In Silico Characterization of Heavy Metal Binding Protein Predicted In the Genome Sequence of Lactobacillus pentosus KCA1
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Abstract
Heavy metals, such as lead, cadmium, arsenic and mercury can contaminate the food chain and pose serious health problems.
We characterized the heavy metal binding protein predicted in the genome sequence of Lactobacillus pentosus KCA1.
Bioinformatic tools such as BLASTp, ClustalW and iterative threading assembly refinement (I-TASSER) server were used for
protein sequence similarity, secondary structure and 3-D model prediction for potential active binding sites. Two cysteine
residues were identified at position 12 and 15 (Cys12 and Cys15), separated by proline (P) and serine (S). The secondary
structure prediction revealed 2 alpha helices and 5 beta-strands. The 3-D model structure of KCA1_2798 has a confidence scoreof 1.26 that reflects a model of good quality with binding site residues predicted to occur at five positions (Thr11, Cys12, Ser14, Cys15, Gly63) of the KCA1_2798 sequence based on a protein (3iwlA) template. The heavy metal binding protein encoded in the genome sequence of L. pentosus KCA1 has laid a foundation for further investigation into its potential health applications.
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