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1953 ], which displays the chemical properties of individual atoms, and cartoon or ribbon, which shows a more abstract, stylized version of the backbone’s secondary structures [Natarajan et al. 2008 ]. PyMOL is a popular viewer that gives access to many of these visualizations.¹⁶ These visualizations are tuned for scientists, and may not be appropriate for novices.

      One possible approach to manipulating three-dimensional objects is to use widgets. Widgets associate behavior with geometry in the scene, so users can interact directly with the environment [Conner et al. 1992 ]. The Sculpt system allows users to interact with and guide a protein as it folds in the presence of minimization of a physically plausible energy [Surles et al. 1994 ]. While Sculpt has some features in common with Foldit, it is a single-user application, while Foldit is a multiplayer game, with many new features.

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3 Framework

3.1 Introduction

      This chapter introduces a general framework for scientific discovery games. We present guidelines for mapping a scientific problem into a game, and address the often conflicting goals of engagement and scientific relevance. The driving example is Foldit, a game for scientific discovery in biochemistry. We describe the architecture of the game. The architecture is flexible and able to coevolve, along with the game’s players, to improve as a tool. We discuss the teaching and reward structures in the game, intended to appeal to a wide variety of players, regardless of biochemistry background.

      A scientific discovery game translates a class of computationally difficult scientific problems into puzzles, and provides a game-like mechanism for non-scientist players to help solve these problems. Many traditional aspects of game design apply to scientific discovery games, including the design of introductory levels to draw newcomers and explain game mechanics, the use of a client-server architecture for competition and collaboration, and the requirement that the game be fun. However, unlike games whose goal is entertainment or education, scientific discovery games introduce a unique challenge: enabling non-scientist natural problem solvers to advance a specific scientific domain. This challenge influences all aspects of the game design. First, visualization and graphics need to promote human ability to see complex solutions and convey accurate scientific information while remaining accessible to beginners. Second, interaction design must optimize for natural interactions suitable for the human exploration process, while still respecting scientific constraints. Finally, the scoring mechanism needs to be informative enough to promote multiple human strategies, while remaining true to the latest models of the underlying scientific phenomenon. Perhaps the most distinguishing feature and the greatest difficulty of design for this type of game is that the solution to the scientific problem, and thus the solution to the corresponding puzzles, is unknown. Since we do not know the solution a priori, we cannot design the game with specific solutions in mind.

      Figure 3.1 Foldit webpage. The front page shows recent news about the game, the top players and groups for the current puzzles, and allows the player to log in.

      To explore this space, we focused on human ability to reason about 3D structures and on the biochemistry domain, where many problems tend to be structural. We developed Foldit, a biochemical discovery game. In this chapter, we discuss the framework for Foldit’s design, with emphasis on the game’s initial focus on protein structure prediction—determining a protein’s shape given its sequence of constituent amino acids. Protein structure prediction involves finding favorable interactions that form when the protein’s chemical groups come into contact—essentially a 3D jigsaw puzzle. We believe that humans’ innate spatial reasoning ability makes it possible for non-scientists to make useful contributions to this problem. We leverage scientists’ knowledge to shape the rules of the game, thus enabling a much larger pool of non-scientists to make discoveries within this framework.

      The webpage for Foldit is located at http://fold.it. The front page is shown in Figure 3.1. Foldit was publicly released in May 2008. During the first two years following release, we ran roughly 600 structure prediction puzzles and had over 57,000 players from a wide variety of backgrounds participate.

      The rest of this chapter describes our experience designing Foldit, with a special emphasis on the unique challenges posed by making biochemistry problems accessible to anyone. The creation of Foldit was a challenging and multidisciplinary project, drawing together computer science, art, game design and biochemistry.

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