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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