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Published on: December 25, 2021
Protein structure-function exploration initiative in undergraduate biochemistry and independent research courses
1Natural Sciences, Bethune-Cookman University, Daytona Beach, Florida, USA.
Abstract:
Protein structure-function relationship serves as the primary learning outcome in any undergraduate biochemistry course. We expanded the protein structure-function exploration, PSFE initiative during COVID-19 to provide more effective and engaging experience to our undergraduates in biochemistry and independent research courses. Multiple alignments of protein sequences provided crucial insight into sequence conservation across many species and thus allow identification of those sections of the sequence most critical to protein function. We used Anabaena Sensory Rhodopsin, ASR its transducer, ASRT and downstream novel kinase gene products of Anabaena PCC 7120 to seek their alignment with homologs in available database. Pymol served an opportunity to achieve this goal (interactive learning during lab session and stimulation of course content discussion) in interesting ways. The PSFE initiative expansion continued during pandemic using online/hybrid modality. Initially model examples all helical ASR and beta-sheet ASRT were introduced to connect and integrate our ongoing research interest into classroom activities. Subsequently, undergraduates in biochemistry course were assigned a homolog of model proteins any particular protein of students choice to study and characterize using Pymol in semester. During first phase, each undergraduate worked independently using established guidelines. Student's exploration progress was periodically reviewed in pilot phase with majority of students who perceived it as challenging task successfully completed the assignment. Using the PyMol application to reinforce visual understanding of protein structure was highly satisfying experience that greatly enriched undergraduates understanding and appreciation. This article reports a session from the virtual international 2021 IUBMB/ASBMB workshop, "Teaching Science on BigData."
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