular conformations. Thus, conformational analysis often only generates a crude approximation of active conformations. In order to at least partly compensate for these difficulties, information from active sites in target proteins is taken into account, if available (receptor-dependent QSAR). Second, once conformations are modeled, they must be correctly aligned in three dimensions, which is another major source of errors in the system set-up for 3D-QSAR studies. 

Shaguffa, Kumar A, Panda G, Siddiqi MI (2007) CoMFA and CoMSIA 3D-QSAR analysis of diaryloxy-methano-phenanthrene derivatives as anti-tubercular agents. J Mol Model 13 99-109... 

Three novel pteridine alkaloids bearing two pteridine units and a tryptophan core have been isolated from the sponge Clathria sp <02T4481>. Structural requirements for inhibition of neural nitric oxide synthase (NOS-I) and 3D-QSAR analysis of 4-oxo-pteridine-based and 4-amino-pteridine-based inhibitors have been reported <02JMC2923>. 

On the basis of this equation Zou et al. have concluded that hydrophobic compounds with inductively electron-donating ortho substituents would be favorable for the activity [193]. In continuation of this, Zou and coworkers have carried out CoMFA-based 3D-QSAR analysis of these compounds together with 5-[l-aryl-l,4-dihydro-6-methylpyridazin-4-one-3-ylj-2-arylamino- 1,3,4-oxadiazoles [ 194]. Here also the antifungal activity of these compounds has been found to be well explained by their steric and electrostatic properties. In addition to this, it has confirmed the bioisosterism... 

The most commonly used and possibly even classical method of 3D QSAR analysis is the Comparative Molecular Field Analysis (CoMFA) technique introduced by R. Cramer et al. in 1988. In almost 20 years since, it has seen substantial development and enhancement, as well as the creation of several related approaches. In general terms, it aims to identify the spatial regions around the molecule where certain local properties have a positive or negative effect on activity. 

J. S. Tokarski and A. J. Hopfinger, Prediction of ligand receptor binding thermodynamics by free energy force field (FEFF) 3D-QSAR analysis application to a set of peptidometic renin inhibitors., J. Chem. Inf. Comput. Sci., 1997, 37, 792-811. 

The pharmacophore concept plays a very important role in guiding the drug discovery process. Pharmacophore models help medicinal chemists gain an insight into the key interactions between ligand and receptor when the receptor structure has not been determined experimentally. A pharmacophore can be used as a basis for the alignment rules in 3D-QSAR analysis for the lead compound optimization... 

A series of pyridine-based nicotine congeners (76- 80) in which and R2 were H or a variety of substituents was subjected to 3D-QSAR analysis of their ability to bind to central receptors (128). 

Nakagawa Y, Wheelock CE, Morisseau C, Goodrow MH, Hammock BG, Hammock BD. 3D-QSAR analysis of inhibition of murine soluble epoxide hydrolase (MsEH) by benzoylureas, arylureas, and their analogues. Bioorg Med Chem 2000 8 2663-73. 

Liu H, Ji M, Luo X, Shen J, Huang X, Hua W, et al. New p-methylsulfonamido phenylethylamine analogues as class III antiarrhythmic agents Design, synthesis, biological assay, and 3D-QSAR analysis. 7 Med Chem 2002 45 2953-69. 

Kim KH. 3D-QSAR analysis of 2,4,5- and 2,3,4,5-substituted imidazoles as potent and nontoxic modulators of P-glycoprotein mediated MDR. Bioorg Med Chem 2001 9 1517-23. 

Sippl, W. Receptor-based 3D QSAR analysis of estrogen receptor ligands-merging the accuracy of receptor-based alignments with the computational efficiency of hgand-based methods. J. Comput-Aided Mol. Des. 2000,14,559-572. 

The aim of any 3D QSAR study is to determine a correlation between a compound s molecular field and its biological activity, that is, the affinity to its target. One of the first steps is to delineate which parts of the molecules form a common core substructure, and which side chains are responsible for specific interactions. These facts will determine for the most part, how the compounds are to be superimposed in the grid for the molecular field calculation. From the user s point of view, a typical 3D QSAR analysis workflow (Figure 29.2) contains several consecutive steps ... 

The quality and reliability of any 3D QSAR model is strongly dependent on the careful examination of each step within a 3D QSAR analysis. As with any QSAR method, an important point to consider is if the biological activities... 

---