Fragmental Methods in the Analysis of Biological Activities of Diverse Compound Sets

被引:22
作者
Japertas, P. [1 ,2 ]
Didziapetris, R. [1 ]
Petrauskas, A. [1 ]
机构
[1] Pharma Algorithms Inc, Tauro 12, LT-2001 Vilnius, Lithuania
[2] Vilnius Univ, Fac Chem, LT-2006 Vilnius, Lithuania
关键词
Fragmental methods; biological activity prediction; mechanistic approach; classification analysis;
D O I
10.2174/1389557033487601
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
The current mini-review explains how fragmental methods (FMs) can be used in the analysis and prediction of physicochemical properties and biological activities. The considered properties include log P, solubility, pK(a), intestinal permeability, P-gp substrate specificity and toxicity. The focus will be a description of a "mechanistic" approach, which implies a gradual reduction of alternative explanations for any property or activity. This means a flexible construction of fragmental parameters using large amounts of experimental data. Since biological activities involve multiple (unknown) target macromolecules with multiple binding modes, a stepwise classification (C-SAR) analysis is most useful. It involves the following procedures: (i) construction of physicochemical profiles using parameters that can be reliably predicted, (ii) identification of reactive functional groups and the largest active skeletons, (iii) generalization of these groups and skeletons in terms of "site-specific physicochemical profiling". This entails a dynamic construction of 2D pharmacophores that can be converted into 3D models.
引用
收藏
页码:797 / 808
页数:12
相关论文
共 67 条
[1]   The correlation and prediction of the solubility of compounds in water using an amended solvation energy relationship [J].
Abraham, MH ;
Le, J .
JOURNAL OF PHARMACEUTICAL SCIENCES, 1999, 88 (09) :868-880
[2]  
Albert A., 1951, SELECTIVE TOXICITY S
[3]   Predicting human oral bioavailability of a compound: Development of a novel quantitative structure-bioavailability relationship [J].
Andrews, CW ;
Bennett, L ;
Yu, LX .
PHARMACEUTICAL RESEARCH, 2000, 17 (06) :639-644
[4]  
[Anonymous], PRACTICAL APPL QUANT
[5]   Discriminating between drugs and nondrugs by prediction of activity spectra for substances (PASS) [J].
Anzali, S ;
Barnickel, G ;
Cezanne, B ;
Krug, M ;
Filimonov, D ;
Poroikov, V .
JOURNAL OF MEDICINAL CHEMISTRY, 2001, 44 (15) :2432-2437
[6]  
Avdeef Alex, 2001, Current Topics in Medicinal Chemistry, V1, P277, DOI 10.2174/1568026013395100
[7]   Classification of multidrug-resistance reversal agents using structure-based descriptors and linear discriminant analysis [J].
Bakken, GA ;
Jurs, PC .
JOURNAL OF MEDICINAL CHEMISTRY, 2000, 43 (23) :4534-4541
[8]  
BREMSER W, 1978, ANAL CHIM ACTA-COMP, V2, P355
[9]   Estimating the pKa of phenols, carboxylic acids and alcohols from semi-empirical quantum chemical methods [J].
Citra, MJ .
CHEMOSPHERE, 1999, 38 (01) :191-206
[10]   Ab initio calculations of absolute pKa values in aqueous solution I.: Carboxylic acids [J].
da Silva, CO ;
da Silva, EC ;
Nascimento, MAC .
JOURNAL OF PHYSICAL CHEMISTRY A, 1999, 103 (50) :11194-11199