dc.contributor.author	Yallapragada, V. V. B.
dc.contributor.author	Walker, Sidney P.
dc.contributor.author	Devoy, Ciaran
dc.contributor.author	Buckley, Stephen
dc.contributor.author	Flores, Yensi
dc.contributor.author	Tangney, Mark
dc.contributor.funder	Science Foundation Ireland	en
dc.contributor.funder	Health Research Board	en
dc.contributor.funder	Breakthrough Cancer Research, Ireland	en
dc.date.accessioned	2019-10-17T09:08:58Z
dc.date.available	2019-10-17T09:08:58Z
dc.date.issued	2019-10-07
dc.date.updated	2019-10-17T08:50:34Z
dc.description.abstract	Protein engineering and synthetic biology stand to benefit immensely from recent advances in in silico tools for structural and functional analyses of proteins. In the context of designing novel proteins, current in silico tools inform the user on individual parameters of a query protein, with output scores/metrics unique to each parameter. In reality, proteins feature multiple â partsâ /functions, and modification of a protein aimed at altering a given part, typically has collateral impact on other protein parts. A system for prediction of the combined effect of design parameters on the overall performance of the final protein does not exist. Function2Form Bridge (F2F-Bridge), attempts to address this by combining the scores of different design parameters pertaining to the protein being analysed into a single easily interpreted output describing overall performance. The strategy comprises 1. A mathematical strategy combining data from a myriad of in silico tools into an OP-score (a singular score informing on a user-defined overall performance); 2. The F2F-Plot, a graphical means of informing the wetlab biologist holistically on designed construct suitability in the context of multiple parameters, highlighting scope for improvement. F2F predictive output was compared with wetlab data from a range of synthetic proteins designed, built and tested for this study. Statistical/machine learning approaches for predicting overall performance, for use alongside the F2F plot, were also examined. Comparisons between wetlab performance and F2F predictions demonstrated close and reliable correlations. This user-friendly strategy represents a pivotal enabler in increasing accessibility of synthetic protein building and de novo protein design.	en
dc.description.sponsorship	Health Research Board (MRCG2016-25)	en
dc.description.status	Peer reviewed	en
dc.description.version	Accepted Version	en
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Yallapragada, V. V. B., Walker, S. P., Devoy, C., Buckley, S., Flores, Y. and Tangney, M. (2019) 'Function2Form Bridge - Towards synthetic protein holistic performance-prediction', Proteins. doi: 10.1002/prot.25825	en
dc.identifier.doi	10.1002/prot.25825	en
dc.identifier.eissn	1097-0134
dc.identifier.issn	0887-3585
dc.identifier.journaltitle	Proteins	en
dc.identifier.uri	https://hdl.handle.net/10468/8789
dc.language.iso	en	en
dc.publisher	John Wiley & Sons, Inc.	en
dc.relation.project	info:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2273/IE/Alimentary Pharmabiotic Centre (APC) - Interfacing Food & Medicine/	en
dc.relation.project	info:eu-repo/grantAgreement/SFI/SFI Career Development Award/15/CDA/3630/IE/Edible Probiotics As Cancer Theranostics/	en
dc.relation.uri	https://onlinelibrary.wiley.com/doi/abs/10.1002/prot.25825
dc.rights	© 2019, Wiley Periodicals, Inc. All rights reserved. This is the peer reviewed version of the following article: Yallapragada, V. V. B., Walker, S. P., Devoy, C., Buckley, S., Flores, Y. and Tangney, M. (2019) 'Function2Form Bridge - Towards synthetic protein holistic performance-prediction', Proteins, doi: 10.1002/prot.25825, which has been published in final form at https://doi.org/10.1002/prot.25825. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.	en
dc.subject	Synthetic biology	en
dc.subject	High throughput in silico screening	en
dc.subject	In silico modelling	en
dc.subject	Antibody screening	en
dc.subject	Protein scoring	en
dc.subject	Community‐based data reporting Machine learning	en
dc.subject	De novo protein design	en
dc.title	Function2Form Bridge - Towards synthetic protein holistic performance-prediction	en
dc.type	Article (peer-reviewed)	en

Function2Form Bridge - Towards synthetic protein holistic performance-prediction

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