Database-Centric Method for Automated High-Throughput Deconvolution and Analysis of Kinetic Antibody Screening Data.
SLAS Technol
; 22(5): 547-556, 2017 10.
Article
em En
| MEDLINE
| ID: mdl-28430560
ABSTRACT
The state-of-the-art industrial drug discovery approach is the empirical interrogation of a library of drug candidates against a target molecule. The advantage of high-throughput kinetic measurements over equilibrium assessments is the ability to measure each of the kinetic components of binding affinity. Although high-throughput capabilities have improved with advances in instrument hardware, three bottlenecks in data processing remain (1) intrinsic molecular properties that lead to poor biophysical quality in vitro are not accounted for in commercially available analysis models, (2) processing data through a user interface is time-consuming and not amenable to parallelized data collection, and (3) a commercial solution that includes historical kinetic data in the analysis of kinetic competition data does not exist. Herein, we describe a generally applicable method for the automated analysis, storage, and retrieval of kinetic binding data. This analysis can deconvolve poor quality data on-the-fly and store and organize historical data in a queryable format for use in future analyses. Such database-centric strategies afford greater insight into the molecular mechanisms of kinetic competition, allowing for the rapid identification of allosteric effectors and the presentation of kinetic competition data in absolute terms of percent bound to antigen on the biosensor.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Processamento Eletrônico de Dados
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Automação Laboratorial
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Ensaios de Triagem em Larga Escala
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Anticorpos
Tipo de estudo:
Diagnostic_studies
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Prognostic_studies
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Screening_studies
Limite:
Animals
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Humans
Idioma:
En
Revista:
SLAS Technol
Ano de publicação:
2017
Tipo de documento:
Article
País de afiliação:
Estados Unidos