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An Artificial Design Technique to Optimize Signal Peptide

Gao Cui-Fang1, Wang Sen1, Tian Feng-Wei1, Zhu Ping1 and Chen Wei 1
  • 1 Jiangnan University, China

Abstract

To determine optimal artificial signal peptide candidates for the possibility of creating high levels of secretion of heterologous proteins, substitution and redesign of amino acid sequences in the H-domain of the signal peptide was theoretically attempted. The method was based on comprehensive score matrix and Markov transfer matrix, which can make the artificial sequences maintain the structural characteristics and original polarity of signal peptides. For the artificial sequence, the feature vector of Structural Fusion Degree (SFD) is first extracted to quantitatively describe the compatibility of artificial cleaved region, then by comparing with highly secreted natural samples; tendencies of specific substitutions in the amino acid sequence can be identified at certain locations. These substitutions may represent the key amino acids that influence the secretion and expression levels of heterologous proteins. 

American Journal of Biochemistry and Biotechnology
Volume 13 No. 3, 2017, 114-122

DOI: https://doi.org/10.3844/ajbbsp.2017.114.122

Submitted On: 8 June 2017 Published On: 21 July 2017

How to Cite: Cui-Fang, G., Sen, W., Feng-Wei, T., Ping, Z. & Wei , C. (2017). An Artificial Design Technique to Optimize Signal Peptide. American Journal of Biochemistry and Biotechnology, 13(3), 114-122. https://doi.org/10.3844/ajbbsp.2017.114.122

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Keywords

  • Markov Transition Matrix
  • Signal Peptide
  • Feature Vector
  • Artificial Sequence