RECCR Rensselaer Exploratory Center for Cheminformatics Research


Molecular Lipophilicity Potential



PI:Curt M. Breneman

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Protein Dissimilarity Analysis using Shape/Property Descriptors


To date, very few studies has been done on the relationship between retention of proteins in HIC and the physicochemical properties of proteins such as size, surface hydrophobicity. In other words, if the similarity/dissimilarity between different protein structures could be quantified, it will help us to recognize common features of proteins with similar retention/binding behavior in HIC systems, help us to understand the mechanism behind protein interactions with the stationary phases, as well as to predict the retention behavior of proteins in HIC systems.

A new technique, which we call PPEST (Protein Property-Encoded Surface Translator), is developed based on the PEST algorithm (Breneman et al., 2003) for describing the shape and property distribution of proteins. This method uses a technique akin to ray-tracing to explore the volume enclosed by a protein. Probability distributions are derived from the ray-trace, and based solely on the geometry of the reflecting ray, or may include joint dependence on properties, such as the molecular lipophilicity potentials (MLP) (Audry et al., 1986; Kellogg et al., 1991; Heiden et al., 1993) and molecular electrostatic potential (MEP). These probability distributions, stored as histograms, make a unique profile for each protein and they are independent of molecular orientation. Clearly, the profiles are useful only in being compared. In brief, these profiles generated by PPEST can be rapidly compared to test for similarity between one protein and another. The triangulated protein surface subjected to internal ray-reflection is derived from the GaussAccessible surface provided by MOE (Chemical Computing Group, version 2004.03), which is a Gaussian approximation to a probe sphere’s accessibility, calculated by rolling a sphere of a given probe radius over the surface of the protein.

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