Kinetic analysis and enzyme concentration effect relevant to dependence of amylolysis of starch granules on specific surface area concentration

Interfacial Catalysis during Amylolytic Degradation of Starch Granules: Current Understanding and Kinetic Approaches

Enzymatic hydrolysis of starch granules forms the fundamental basis of how nature degrades starch in plant cells, how starch is utilized as an energy resource in foods, and develops efficient, low-cost saccharification of starch, such as bioethanol and sweeteners. However, most investigations on starch hydrolysis have focused on its rates of degradation, either in its gelatinized or soluble state. These systems are inherently more well-defined, and kinetic parameters can be readily derived for different hydrolytic enzymes and starch molecular structures. Conversely, hydrolysis is notably slower for solid substrates, such as starch granules, and the kinetics are more complex. The main problems include that the surface of the substrate is multifaceted, its chemical and physical properties are ill-defined, and it also continuously changes as the hydrolysis proceeds. Hence, methods need to be developed for analyzing such heterogeneous catalytic systems. Most data on starch granule degradation are obtained on a long-term enzyme-action basis from which initial rates cannot be derived. In this review, we discuss these various aspects and future possibilities for developing experimental procedures to describe and understand interfacial enzyme hydrolysis of native starch granules more accurately.

Reliability factor for identification of amylolytic enzyme activity in the optimized starch-iodine assay

Amylolytic enzymes are a group of proteins degrading starch to its constitutional units. For high-throughput screening, simple yet accurate methods in addition to the reducing ends assays are required. In this article, the iodine assay, a photometric assay based on the intensely colored starch-iodine complex, was adapted to enable accurate and objective differentiation between enzyme and background activity using a newly introduced mathematical factor. The method was further improved by designing a simple setup for multiple time point detection and discussing the applicability of single wavelength measurements.