RT Journal Article
SR Electronic
T1 A Method for Computationally Constructing Eukaryotic Synthetic Signal Peptide Sequences
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2021.11.19.469281
DO 10.1101/2021.11.19.469281
A1 Grant T. Daly
A1 Aishwarya Prakash
A1 Ryan G. Benton
A1 Tom Johnsten
YR 2021
UL http://biorxiv.org/content/early/2021/11/20/2021.11.19.469281.abstract
AB We developed a computational method for constructing synthetic signal peptides from a base set of signal peptides (SPs) and non-SP sequences. A large number of structured “building blocks”, represented as m-step ordered pairs of amino acids, are extracted from the base. Using a straightforward procedure, the building blocks enable the construction of a diverse set of synthetic SPs that could be utilized for industrial and therapeutic purposes. We have validated the proposed methodology using existing sequence prediction platforms such as Signal-BLAST and MULocDeep. In one experiment, 9,555 protein sequences were generated from a large randomly selected set of “building blocks”. Signal-BLAST identified 8,444 (88%) of the sequences as signal peptides. In addition, the Signal-BLAST tool predicted that the generated synthetic sequences belonged to 854 distinct eukaryotic organisms. Here, we provide detailed descriptions and results from various experiments illustrating the potential usefulness of the methodology in generating signal peptide protein sequences.Competing Interest StatementThe authors have declared no competing interest.