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Cited by 934

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A Method for the Quantitative Modification and Estimation of Carboxylic Acid Groups in Proteins

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Hoare, D.G., Koshland, D.E.·1967·Journal of Biological Chemistry

Abstract

A method for the rapid modification under mild conditions of carboxyl groups in proteins has been developed. The method involves the activation of the carboxyl group by a water-soluble carbodiimide and the subsequent reaction of the activated carboxyl group with a nucleophile such as glycine methyl ester. The kinetics of the reaction indicates that there are limits to the variation of carbodiimide and nucleophile when quantitative modification is desired, but that a wide variety of reagents can be used if quantitative reaction is not essential. Thus, variation in the structure of the carbodiimide can affect the carboxyl groups activated, and variation in the charge, size, and chemical and spectral properties of the nucleophile can alter the type of modification at a specific carboxyl group. The reaction proceeds equally well in high concentrations of urea or guanidine hydrochloride. The method appears to be of wide utility for analytical purposes and structure-function correlations.

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Metadata

Authors
Hoare, D. G., & Koshland, D. E.
Venue
Journal of Biological Chemistry
Publisher
Elsevier BV
Published
1967-05
Volume
242
Issue
10
Pages
2447-2453
ISSN
0021-9258 (ISSN-L)
OpenAlex
W1576127641
Cited by
934
References
1
FWCI
8.97
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: A Method for the Quantitative Modification and Estimation of Carboxylic Acid Groups in Proteins. https://app.cochat.ai/papers/10.1016/s0021-9258(18)95981-8
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Hoare, D. G., & Koshland, D. E. (1967). A Method for the Quantitative Modification and Estimation of Carboxylic Acid Groups in Proteins. Journal of Biological Chemistry. https://doi.org/10.1016/s0021-9258(18)95981-8

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.