networks of high mutual information define the structural proximity of catalytic sites implications for catalytic residue identification网络的高互信息定义的结构接近催化对催化残基识别网站的影响.pdfVIP

Networks of High Mutual Information Define the Structural Proximity of Catalytic Sites: Implications for Catalytic Residue Identification 1. 1. ´ 2 ´ ´ 2 3 Cristina Marino Buslje *, Elin Teppa , Tomas Di Domenico , Jose Marıa Delfino , Morten Nielsen ´ 1 Fundacion Instituto Leloir, Buenos Aires, Argentina, 2 Institute of Biochemistry and Biophysics (IQUIFIB), School of Pharmacy and Biochemistry, University of Buenos Aires, Buenos Aires, Argentina, 3 Center for Biological Sequence Analysis, Department of Systems Biology, The Technical University of Denmark, Lyngby, Denmark Abstract Identification of catalytic residues (CR) is essential for the characterization of enzyme function. CR are, in general, conserved and located in the functional site of a protein in order to attain their function. However, many non-catalytic residues are highly conserved and not all CR are conserved throughout a given protein family making identification of CR a challenging task. Here, we put forward the hypothesis that CR carry a particular signature defined by networks of close proximity residues with high mutual information (MI), and that this signature can be applied to distinguish functional from other non- functional conserved residues. Using a data set of 434 Pfam families included in the catalytic site atlas (CSA) database, we tested this hypothesis and demonstrated that MI can complement amino acid conservation scores to detect CR. The Kullback-Leibler (KL) conservation measurement was shown to significantly outperform both the Shannon entropy and maximal frequency measurements. Residues in the proximity of catalytic sites were shown to be rich in shared MI