1. Who are the three scientists awarded the 2024 Nobel Prize in Chemistry?
1) Watson, Crick, and Franklin
2) Einstein, Bohr, and Planck
3) Hassabis, Jumper, and Baker
4) Curie, Meitner, and Hodgkin
2. What organization is Demis Hassabis associated with?
1) Microsoft Research
2) IBM Watson
3) Google DeepMind
4) OpenAI
3. What is David Baker’s primary contribution to protein science?
1) Discovering new natural proteins
2) Designing completely new proteins that don’t exist in nature
3) Improving X-ray crystallography
4) Developing new microscopes
4. What is AlphaFold2?
1) A new protein
2) A microscope
3) A crystallography technique
4) An AI model for predicting protein structures
5. By October 2024, how many scientists had adopted AlphaFold2?
1) 500,000
2) 1 million
3) Over 2 million
4) 3 million
6. What is Top7?
1) A research team
2) A designed protein created by Baker’s team
3) A computer model
4) A microscope brand
7. What traditional method was used to study protein structures before AI?
1) X-ray crystallography
2) Nuclear magnetic resonance
3) Electron microscopy
4) Mass spectrometry
8. In which year did AlphaFold2 achieve its breakthrough?
1) 2018
2) 2019
3) 2020
4) 2021
9. What institution is David Baker affiliated with?
1) Harvard University
2) MIT
3) Stanford University
4) University of Washington
10. What was the main challenge in protein research that AI helped solve?
1) Predicting 3D structure from amino acid sequence
2) Creating new amino acids
3) Measuring protein mass
4) Identifying protein function
11. When was Top7 developed?
1) 2001
2) 2002
3) 2003
4) 2004
12. What is one potential application of designed proteins?
1) Space travel
2) Nanotechnology
3) Nuclear power
4) Solar energy
13. What did AlphaFold2’s accuracy compare to?
1) Electron microscopy
2) X-ray crystallography
3) Mass spectrometry
4) NMR spectroscopy
14. What distinguishes Baker’s work from Hassabis and Jumper’s?
1) Creating new proteins vs. predicting existing structures
2) Using AI vs. not using AI
3) Studying natural vs. synthetic proteins
4) Academic vs. industrial research
15. What are the potential applications of these discoveries?
1) Space exploration
2) Quantum computing
3) Medicine, agriculture, and environmental science
4) Transportation
16. How did AI learn to predict protein structures?
1) Through random guessing
2) By learning patterns from known structures
3) Through chemical reactions
4) By human programming
17. What is the primary focus of Hassabis and Jumper’s work?
1) Creating new proteins
2) Predicting protein structures using AI
3) Studying protein function
4) Developing new laboratory techniques
18. What is one field where designed proteins could be useful?
1) Space exploration
2) Industrial processes
3) Transportation
4) Entertainment
19. What type of proteins did Baker work on?
1) Only natural proteins
2) Modified natural proteins
3) Completely new, designed proteins
4) Plant proteins only
20. What role did AI play in protein structure prediction?
1) Minor support role
2) No role
3) Revolutionary breakthrough role
4) Limited experimental role
21. What is a key benefit of AI in protein research?
1) Lower cost
2) Faster prediction of structures
3) Better microscopes
4) More funding
22. What makes the 2024 Nobel Prize significant?
1) First time for protein research
2) Recognition of AI’s role in science
3) Largest prize amount
4) Most nominees
23. How did traditional protein structure determination differ from AI methods?
1) More accurate
2) Cheaper
3) Faster
4) Required more time and effort
24. What area of science does this Nobel Prize recognize?
1) Physics
2) Chemistry
3) Medicine
4) Biology
25. What is the main advantage of designed proteins?
1) They are natural
2) They are cheaper
3) They can have specific desired functions
4) They are more stable