Booth, J, Alexandru-Crivac, CN, Rickaby, KA et al. (7 more authors) (2017) A Blind Test of Computational Technique for Predicting the Likelihood of Peptide Sequences to Cyclize. Journal of Physical Chemistry Letters, 8 (10). pp. 2310-2315. ISSN 1948-7185
Abstract
An in silico computational technique for predicting peptide sequences that can be cyclized by cyanobactin macrocyclases, e.g., PatGmac, is reported. We demonstrate that the propensity for PatGmac-mediated cyclization correlates strongly with the free energy of the so-called pre-cyclization conformation (PCC), which is a fold where the cyclizing sequence C and N termini are in close proximity. This conclusion is driven by comparison of the predictions of boxed molecular dynamics (BXD) with experimental data, which have achieved an accuracy of 84%. A true blind test rather than training of the model is reported here as the in silico tool was developed before any experimental data was given, and no parameters of computations were adjusted to fit the data. The success of the blind test provides fundamental understanding of the molecular mechanism of cyclization by cyanobactin macrocyclases, suggesting that formation of PCC is the rate-determining step. PCC formation might also play a part in other processes of cyclic peptides production and on the practical side the suggested tool might become useful for finding cyclizable peptide sequences in general.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This is an open access article published under a Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemistry (Leeds) > Physical Chemistry (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 09 May 2017 09:44 |
Last Modified: | 23 Jun 2023 22:28 |
Status: | Published |
Publisher: | American Chemical Society |
Identification Number: | 10.1021/acs.jpclett.7b00848 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:116087 |