2012Journal of Enzyme Inhibition and Medicinal ChemistryOpen access

Classification of difference between inhibition constants of an inhibitor to facilitate identifying the inhibition type

Xiaolan Yang, Zhiyin Du, Jun Pu, Hua Zhao, Hong Chen, Yin Liu, Zhirong Li, Zhenli Cheng, Huansi Zhong, Fei Liao

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Abstract

To identify the common inhibition types, the putative decision system is unsatisfactory. In a new decision system, Michaelis-Menten constants and maximal reaction rates were plotted versus inhibitor concentrations for deriving K(ik) and K(iv) as the inhibition constants, respectively; their difference was quantified as the ratio of the larger one to the smaller one. Such ratios below 2.0 suggested uncompetitive inhibitors, over 5.0 suggested noncompetitive or competitive inhibitors, and from 2.0 to 5.0 suggested mixed inhibitors. By the new decision system, (i) the simulation recovery of uncompetitive inhibitors under CVs of 2% or 5% was improved by four times, but that of competitive or noncompetitive inhibitors was improved slightly; (ii) the recovery of L-phenylalanine as an uncompetitive inhibitor of intestinal alkaline phosphatase reached 38%, while the putative decision system lost all; the recovery of xanthine as a competitive inhibitor of uricase was improved slightly. Therefore, the new decision system was better.

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To identify the common inhibition types, the putative decision system is unsatisfactory. In a new decision system, Michaelis-Menten constants and maximal reaction rates were plotted versus inhibitor concentrations for deriving K(ik) and K(iv) as the inhibition constants, respectively; their difference was quantified as the ratio of the larger one to the smaller one. Such ratios below 2.0 suggested uncompetitive inhibitors, over 5.0 suggested noncompetitive or competitive inhibitors, and from 2.0 to 5.0 suggested mixed inhibitors. By the new decision system, (i) the simulation recovery of uncompetitive inhibitors under CVs of 2% or 5% was improved by four times, but that of competitive or noncompetitive inhibitors was improved slightly; (ii) the recovery of L-phenylalanine as an uncompetitive inhibitor of intestinal alkaline phosphatase reached 38%, while the putative decision system lost all; the recovery of xanthine as a competitive inhibitor of uricase was improved slightly. Therefore, the new decision system was better.

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Available abstract

To identify the common inhibition types, the putative decision system is unsatisfactory. In a new decision system, Michaelis-Menten constants and maximal reaction rates were plotted versus inhibitor concentrations for deriving K(ik) and K(iv) as the inhibition constants, respectively; their difference was quantified as the ratio of the larger one to the smaller one. Such ratios below 2.0 suggested uncompetitive inhibitors, over 5.0 suggested noncompetitive or competitive inhibitors, and from 2.0 to 5.0 suggested mixed inhibitors. By the new decision system, (i) the simulation recovery of uncompetitive inhibitors under CVs of 2% or 5% was improved by four times, but that of competitive or noncompetitive inhibitors was improved slightly; (ii) the recovery of L-phenylalanine as an uncompetitive inhibitor of intestinal alkaline phosphatase reached 38%, while the putative decision system lost all; the recovery of xanthine as a competitive inhibitor of uricase was improved slightly. Therefore, the new decision system was better.

Key concepts: Uncompetitive inhibitor, Non-competitive inhibition, Chemistry, Michaelis–Menten kinetics, Stereochemistry, Biochemistry, Enzyme, Enzyme assay

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