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Title: Entropy-variability analysis of the nuclear receptor ligand binding domain
P36
Folkertsma, Simon; Bettler, Emmanuel; van Durme, Joost; Joosten, Henk-Jan; Oliveira, Laerte; de Vlieg, Jacob; Vriend, Gert

simon@cmbi.kun.nl
CMBI

Nuclear receptors are of enormous importance for the pharmaceutical industry as potential targets for therapy of diseases such as breast cancer, diabetes and osteoporosis. In the process of drug design it is crucial to know the function of each amino-acid in the ligand binding domain of this receptor class. To achieve this goal we performed an entropy-variability analysis on the ligand binding domain of the nuclear receptors. This is a new method of analysing families of protein sequences which has already been applied to globins, ras-like proteins, and serine-proteases. In these protein families the method was able to predict the positions in the alignment related to
the main function, ligand binding capacity, and positions in the core or at the surface of the protein.
A reliable multiple sequence alignment of the nuclear receptor ligand binding domain is required for the analysis. Numerous crystal structures of nuclear receptor ligand binding domains (LBDs) have been solved in recent years. All LBDs show a characteristic anti-parallel 'alpha-helical sandwich' fold, despite their sequence differences.
A multiple sequence alignment was produced by superposing the 3D structures of all known nuclear receptor LBDs. We found 185 residues to be structurally conserved in all nuclear receptor LBDs. Two simple parameters are defined for each position in the alignment: variability (number of different amino acids) and entropy (frequency of occurrence of the possible amino acids). We found that the position of an aligned residue in an entropy-variability plot correlates with structural characteristics, and with known facts about the roles of individual amino acids in the function of these proteins.
The results of this study will lead to a better understanding of the nuclear receptor ligand binding domain, which is needed in the process of drug design and discovery.