Video Gamers Beat Scientists and Computers in Protein Folding Competition

Researchers from the University of Michigan (U-M) have discovered that video gamers can be as good or better than professionally trained crystallographers and computer algorithms at identifying the shape of a protein, a finding that has the potential to bolster citizen science initiatives and classroom gamification.

The researchers held a competition "to interpret biochemical data in order to discover the protein's structure," according to a news release. Participants included 469 gamers, two trained crystallographers, 61 University of Michigan undergraduate students with computer modeling training, and two separate computer algorithms.

The video gamers were playing Foldit, a computer-based videogame that challenges players to use their puzzle-solving skills to fold 3-D graphical representations of proteins and consequently contribute to crowdsourced scientific research into diseases such as HIV, cancer and Alzheimer's. In the end, the video gamers outperformed all other groups in the competition.

Analysis of the competition results "uncovered a new family of proteins that appears to be involved in preventing plaque formation, which is implicated in diseases like Alzheimer's," stated the news release.

One major difference between the winning gamers and the other groups is that the video gamers worked collaboratively, while the crystallographers, computer modeling students and computer algorithms worked independently. The researchers concluded that collaboration may improve results in this type of research.

"We think this is a big deal because interpreting an electron-density map can be a labor-intensive, error-prone process — and we show that crowd-sourced Foldit players can do it as well as, or better than, professionally trained crystallographers," said Brian Koepnick in a prepared statement. Koepnick  is a graduate student from the University of Washington Institute for Protein Design, and a member of the team that designed the contest and analyzed its results.

Through this competition, the researchers picked up some tips and tricks from the gamers and plan to incorporate those findings into the software scientists use when modeling protein structures.

Scott Horowitz, a postdoctoral fellow at U-M and co-author of the study, said he plans to start using Foldit in his classes. "I've seen how much players learn about proteins from playing this game,"he told Michigan News. "We spend weeks and weeks trying to jam this into students' brains and Foldit players learn it naturally because it's fun."

The study was led by U-M researchers in collaboration with the University of Washington, University of Massachusetts-Dartmouth and Northeastern University, according to Michigan News. The study has been published in Nature Communications.

About the Author

Leila Meyer is a technology writer based in British Columbia. She can be reached at [email protected].

Featured

  • abstract generative AI technology

    Apple and Google Strike AI Deal to Bring Gemini Models to Siri

    Apple and Google announced they have embarked on a multiyear partnership that will put Google's Gemini models and cloud technology at the core of the next generation of Apple Foundation Models, a move that could help Apple accelerate long-promised upgrades to Siri while handing Google a high-profile distribution win on the iPhone.

  • network of various technology icons

    Newly Launched Agentic AI Foundation Brings Together Tech Giants for Open Source AI Development

    The Linux Foundation has announced the formation of the Agentic AI Foundation, bringing together Microsoft, OpenAI, Anthropic, and other major tech companies to advance open source development of autonomous AI systems.

  • glowing brain above stacked coins

    The Higher Ed Playbook for AI Affordability

    Fulfilling the promise of AI in higher education does not require massive budgets or radical reinvention. By leveraging existing infrastructure, embracing edge and localized AI, collaborating across institutions, and embedding AI thoughtfully across the enterprise, universities can move from experimentation to impact.

  • AI word on microchip and colorful light spread

    Microsoft Unveils Maia 200 Inference Chip to Cut AI Serving Costs

    Microsoft recently introduced Maia 200, a custom-built accelerator aimed at lowering the cost of running artificial intelligence workloads at cloud scale, as major providers look to curb soaring inference expenses and lessen dependence on Nvidia graphics processors.