Quantitative structure-bioactivity relationships

Certain computational methodologies such as some approaches to quantitative structure-activity relationship (QSAR) studies use 3D ligand structures [37, 38]. These methods generally assume that a bioactive conformation has been estab-Hshed for a set of molecules and that these conformers can be ahgned in a maimer that reflects the relative orientation they would adopt in a binding site. It is thus... 

Cuba, W. and Cruciani, G. Molecular field-derived descriptors for the multivariate modelling of pharmacokinetic data, in Mdecular Modelling and Prediction of Bioactivity, Proceedings of the 12th European Symposium on Quantitative Structure-Activity Relationships (QSAR 98), Gundertofte, K. and Jorgensen, F.S. (Eds). Plenum Press, New York, 2000, 89-95. 

The underlying theory of Quantitative Structure-Activity Relationship (QSAR) is that biological activity is directly related to molecular structure. Therefore, molecules with similar structure will possess similar bioactivities for similar proteins/receptors/enzymes and the changes in structure will be represented through the changes in the bioactivities. The best general description of a QSAR model is... 

Correlating analog structure with bioactivity via quantitative structure-activity relationship (QSAR) studies... 

The correlation of bioactivity data with Eq. 1 or some relationship derived from it results, if successful, in a correlation equation called a quantitative structure activity relationship (QSAR). 

For years, we have been studying QSAR (quantitative structure-activity relationship) analyses of pesticides and other bioactive compounds. In many examples, we have found a decisive role of the steric effect in determining the activity variation. In this chapter, applications of various steric constants such as E E°, Vw and STERIMOL parameters to QSAR studies mostly from our own laboratory are reviewed. 

Schaper, K. J. and J. K. Seydel. 1985. Multivariate methods in quantitative structure-pharmacokinetics relationship analysis. IrQSAR and Strategies in the Design of Bioactive CompquuHted by J. K. Seydel, pp. 173-189. Weinheim, Germany VCH. 

Lajiness MS (1991) Evaluation of the performance of dissimilarity selection methodology. In Silipo C, Vittoria A (eds) QSAR rational approaches to the design of bioactive compounds. Proceedings of the VIII European symposium on quantitative structure-activity relationships. Sorrento, Italy, 9-13 Sept 1990. ESCOM, Leiden, pp 201-204... 

These efforts were guided by the study of quantitative structure-activity relationships (QSAR) following the Hansch approach. In this method linear free-energy related and other electronic, hydrophobic, and steric substituent constants are used for a quantitative analysis of the possible ways in which substituents may modulate bioactivity in a congeneric series. In the QSAR studies of benzoylphenyl ureas the electronic Hammett a-constants and the hydro-phobic Hansch n-constants were used. To measure the steric influences, steric substituent constants of a new type (B1,B2,B3,B4, and L) were applied which had recently been introduced by us and which give improved correlations in comparison with the steric Es constants used in the literature hitherto (21, 22). The constants B- toBj are measures of the widths of substituents in four rectangular directions. The L-constant accounts for the length of a substituent ... 

J. K. Seydel, QSAR and Strategies in the Design of Bioactive Compounds. Proceedings of the 5th European Symposium on Quantitative Structure-Activity Relationships, Bad Segeberg, Federal Republic of Germany, 17-21 September 1984, VCH, Weinheim,... 

Cruciani G, Crivori P, Carrupt PA, Testa B (2000) Molecular fields in quantitative structure-permeation relationships The VolSurf approach. Theochem 503 17-30 Cruciani G, Pastor M, Clementi S (2000) Handling information from 3D GRID maps for QSAR studies. In Gun-dertofte K, Jorgensen FS (eds) Molecular modelling and prediction of bioactivity, proceedings of the 12th European symposium on quantitative structure-activity relationships (QSAR 98). Plenum Press, New York, pp 73-81 Cruciani G, Pastor M, Guba W (2000) VolSurf A new tool for the pharmacokinetic optimization of lead compounds. Eur J Pharm Sd 11 S29-S39... 

Ray, S.K., Basak, S.C., Raychaudhury, C, Roy, A.B. and Ghosh, J.J. (1981). Quantitative Structure-Activity Relationship Studies of Bioactive Molecules Using Structural Information Indices. Indian J.Chem., 20B, 894-897. 

Quantitative Structure-Cytotoxicity Relationship of Bioactive Heterocycles by the Semi-empirical Molecular Orbital Method with the Concept of Absolute Hardness... 

The third chapter, Quantitative Structure-Cytotoxicity Relationship of Bioactive Heterocycles by the Semi-empirical Molecular Orbital Method with the Concept of Absolute Hardness by Mariko Ishihara, Hiroshi Sakagami, Masami Kawase, and Noboru Motohashi, presents the relationship between the cytotoxicity (defined as 50% cytotoxic concentration) of heterocycles such as phenoxazine, 5-trifluoromethyloxazoles, O-heterocycles such as 3-formylchromone and coumarins, and vitamin K2 derivatives against some tumor cell lines and 15 chemical descriptors. The results suggest the importance of selecting the most appropriate descriptors for each cell type and compound. The review is of interest as it represents the relationship of the molecular structures with the cytotoxic activity of these heterocycles. 

Zhang et al. [36] combine DFT-based conformation analysis with quantitative structure-activity relationship (QSAR) analysis. They looked at bioactive conformations for 25 cyclic imide derivatives as proto-porphyrinogen oxidase (PPO) inhibitors. PPO is the last common enzyme in the biosynthetic... 

Lebez, M., Solmajer, T. and Zupan, J. (2002) Quantitative structure-activity relationship of tricyclic carbapenems application of artificial intelligence methods for bioactivity prediction. Croat. Chem. Acta, 75, 545-562. 

Lin, T.-H. and Lin, J.-J. (2001) Three-dimensional quantitative structure-activity relationship for several bioactive peptides searched by a convex hull-comparative molecular field analysis approach. Computers Chem., 25, 489—498. 

Variables commonly used in PARs and SARs are summarized in Table 4. The main processes of interest relative to the bioactivity of aquatic contaminants are bioaccumulation, biodegradation, and acute toxicity (LC50), but inhibition of key biological processes such as respiration rate and photosynthesis also are used in some PARs and SARs as measures of a compound s toxicity. The physicochemical properties listed in Table 4 reflect molecular structure, but they are not structural characteristics themselves. Relationships based on these properties thus should be called property-activity relationships (PARs), and the term (quantitative) structure-activity relationship, (Q)SAR should be restricted to relationships based on structural or topological parameters. However, the literature is not consistent in this terminology, and the line between structural characteristics and properties resulting from structure is not always clear. 

C. Lemmen, T. Lengauer, in K. Gundertofte, F. S. Jorgensen (Eds.) Molecular modelling and prediction of bioactivity, Proceeding of the 12th European symposium on quantitative structure-activity relationships, Plenum Press, New York 1999, 169-174. 

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