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Novel 3D/VR Interactive Environment for MD Simulations, Visualization and Analysis
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ezCADD: A Rapid 2D/3D Visualization-Enabled Web Modeling Environment for Democratizing Computer-Aided Drug Design.

Aoxiang Tao1, Yuying Huang1, Yasuhiro Shinohara1

  • 1Department of Biomedical and Pharmaceutical Sciences, College of Pharmacy, Kasiska Division of Health Sciences , Idaho State University , Meridian , Idaho 83642 , United States.

Journal of Chemical Information and Modeling
|November 8, 2018
PubMed
Summary

ezCADD is a new web-based tool making computer-aided drug design (CADD) accessible to researchers without computational training. This user-friendly platform enhances understanding of drug-receptor interactions and aids drug discovery.

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Area of Science:

  • Biomedical research
  • Computational chemistry
  • Drug discovery

Background:

  • Computer-aided drug design (CADD) software often requires computational expertise and significant funding, limiting its accessibility.
  • A substantial population of biomedical researchers lacks the necessary training and resources to utilize CADD tools effectively.
  • Bridging this gap is crucial for advancing drug discovery efforts globally.

Purpose of the Study:

  • To develop and present ezCADD, a web-based CADD environment designed for ease of use and accessibility.
  • To implement fundamental CADD applications including small-molecule docking, protein-protein docking, and binding pocket detection within ezCADD.
  • To evaluate the usability and effectiveness of ezCADD for researchers with no prior computational background.

Main Methods:

  • ezCADD was developed based on principles of simplicity, speed, user-friendliness, and 2D/3D visualization.
  • Core applications like molecular docking and binding pocket analysis were implemented.
  • First-year pharmacy students used ezCADD as an active learning tool in a drug action course to assess user experience.

Main Results:

  • The ezCADD web service successfully managed 95 simultaneous molecular docking jobs.
  • A high percentage of students (97%) completed experiments with minimal training, and 88% found ezCADD easy to use.
  • Students reported significant improvements in understanding drug-receptor interactions and molecular visualization.

Conclusions:

  • ezCADD effectively lowers barriers to CADD, supporting drug discovery research for non-computational scientists.
  • The platform serves as an effective tool for Science, Technology, Engineering, and Mathematics (STEM) education, enhancing scientific understanding.
  • ezCADD demonstrates potential for broader adoption in both research and educational settings.