Assessment of α‑Amylase Activity in a Microanalysis System: Experimental Optimization and Evaluation of Type of Inhibition

• Published in: Journal of chemical education Vol. 100; no. 3; pp. 1237 - 1245
• Main Authors: Freitas, Marisa, Proença, Carina, Ribeiro, Daniela, Quinaz-Garcia, Maria Beatriz, Araújo, Alberto N., Fernandes, Eduarda
• Format: Journal Article
• Language: English
• Published: Easton American Chemical Society and Division of Chemical Education, Inc 14.03.2023; American Chemical Society
• Subjects: Amylases; Drugs; Educational Environment; Enzymes; Evaluation; Inhibition; Kinetics; Learning environment; Linear transformations; Mathematical models; Optimization; Pancreas; Parameters; Physiology; Students; Substrates; Textbooks; Transformations (Mathematics); Medicinal Chemistry; Enzymes; Upper-Division Undergraduate; Discovery Learning; Manipulatives; Laboratory Instructions; Biochemistry; Kinetics; Hands-On Learning
• ISSN: 0021-9584; 1938-1328
• DOI: 10.1021/acs.jchemed.2c00392

Enzymes, enzymatic kinetics, and enzyme inhibition are topics covered in undergraduate biochemistry textbooks, having perceptible relevance to everyday life. The experimental use of enzymes involved in basic physiologic processes may be of utmost pedagogic interest because they bring evidence on how a significant number of drugs are used to control illnesses. Salivary and pancreatic α-amylases are essential digestive enzymes responsible for the partial hydrolysis of starch, the primary source of calories in human diet. As the structures of α-amylase from human pancreas and porcine pancreas are highly similar, the latter is an enzyme that can be easily used in laboratory classes at an accessible price. The activity of this enzyme can also be easily and affordably evaluated by resorting to the substrate 2-chloro-4-nitrophenyl-α-d-maltotrioside (CNPG3). Here, we propose an active-learning environment activity where students use a physiologically relevant enzyme (α-amylase) to develop an experimental protocol, explore their own experimental results, and discriminate between different kinetic models. For this purpose, students are invited to select the best experimental protocol (optimizing the activity conditions/concentration of the enzyme and substrate, pH and temperature parameters), to discriminate different enzymatic models and determine the kinetic parameters through both linear transformations of the Michaelis–Menten equations (Lineweaver–Burk double-reciprocal transformation) and nonlinear regression using the Solver tool of Microsoft Office Excel.