Scientific shape-based method

To exemplify a molecular similarity method, we employed here a 3D shape-based molecular similarity approach using OpenEye scientific software (OpenEye). A set of 27 molecules (Amoore, 1971) were compared to benzaldehyde (query molecule). The representation used here is based on the volume of each molecule. A conformational ensemble is built for the molecules in the database, whereas the conformation of the query remains fixed (the chemical nature of benzaldehyde does not entail different conformers, though in many cases the conformation of the query molecules might be complex and crucial). After the conformers of each molecule in the data set are built, each one of them is compared with the query and a similarity value is computed. For the particular program employed here (ROCS), the similarity is quantified as a score formed by two terms, one takes into account the chemical nature of the molecules while the other relies on molecular shape, such score is referred to as combo score. The maximum similarity value is 2 which can only be obtained from the comparison of a molecule with itself in the exact same conformation (perfect match). The normalized values (from 0 to 1) for the odor and combo score similarities are compared in the graph shown in Fig. 2.4. As can be observed, as the combo score increases, the odor similarity to benzaldehyde also increases. This correlation shows that part of the odor similarity was captured by the molecular... 

These methods include estimating failure rate data using models or correlations developed from an engineering or scientific analysis of the influences on the reliability of particular types, classes, or groups of equipment. For example, Thomas provides a factor-based technique for estimating the probability of catastrophic leakage from a pipe or pressure vessel. Factors include size and shape influences, weld zones, facility age, and other quality factors (CCPS, 2000). 

Reviewing the calculation methods as implemented in the various pressure vessel codes (see Table 4.3-1) shows that these are based on the scientific formulae as per Table 4.3-2 but partly appear in a different shape due to approximations, simplifications, additional safety margins and other factors taking care of manufacturing tolerances, weakening by corrosion and welding seams [3] [4] [5] involved. 

A further important option for ligand-based virtual screening is to perform shape comparisons that have a pronounced scaffold hopping potential. An often used method of this kind is ROCS [31] (OpenEye Scientific Sofiware, 9 Bisbee Court Suite D, Santa Fe, NM 87508, USA. Available at http //www.eyesopen.com, March 20, 2009). ROCS employs continuous functions that are derived from atom-centered Gaussians to calculate the volume overlap between two 3D structures. The use of Gaussians drastically speeds up the computational process, and ROCS is able to search even databases with millions of compounds for molecules that can adopt shapes similar to the reference compound. As in the case of 3D pharmacophore searches, the low-energy conformations must be precomputed for the search database. 

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