Evaluation of pyridine-3-carboxylic acid as a drug carrier by utilizing multivariate methods, structure property correlations, and pattern recognition techniques.

Ronald L Bartzatt
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引用次数: 2

Abstract

Multivariate methods and molecular properties are utilized to show similarity of pyridine-3-carboxylic acid (nicotinic acid) to seven drugs that penetrate the central nervous system. Multivariate methods applied include cluster analysis, discriminant analysis, correspondence analysis, self organizing tree algorithm (SOTA) analysis, factor analysis, and principal component analysis. Numerical values of properties for nicotinic acid showed very high correlation with the values from dihydropyridine, barbital, metharbital, phenobarbital, methohexital, 4-aminohex-5-enoic acid, and (4-chlorophenyl)(5-fluoro-2-hydroxyphenyl)methanone. Descriptive statistics of property values for these drugs showed overlapping numerical values for partition coefficients, index of refraction, and nOnN. Principal component analysis and factor analysis of molecular properties showed that nicotinic acid is highly similar to dihydropyridine as well as to other members of this group of drugs. Applying cluster analysis utilizing standard euclidean distance with single linkage and centroid linkage showed that nicotinic acid is highly similar to dihydropyridine and both are consistently grouped into the identical cluster (indicating high similarity). Both nicotinic acid and dihydropyridine show zero violations of the Rule of 5, which indicates good bioavailability characteristics. Discriminant analysis of molecular properties for these eight compounds could not demonstrate differentiation between nicotinic acid and dihydropyridine within the properties applied, this indicating high level of similarity. Neural cluster analysis of molecular properties showed that nicotinic acid and dihydropyridine are included into the same cluster (indicating very strong similarity). SOTA analysis also placed nicotinic acid and dihydropyridine into the same cluster unit. SOTA analysis of molecular properties indicates high similarity between nicotinic acid and dihydropyridine. Correspondence analysis was performed on the molecular properties and showed that there exists considerable association between dihydropyridine and nicotinic acid. Multiple regression analysis of these molecular properties produced a mathematical equation to predict the formula weight of similar compounds for use as drug carriers.

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吡啶-3-羧酸作为药物载体的评价:利用多元方法、结构性质相关性和模式识别技术。
利用多变量方法和分子特性来显示吡啶-3-羧酸(烟酸)与七种穿透中枢神经系统的药物的相似性。多变量分析方法包括聚类分析、判别分析、对应分析、自组织树分析、因子分析和主成分分析。烟酸的性质数值与二氢吡啶、巴比妥、甲阿比妥、苯巴比妥、甲己酮、4-氨基己烯酸和(4-氯苯基)(5-氟-2-羟基苯基)甲烷酮的性质数值有很高的相关性。描述性统计显示,这些药物的分割系数、折射率和nOnN的数值重叠。分子性质的主成分分析和因子分析表明,烟酸与二氢吡啶以及该组药物的其他成员高度相似。利用单键和质心键的标准欧几里得距离进行聚类分析,发现烟酸与二氢吡啶高度相似,两者一致地归为同一聚类(表明相似性高)。烟酸和二氢吡啶均不违反规则5,表明具有良好的生物利用度特性。对这8个化合物的分子性质进行判别分析,不能证明烟酸和二氢吡啶在性质上的区别,这表明它们具有高度的相似性。分子性质的神经聚类分析表明,烟酸和二氢吡啶属于同一聚类,具有很强的相似性。SOTA分析还将烟酸和二氢吡啶置于同一簇单元中。SOTA分析表明,烟酸与二氢吡啶具有较高的相似性。对二氢吡啶和烟酸的分子性质进行了对应分析,结果表明二氢吡啶和烟酸之间存在相当大的关联。对这些分子性质进行多元回归分析,得出一个数学方程,用于预测用作药物载体的类似化合物的配方重量。
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