Prediction of Physicochemical Properties of Organic Compounds from Molecular Structure

Abstract

Relationships between molecular structure and biological activity or molecular structure and physical properties can be investigated for large sets of organic compounds using computer-assisted methods. Our research involves the design, implementation, testing, and application of computer software for the purpose of discovering structure-property and structure-activity relationships and thus developing the capability to predict properties for unknown compounds. The approach involves the graphical entry and storage of structures, three-dimensional molecular modeling, molecular structure descriptor generation, and analysis of the descriptors using pattern recognition methods or multivariate statistical methods. The computer-generated structural descriptors represent the molecules topologically (e.g., path counts, molecular connectivity), geometrically (e.g., molecular volume, surface area, principal moments), electronically (e.g., partial charges, bond orders), and physicochemically (e.g., log P, molar refractivity). A large, fully-integrated, interactive software system, called ADAPT for Automated Data Analysis and Pattern recognition Toolkit, has been developed to make such S AR and SPR research convenient. ADAPT is under continual development through the introduction of new molecular structure descriptors and new analysis methods. A number of successful studies have been reported in property prediction (prediction of boiling points of olefins, GC and HPLC retention indices, and simulation of 13C NMR chemical shifts) and in the structure-activity area (pharmaceutical drugs, olfactory stimulants, mutagens, carcinogens, anti-tumor drugs). Examples of current studies include: S AR of anti-tumor retinoids, carcinogenicity of N-nitroso compounds, HPLC retention indices of PACs and the importance of molecular shape, GC retention indices of polychlorinated biphenyls, 13C NMR simulation of substituted norbornanes.