适体
计算生物学
蛋白质组
多路复用
人类蛋白质组计划
指数富集配体系统进化
表位
计算机科学
化学
生物
蛋白质组学
生物信息学
生物化学
分子生物学
核糖核酸
抗体
遗传学
电信
基因
作者
S. Kraemer,Daniel J. Schneider,Clare Paterson,Darryl Perry,Matthew J. Westacott,Yolanda Hagar,Evaldas Katilius,Sean Lynch,Theresa M. Russell,Theodore Johnson,David P. Astling,Robert Kirk DeLisle,J. P. Cleveland,Larry Gold,Daniel W. Drolet,Nebojša Janjić
标识
DOI:10.1021/acs.jproteome.4c00411
摘要
Measuring responses in the proteome to various perturbations improves our understanding of biological systems. The value of information gained from such studies is directly proportional to the number of proteins measured. To overcome technical challenges associated with highly multiplexed measurements, we developed an affinity reagent-based method that uses aptamers with protein-like side chains along with an assay that takes advantage of their unique properties. As hybrid affinity reagents, modified aptamers are fully comparable to antibodies in terms of binding characteristics toward proteins, including epitope size, shape complementarity, affinity and specificity. Our assay combines these intrinsic binding properties with serial kinetic proofreading steps to allow highly effective partitioning of stable specific complexes from unstable nonspecific complexes. The use of these orthogonal methods to enhance specificity effectively overcomes the severe limitation to multiplexing inherent to the use of sandwich-based methods. Our assay currently measures half of the unique proteins encoded in the human genome with femtomolar sensitivity, broad dynamic range and exceptionally high reproducibility. Using machine learning to identify patterns of change, we have developed tests based on measurement of multiple proteins predictive of current health states and future disease risk to guide a holistic approach to precision medicine.
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