Abstract

BackgroundEnzyme assays have widespread applications in drug discovery from plants to natural products. The appropriate use of blanks in enzyme assays is important for assay baseline-correction, and the correction of false signals associated with background matrix interferences. However, the blank-correction procedures reported in published literature are highly inconsistent. We investigated the influence of using different types of blanks on the final calculated activity/inhibition results for three enzymes of significance in diabetes and obesity; α-glucosidase, α-amylase, and lipase. This is the first study to examine how different blank-correcting methods affect enzyme assay results. Although assays targeting the above enzymes are common in the literature, there is a scarcity of detailed published protocols. Therefore, we have provided comprehensive, step-by-step protocols for α-glucosidase-, α-amylase- and lipase-inhibition assays that can be performed in 96-well format in a simple, fast, and resource-efficient manner with clear instructions for blank-correction and calculation of results.ResultsIn the three assays analysed here, using only a buffer blank underestimated the enzyme inhibitory potential of the test sample. In the absorbance-based α-glucosidase assay, enzyme inhibition was underestimated when a sample blank was omitted for the coloured plant extracts. Similarly, in the fluorescence-based α-amylase and lipase assays, enzyme inhibition was underestimated when a substrate blank was omitted. For all three assays, method six [Raw Data - (Substrate + Sample Blank)] enabled the correction of interferences due to the buffer, sample, and substrate without double-blanking, and eliminated the need to add substrate to each sample blank.ConclusionThe choice of blanks and blank-correction methods contribute to the variability of assay results and the likelihood of underestimating the enzyme inhibitory potential of a test sample. This highlights the importance of standardising the use of blanks and the reporting of blank-correction procedures in published studies in order to ensure the accuracy and reproducibility of results, and avoid overlooked opportunities in drug discovery research due to inadvertent underestimation of enzyme inhibitory potential of test samples resulting from unsuitable blank-correction. Based on our assessments, we recommend method six [RD − (Su + SaB)] as a suitable method for blank-correction of raw data in enzyme assays.

Highlights

  • Enzyme assays have widespread applications in drug discovery from plants to natural products

  • Enzyme inhibition assays targeting α-glucosidase, α-amylase and lipase are widespread in research, and screening plant extracts and natural products for inhibitory activity against these enzymes is a common approach for the discovery of potential antidiabetic and antiobesity drugs to treat and manages these metabolic diseases [18,19,20]

  • The aims of this study were to (1) provide comprehensive protocols for carrying out a colorimetric α-glucosidase inhibition assay, and fluorometric α-amylase and lipase inhibition assays in 96-well microplates; and (2) investigate whether using a buffer blank, substrate blank, sample blank, or a combination of blanks for blank-correction will affect the final, calculated enzyme inhibition results

Read more

Summary

Introduction

Enzyme assays have widespread applications in drug discovery from plants to natural products. We investigated the influence of using different types of blanks on the final calculated activity/inhibition results for three enzymes of significance in diabetes and obesity; α-glucosidase, α-amylase, and lipase. This is the first study to examine how different blank-correcting methods affect enzyme assay results. Enzyme inhibition assays targeting α-glucosidase, α-amylase and lipase are widespread in research, and screening plant extracts and natural products for inhibitory activity against these enzymes is a common approach for the discovery of potential antidiabetic and antiobesity drugs to treat and manages these metabolic diseases [18,19,20]

Objectives
Methods
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.