UZH-Logo

Maintenance Infos

Computational analysis of off-rate selection experiments to optimize affinity maturation by directed evolution


Zahnd, C; Sarkar, C A; Plückthun, A (2010). Computational analysis of off-rate selection experiments to optimize affinity maturation by directed evolution. Protein Engineering Design and Selection : PEDS, 23(4):175-184.

Abstract

Directed evolution is a powerful approach for isolating high-affinity binders from complex libraries. In affinity maturation experiments, binders with the highest affinities in the library are typically isolated through selections for decreased off rate using a suitable selection platform (e.g. phage display or ribosome display). In such experiments, the library is initially exposed to biotinylated antigen and the binding reaction is allowed to proceed. A large excess of unbiotinylated antigen is then added as a competitor to capture the vast majority of rapidly dissociating molecules; the slowly dissociating library members can subsequently be rescued by capturing the biotin-carrying complexes. To optimize the parameters for such affinity maturation experiments, we performed both deterministic and stochastic simulations of off-rate selection experiments using different input libraries. Our results suggest that the most critical parameters for achieving the lowest off rates after selection are the ratio of competitor antigen to selectable antigen and the selection time. Furthermore, the selection time has an optimum that depends on the experimental setup and the nature of the library. Notably, if selections are carried out for times much longer than the optimum, equilibrium is reached and the selection pressure is weakened or lost. Comparison of different selection strategies revealed that sequential selection rounds with lower stringency are favored over high-stringency selection experiments due to enhanced diversity in the selected pools. Such simulations may be helpful in optimizing affinity maturation strategies and off-rate selection experiments.

Directed evolution is a powerful approach for isolating high-affinity binders from complex libraries. In affinity maturation experiments, binders with the highest affinities in the library are typically isolated through selections for decreased off rate using a suitable selection platform (e.g. phage display or ribosome display). In such experiments, the library is initially exposed to biotinylated antigen and the binding reaction is allowed to proceed. A large excess of unbiotinylated antigen is then added as a competitor to capture the vast majority of rapidly dissociating molecules; the slowly dissociating library members can subsequently be rescued by capturing the biotin-carrying complexes. To optimize the parameters for such affinity maturation experiments, we performed both deterministic and stochastic simulations of off-rate selection experiments using different input libraries. Our results suggest that the most critical parameters for achieving the lowest off rates after selection are the ratio of competitor antigen to selectable antigen and the selection time. Furthermore, the selection time has an optimum that depends on the experimental setup and the nature of the library. Notably, if selections are carried out for times much longer than the optimum, equilibrium is reached and the selection pressure is weakened or lost. Comparison of different selection strategies revealed that sequential selection rounds with lower stringency are favored over high-stringency selection experiments due to enhanced diversity in the selected pools. Such simulations may be helpful in optimizing affinity maturation strategies and off-rate selection experiments.

Citations

25 citations in Web of Science®
26 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

2 downloads since deposited on 18 Jan 2011
0 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Department of Biochemistry
07 Faculty of Science > Department of Biochemistry
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2010
Deposited On:18 Jan 2011 12:49
Last Modified:05 Apr 2016 14:27
Publisher:Oxford University Press
ISSN:1741-0126
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/protein/gzp087
PubMed ID:20130104
Permanent URL: https://doi.org/10.5167/uzh-39966

Download

[img]
Filetype: PDF - Registered users only
Size: 2MB
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations