Published By: University of Toronto News, 2/6/2017

>> View the Article <<

Summary

University of Toronto researchers have developed algorithms which can efficiently generate an accurate 3D image of a protein molecule from a set of 2D images in just a few minutes. This advance has far-reaching implications for the medical field. For example, drug researchers will be able to use these 3D protein models to analyze the structure of disease-specific proteins and predict the way experimental medications will bind to those proteins inside the body.

Flesch-Kincaid Grade Level of Article: 14.8

Extended Discussion Questions

• The article points out that modeling which proteins a drug would interact with could eliminate some guesswork in the early stages of developing a new drug.
  • Are there ways that computational modeling could also help other aspects of drug development?
  • Do you think computer models could ever reduce — or even eliminate — the need for clinical trials with humans? Why or why not?
• These new algorithms allow medical researchers to analyze proteins at much higher speeds than previously, using fewer computational resources. How might algorithms that improve the speed and efficiency of analyzing information help researchers or businesses in other fields? (Example to start: YouTube?)

Global Impact Learning Objectives:

• LO 7.2.1 Explain how computing has impacted innovations in other fields.

Global Impact Essential Knowledge:

• EK 7.2.1B Scientific computing has enabled innovation in science and business.
• EK 7.2.1G Advances in computing as an enabling technology have generated and increased the creativity in other fields.

Other CSP Big Ideas:

• Idea 4 Algorithms

Banner Image: “Network Visualization – Violet – Offset Crop”, derivative work by ICSI. New license: CC BY-SA 4.0. Based on “Social Network Analysis Visualization” by Martin Grandjean. Original license: CC BY-SA 3.0