Molecular evolution of peptide ligands with custom-tailored characteristics for targeting of glycostructures.
As an advanced approach to identify suitable targeting molecules required for various diagnostic and therapeutic interventions, we developed a procedure to devise peptides with customizable features by an iterative computer-assisted optimization strategy. An evolutionary algorithm was utilized to br...
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2012-01-01
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Series: | PLoS Computational Biology |
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doaj-439e615a903a4fffb85a5f250958f7cc2020-11-25T02:11:59ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582012-01-01812e100280010.1371/journal.pcbi.1002800Molecular evolution of peptide ligands with custom-tailored characteristics for targeting of glycostructures.Niels RöckendorfMarkus BorschbachAndreas FreyAs an advanced approach to identify suitable targeting molecules required for various diagnostic and therapeutic interventions, we developed a procedure to devise peptides with customizable features by an iterative computer-assisted optimization strategy. An evolutionary algorithm was utilized to breed peptides in silico and the "fitness" of peptides was determined in an appropriate laboratory in vitro assay. The influence of different evolutional parameters and mechanisms such as mutation rate, crossover probability, gaussian variation and fitness value scaling on the course of this artificial evolutional process was investigated. As a proof of concept peptidic ligands for a model target molecule, the cell surface glycolipid ganglioside G(M1), were identified. Consensus sequences describing local fitness optima were reached from diverse sets of L- and proteolytically stable D lead peptides. Ten rounds of evolutional optimization encompassing a total of just 4400 peptides lead to an increase in affinity of the peptides towards fluorescently labeled ganglioside G(M1) by a factor of 100 for L- and 400 for D-peptides.http://europepmc.org/articles/PMC3521706?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Niels Röckendorf Markus Borschbach Andreas Frey |
spellingShingle |
Niels Röckendorf Markus Borschbach Andreas Frey Molecular evolution of peptide ligands with custom-tailored characteristics for targeting of glycostructures. PLoS Computational Biology |
author_facet |
Niels Röckendorf Markus Borschbach Andreas Frey |
author_sort |
Niels Röckendorf |
title |
Molecular evolution of peptide ligands with custom-tailored characteristics for targeting of glycostructures. |
title_short |
Molecular evolution of peptide ligands with custom-tailored characteristics for targeting of glycostructures. |
title_full |
Molecular evolution of peptide ligands with custom-tailored characteristics for targeting of glycostructures. |
title_fullStr |
Molecular evolution of peptide ligands with custom-tailored characteristics for targeting of glycostructures. |
title_full_unstemmed |
Molecular evolution of peptide ligands with custom-tailored characteristics for targeting of glycostructures. |
title_sort |
molecular evolution of peptide ligands with custom-tailored characteristics for targeting of glycostructures. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS Computational Biology |
issn |
1553-734X 1553-7358 |
publishDate |
2012-01-01 |
description |
As an advanced approach to identify suitable targeting molecules required for various diagnostic and therapeutic interventions, we developed a procedure to devise peptides with customizable features by an iterative computer-assisted optimization strategy. An evolutionary algorithm was utilized to breed peptides in silico and the "fitness" of peptides was determined in an appropriate laboratory in vitro assay. The influence of different evolutional parameters and mechanisms such as mutation rate, crossover probability, gaussian variation and fitness value scaling on the course of this artificial evolutional process was investigated. As a proof of concept peptidic ligands for a model target molecule, the cell surface glycolipid ganglioside G(M1), were identified. Consensus sequences describing local fitness optima were reached from diverse sets of L- and proteolytically stable D lead peptides. Ten rounds of evolutional optimization encompassing a total of just 4400 peptides lead to an increase in affinity of the peptides towards fluorescently labeled ganglioside G(M1) by a factor of 100 for L- and 400 for D-peptides. |
url |
http://europepmc.org/articles/PMC3521706?pdf=render |
work_keys_str_mv |
AT nielsrockendorf molecularevolutionofpeptideligandswithcustomtailoredcharacteristicsfortargetingofglycostructures AT markusborschbach molecularevolutionofpeptideligandswithcustomtailoredcharacteristicsfortargetingofglycostructures AT andreasfrey molecularevolutionofpeptideligandswithcustomtailoredcharacteristicsfortargetingofglycostructures |
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1724911421246930944 |