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. 2010 Apr 15;399(2):268-75.
doi: 10.1016/j.ab.2009.12.018. Epub 2009 Dec 14.

Use of thermal melt curves to assess the quality of enzyme preparations

Affiliations

Use of thermal melt curves to assess the quality of enzyme preparations

Gregory J Crowther et al. Anal Biochem. .

Abstract

This study sought to determine whether the quality of enzyme preparations can be determined from their melting curves, which may easily be obtained using a fluorescent probe and a standard reverse transcription-polymerase chain reaction (RT-PCR) machine. Thermal melt data on 31 recombinant enzymes from Plasmodium parasites were acquired by incrementally heating them to 90 degrees C and measuring unfolding with a fluorescent dye. Activity assays specific to each enzyme were also performed. Four of the enzymes were denatured to varying degrees with heat and sodium dodecyl sulfate (SDS) prior to the thermal melt and activity assays. In general, melting curve quality was correlated with enzyme activity; enzymes with high-quality curves were found almost uniformly to be active, whereas those with lower quality curves were more varied in their catalytic performance. Inspection of melting curves of bovine xanthine oxidase and Entamoeba histolytica cysteine protease 1 allowed active stocks to be distinguished from inactive stocks, implying that a relationship between melting curve quality and activity persists over a wide range of experimental conditions and species. Our data suggest that melting curves can help to distinguish properly folded proteins from denatured ones and, therefore, may be useful in selecting stocks for further study and in optimizing purification procedures for specific proteins.

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Figures

FIGURE 1
FIGURE 1
Melting curve quality is similar in standard and enzyme-specific buffers. Q’s were calculated as described in Materials and Methods; each score is an average of at least five to eight replicate wells. Each data point represents a separate Plasmodium enzyme; many enzymes are represented by the point at (1,1). The best-fit line is: y = 0.97x + 0.01 (R2 = 0.94).
FIGURE 2
FIGURE 2
Plasmodium enzymes with high Q’s (>0.60) are almost always active, whereas those with lower Q’s (<0.50) are more variable.
FIGURE 3
FIGURE 3
Melting curves for glyceraldehyde-3-phosphate dehydrogenase in activity assay buffer in response to (A) preheating and (B) SDS. Data shown are typical results from single wells.
FIGURE 4
FIGURE 4
Q’s and activities for (A) adenosine deaminase, (B) glyceraldehyde-3-phosphate dehydrogenase, (C) methionine aminopeptidase 1, and (D) orotidine 5′-monophosphate decarboxylase denatured by heat (solid diamonds) and SDS (open squares). Error bars represent standard deviations.
FIGURE 5
FIGURE 5
Thermal melt curves of catalytically active and inactive stocks of (A) xanthine oxidase from Bos taurus and (B) cysteine protease 1 from Enamoeba histolytica. Data shown are typical results from single wells.

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