Use of interactive mathematical simulations in Fundamentals of Biochemistry, a LibreText online educational resource, to promote understanding of dynamic reactions

Author:

Jakubowski Henry V.1ORCID,Agnew Henry2,Jardine Bartholomew3,Sauro Herbert M.3

Affiliation:

1. Department of Chemistry College of Saint Benedict/Saint John's University Saint Joseph Minnesota USA

2. Department of Chemistry and Biochemistry University of California San Diego San Diego California USA

3. Department of Bioengineering University of Washington Seattle Washington USA

Abstract

AbstractBiology is perhaps the most complex of the sciences, given the incredible variety of chemical species that are interconnected in spatial and temporal pathways that are daunting to understand. Their interconnections lead to emergent properties such as memory, consciousness, and recognition of self and non‐self. To understand how these interconnected reactions lead to cellular life characterized by activation, inhibition, regulation, homeostasis, and adaptation, computational analyses and simulations are essential, a fact recognized by the biological communities. At the same time, students struggle to understand and apply binding and kinetic analyses for the simplest reactions such as the irreversible first‐order conversion of a single reactant to a product. This likely results from cognitive difficulties in combining structural, chemical, mathematical, and textual descriptions of binding and catalytic reactions. To help students better understand dynamic reactions and their analyses, we have introduced two kinds of interactive graphs and simulations into the online educational resource, Fundamentals of Biochemistry, a LibreText biochemistry book. One is available for simple binding and kinetic reactions. The other displays progress curves (concentrations vs. time) for simple reactions and complex metabolic and signal transduction pathways. Users can move sliders to change dissociation and kinetic constants as well as initial concentrations and see instantaneous changes in the graphs. They can also export data into a spreadsheet for further processing, such as producing derivative Lineweaver‐Burk and traditional Michaelis–Menten graphs of initial velocity (v0) versus substrate concentration.

Funder

National Institute of General Medical Sciences

Fundación Para La Innovación Y La Prospectiva En Salud En España

Publisher

Wiley

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