MULISA : A New Strategy for Discovery of Protein Functional Motifs and Residues

To predict and identify details regarding function from protein sequences is an emergency task since the growing number and diversity of protein sequence. Here, we develop a novel approach for identifying conservation residues and motifs of ligand-binding proteins. In this method, called MuLiSA (Multiple Ligand-bound Structure Alignment), we first superimpose the ligands of ligand-binding proteins and then the residues of ligand-binding sites are naturally aligned. We identify important residues and patterns based on the z-scores of the residue entropy and residue-segment entropy. After identifying new pattern candidates, the profiles of patterns are generated to predict the protein function from only protein sequences. We tested our approach on ATP-binding proteins and HEM-binding proteins. The experiments show that MuLiSA can identify the conservation residues and novel patterns which are really correlated with protein functions of certain ligand-binding proteins. We found that our MuLiSA can identify conservation patterns and is better than traditional alignments such as CE and CLUSTALW in some ligand-binding proteins. We believe that our MuLiSA is useful to discover ligand-binding specificity-determining residues and functional important patterns of proteins.