Empirical Protein Adsorption Model derived from the Biomolecular Adsorption Database

The study of protein adsorption on surfaces has been an area of exhaustive research. In the past 5 decades, much has been published in the way of empirical results from protein adsorption studies. The recent progress in biotechnology has resulted in an explosive growth in available bio-medical data from pharmaceutical studies, cancer therapy investigations, proteomics, genomics and protein adsorption studies (Han July 2002). Consequently, several projects and databases exist to cater for the large volume of available data - the Human Genome Project (Watson 1990), several Proteomic Databases and Software (Wojcik and Schächter 2000 ), Medical Science Databases – AIDSTRIALS, ANSTI, MIMS Online (Medical Sciences Databases), Protein-Protein Interaction Databases – PPID (Protein to Protein Interaction Database), The Mamallian Protein-Protein Database (The MIPS Mammalian Protein-Protein Interaction Database), Protein-Ligand interaction databases – PLD (Protein Ligand Database), to name a few. Existing databases concentrate on proteomics, protein-protein or protein-ligand interactions. This work presents the development and reimplementation of a protein-surface (protein adsorption) database – the Biomolecular Adsorption Database and the application of this database in the generation of an Empirical Protein Adsorption Model. Prior to this work, the Biomolecular Adsorption Database in existence comprised only of protein descriptors and a separate surface database was being developed(Nicolau Jr and Nicolau 2002). This research unifies and expands on these concepts by creating one comprehensive database comprising of protein, solution and surface information where researchers can compare their results, can see what kind of experiments have already been conducted and from which data mining and modelling can be performed. The work presents the development and re-implementation of the Biomolecular database to integrate improved features, the evaluation of its statistical quality and its application in the generation of an empirical piecewise model for protein adsorption. The database and empirical model presented in this thesis is expected to be of future value in developing a possible strategy for the engineering-style, design oriented prediction of protein adsorption using databases and empirical models.