In silico Designing of Protein Rich in Large Neutral Amino Acids Using Bovine αs1 Casein for Treatment of PhenylketonuriaPrakruthi Appaiah and Prasanna Vasu*
Department of Food Safety and Analytical Quality Control Laboratory, CSIR-Central Food Technological Research Institute, Mysuru-570020, Karnataka, India
- Corresponding Author:
- Prasanna Vasu
Department of Food Safety and Analytical Quality Control Laboratory,
CSIR-Central Food Technological Research Institute,
E-mail: [email protected]
Received Date: October 06, 2016; Accepted Date: November 11, 2016; Published Date: November 16, 2016
Citation: Appaiah P, Vasu P (2016) In silico Designing of Protein Rich in Large Neutral Amino Acids Using Bovine αs1 Casein for Treatment of Phenylketonuria. J Proteomics Bioinform 9:287-297. doi: 10.4172/jpb.1000417
Copyright: © 2016 Appaiah P, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Phenylketonuria (PKU) is a genetically inherited disease where the body fails to convert Phenylalanine (Phe) to Tyrosine (Tyr) due to the defective Phenylalanine Hydroxylase (PAH) enzyme, resulting in the elevated blood Phe level causing neurological damage. Of all therapies, Large Neutral Amino Acid (LNAA) supplementation has become a promising approach to the dietary treatment of PKU, where the LNAA compete with Phe for the same L-Type Large Neutral Amino Acid Transporter (LAT1, SLC7A5) across the blood-brain barrier, decreasing brain Phe level. In this study we have designed an easily digestible protein enriched with LNAA (except Phe), using bovine αs1 casein as template by homology modeling. Our challenge was to maximize the LNAAs (except Phe) in the protein model by finding a suitable scaffold for hosting LNAAs, thereby turning the usual concept of homology modeling. Bioinformatics tools like SWISS-MODEL, EXPASY, PROFUNC, I-TASSER, RaptorX, and SAVeS Server were used for the structure prediction, and validation of the designed protein. Out of 63 different models designed, Protein Model-54 was selected based on sequence similarity to template (61.4%), compact 3D structure containing only α-helices and coils without β-sheets (QMEAN score of 0.567), and good in silico digestibility. The molecular weight of protein was 12,094.6 Da. Ramachandran plot revealed that the designed protein contained 89.9% amino acid residues in the favored region with ERRAT score of 88.04. Based on these evaluations, the Protein Model-54 was found to be the best, stable and reliable model which may be of high nutritional significance for PKU patients..