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Application of I TASSER, trRosetta, UCSF Chimera, HADDOCK server, and HEX loria for De Novo and In Silico Design of Proteins
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Teaching virtual protein-centric CUREs and UREs using computational tools.

Anthony Bell1, Laura Christian2, David Hecht3

  • 1University of San Diego, San Diego, California, USA.

Biochemistry and Molecular Biology Education : a Bimonthly Publication of the International Union of Biochemistry and Molecular Biology
|September 12, 2020
PubMed
Summary
This summary is machine-generated.

Free computational tools were used to teach undergraduate research experiences, focusing on noncovalent interactions. This approach successfully integrated key components of Course-based Undergraduate Research Experiences (CUREs) for student learning.

Keywords:
computationasl experimental approachescourse-based undergraduate research experiencesprotein biochermistryremote laboratory teaching

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Area of Science:

  • Computational Chemistry
  • Biochemistry Education

Background:

  • Course-based Undergraduate Research Experiences (CUREs) are vital for scientific training.
  • Integrating research components into coursework enhances student learning and engagement.
  • Understanding noncovalent interactions is crucial in chemistry and biology.

Purpose of the Study:

  • To implement free, accessible computational approaches for teaching CUREs.
  • To emphasize the role of noncovalent interactions in molecular structure, binding, and catalysis.
  • To develop adaptable CURE modules suitable for various academic levels.

Main Methods:

  • Utilized readily available and free computational tools.
  • Designed CURE modules covering scientific background, hypothesis development, and proposal writing.
  • Incorporated experimental design, teamwork, quantitative data analysis, and presentation skills.

Main Results:

  • Successfully taught core CURE components using computational methods.
  • Students gained understanding of noncovalent interactions' contributions.
  • The approach proved adaptable for both class settings and individual research projects.

Conclusions:

  • Free computational approaches are effective for delivering CUREs.
  • This methodology enhances student comprehension of fundamental chemical and biological principles.
  • The CURE model effectively prepares students for scientific inquiry and research.