HCC-Small: Protein Design Through Massively Distributed Video Games

在过去的几十年里，生物化学家们发现，几乎所有的基本分子设计问题都是关于复杂分子的几何关系的。这种算法的大规模并行和分布式版本最近已经被开发出来，以期找到具有剪切蛮力的这种蛋白质。例如，实现从全球PC用户那里获取空闲CPU时间的屏幕保护程序，以提供足够的计算能力来解决蛋白质预测问题。到目前为止，所有这些尝试都产生了非常有限的改善。这个项目采取了一种截然不同的方法：分子折叠问题被描绘成一个大规模分布的3D益智游戏，并鼓励人们与计算机合作，寻找当前公开问题的解决方案，包括癌症、艾滋病的治疗和新生物燃料的发现。其基本想法是利用用户辅助优化蛋白质设计，并将其制定并呈现为数千人玩的竞争游戏。这个项目的目的是，人们玩这个游戏是因为它有趣(它看起来像一个有趣的3D拼图，而不像一些生物化学教科书)，它让人上瘾，它是竞争的，它是协作的(玩家可以集体合作解决一个问题)，有影响力(玩家想要从治疗癌症的药物中获得荣誉)。这项提议的影响在于它解决了一些基本领域：1)如何最好地开发游戏，以最大限度地提高人类发现新蛋白质的能力，而不是目前仅使用计算方法所能做到的；2)确定成功的分子设计游戏的指导原则；3)如何最好地将游戏开发原则推广到尽可能广泛的生化问题；4)揭示从人们玩游戏的方式中学到的东西，以及如何“提炼”这些策略，以开发更强大的自动化方法。

In the past few decades biochemists have discovered that practically all fundamental molecular design problems are about the geometric relationship of complex molecules. Massively parallel and distributed versions of such algorithms have been recently developed in hope of finding such proteins with shear brute force. For example, implementing screensavers that harvest idle CPU time from PC users worldwide to provide sufficient computing power to solve the protein prediction problems. So far, all these attempts have produced very modest improvements. This project takes a radically different approach: the molecular folding problem is cast as a massively distributed 3D puzzle game, and encourages people to work together with computers to find the solutions to current open problems including cures for cancer, AIDS, and discovery of novel biofuels.The fundamental idea is to employ user-assisted optimization for protein design, and formulate and present it as a competitive game played by thousands of people. The intention in this project is that people will play the game beacause it is fun (it looks like a fun 3d puzzle and not like some biochemistry textbook), it is addicting, it is competitive, it is collaborative (players can work together in groups to solve a problem), has impact (players want to get credit for the drug that cures cancer). The impact of this proposal is in its addressing of a number of fundamental areas: 1) how to best develop games to maximize human ability to discover novel proteins beyond what is currently possible with computation-only approaches; 2) determining the guiding principles of a successful molecular design game; 3) how to best generalize game-development principles to the widest possible range of biochemical problems; 4) revealing what is learned from the way people play the game, and how these strategies could be "distilled" towards developing stronger automated approaches.