Molecular shape analysis, visualization

P.G. Mezey, "Non-Visual Molecular Shape Analysis Shape Changes in Electronic Excitations and Chemical Reactions," in Computational Advances in Organic Chemistry (Molecular Structure and Reactivity), C. Ogretir and I. Csizmadia (Eds.), Kluwer Academic Publishers, Dordrecht, 1991. 

The above topological shape analysis techniques can replace visual shape comparisons of molecular models on the computer screen with precise, reliable, and reproducible numerical comparisons of topological shape codes. These comparisons and the similarity or complementarity rankings of molecular sequences can be performed by the computer automatically. This eliminates the subjective element of visual shape comparisons, a particularly important concern if large sequences (e.g. several thousands) of molecules are to be compared. In the data banks of most drug companies there is information stored on literally hundreds of thousands of molecules, and their detailed shape analysis by visual comparison on a computer screen is clearly not feasible. By contrast, automatic, numerical, topological shape analysis by computer is a viable alternative. 

Algorithms Infrared Data Correlations with Chemical Structure Infrared Spectra Interpretation by the Characteristic Frequency Approach Machine Learning Techniques in Chemistry Molecular Models Visualization Neural Networks in Chemistry NMR Data Correlation with Chemical Structure Partial Least Squares Projections to Latent Structures (PLS) in Chemistry Shape Analysis Spectroscopic Databases Spectroscopy Computational Methods Structure Determination by Computer-based Spectrum Interpretation Zeolites Applications of Computational Methods. 

A complete review of spectroscopic methods applied to the analysis of alkyl-modified surfaces with a comprehensive list of spectroscopic indicators of alkyl chain conformational order is provided elsewhere [9] this review will focus on the application of spectroscopic and other relevant experimental techniques for the characterization of shape-selective chromatographic materials. On the whole, it has been observed experimentally that any increase in alkyl stationary-phase conformational order promotes an increase in selectivity for shape-constrained solutes in RPLC separations [9], As a complement to the wealth of spectroscopic and chromatographic data, the use of molecular simulation techniques to visualize and characterize alkyl-modified surfaces may also provide new insights into molecular-level features that control shape selectivity. A review of progress in the field of chromatographic material simulations will also be discussed. 

Both aspects will be taken into account in our analysis these should provide, on the one hand, a visualization of the features of molecular charge distribution — i. e. comparisons and relationships among different molecules or among similar chemical groups placed in different chemical frames — and, on the other hand, an approximate picture of the capability of the molecule in question to interact with other chemical species. The more correct the first-order approximation, the sharper this picture becomes. It is particularly well suited for regions at medium or large distances from the molecule where reaction channels begin to assume a definite shape. 

---