Strategies for enriching and characterizing proteins with inhibitory properties on the yeast surface

Author:

Rezhdo Arlinda,Lessard Catherine T.,Islam Mariha,Van Deventer James A.ORCID

Abstract

AbstractDisplay technologies are powerful tools for discovering antibodies and other binding proteins against a broad range of biological targets. However, it remains challenging to adapt display technologies for the discovery of proteins that inhibit the enzymatic activities of such targets because the phenotypic readout during display screens is binding. The goal of this work is to investigate approaches for discovering inhibitory antibodies in yeast display format using a well-defined series of constructs and the target matrix metalloproteinase-9 (MMP-9). Three previously reported antibodies (DX-2802, M0076 and FAPB2.3.6) were used to create model libraries that are representative of protein libraries consisting of inhibitory binders, non-inhibitory binders, and non-binding constructs. Conditions that preferentially enrich for inhibitory clones were identified for both magnetic bead-based enrichments and fluorescence-activated cell sorting (FACS). Finally, we used direct titration of yeast to estimate inhibitor IC50 values with yeast-displayed and soluble constructs and found that the IC50 obtained for DX-2802 in yeast display format (20.01 ± 9.01 nM) falls within the confidence interval of IC50 the soluble scFv-Fc form of DX-2802 (17.56 ± 6.16 nM). Thus, it is possible to obtain IC50 values on the yeast surface, which greatly streamlines initial characterizations of inhibitory properties. Overall, we used these well-defined constructs to identify strategies for the discovery and characterization of inhibitory clones directly in surface display format.

Publisher

Cold Spring Harbor Laboratory

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3