DockIt: Development and launch of a crowd-sourced serious-games platform for protein docking for use by the public and the scientific community.

目的-这笔赠款的目的是开发一款严肃而有趣的电脑游戏(DockIt)，供众多玩家(人群)使用，以模拟两个大的生物分子(蛋白质)如何结合在一起，从而发挥它们的功能。蛋白质对接：一个尚未解决的生物学问题-蛋白质是大的生物分子，通常至少有1000个原子，执行许多生物学功能。蛋白质的三维结构是复杂的。其生物活性的核心是，它经常与另一种蛋白质对接形成复合体。该复合体的结构由分子中的原子相互作用的方式决定。复合体的形状有助于理解蛋白质的作用机制，这一知识在食品安全、工业生物技术和新型药物设计方面具有重大好处。在已知未结合组分的结构的情况下，使用计算方法来预测复合体的形状。然而，这些项目只取得了有限的成功。其他科学领域的研究，包括对蛋白质形状的建模，已经表明，使用人类判断力的个人有时可以找到解决尚不能自动解决的问题的方法。特别是，从一群参与者那里找到一致的解决方案可以产生成功的结果。这种方法被称为众包。因此，我们建议开发一款电脑游戏DockIt，玩家将操纵这两种蛋白质结构并预测一个复合体。这类似于解决三维拼图。对接将从一组由最先进的程序生成的可能的复杂结构开始，因此成功的游戏可以产生比自动生成的结构更好的预测结构。DOCKIT游戏-我们将设计DockIt，使其通过利用休闲游戏行业的最新技术和设计来玩得很有趣。我们将为包括平板电脑、智能手机和个人电脑在内的一系列平台开发DockIt，从而确保广泛接受。用户将能够调整两种蛋白质的相对位置，并改变每种蛋白质的形状。改变蛋白质的方法将被编码为一套用户可以使用的食谱。我们将提供评分功能，向玩家反馈对预测结构的质量估计。DOCKIT发布-我们将发布DockIt，供学术界和公众使用。我们宣传DockIt的战略是与我们的合作伙伴、合作者和行业联系人合作，通过他们广泛的玩家数据库来推广DockIt，例如通过在时事通讯中包含在内。对接目标将包括那些已知解决方案的目标，以及那些使用DockIt解决现实世界生物问题的目标。玩家将从主机服务器下载一个可能的复合体，然后改变其形状以预测最佳复合体，然后将其返回到服务器。来自不同玩家的结果将被汇集在一起，我们将确定最好的预测。玩家将得到一个教程的支持，该教程将提供学习游戏的渐进步骤。将提供电子邮件支持，并将建立一个社交网络小组(如Google+、Facebook、LinkedIn和Twitter)。我们将在科学会议上发表演讲，并发表技术论文。我们将与科普杂志一起发布针对奥运会的新闻稿。我们还将针对电视、广播、教育媒体和行业团体。我们设想，DockIt可以在中小学和大学的教学中使用。

AIM - The aim of this grant is to develop a serious and enjoyable computer game (DockIt) used by numerous players (a crowd) to model how two large biological molecules (proteins) fit together and thereby perform their function. PROTEIN DOCKING: AN UNSOLVED BIOLOGICAL PROBLEM - Proteins are large biological molecules, generally with at least 1,000 atoms, which perform many biological functions. The three-dimensional structure of a protein is complex. Central to its biological activity is that often it docks to another protein to form a complex. The structure of the complex is dictated by how the atoms in the molecules interact with each other. The shape of the complex helps in understanding the mechanism of action of proteins and this knowledge can have major benefits in food security, industrial biotechnology and the design of novel pharmaceuticals. Computational approaches are used to predict the shape of a complex given knowledge of the structures of the unbound components. However the programs have only limited success. Research in other areas of science, including modelling the shape of proteins, has shown that individuals using human judgement can sometimes find solutions to problems that cannot yet be solved automatically. In particular finding consensus solutions from a crowd of players can yield successful results. This approach is known as crowd sourcing. Accordingly, we propose to develop a computer game DockIt where the players will manipulate the two protein structures and predict a complex. This is similar to solving a three-dimensional jigsaw puzzle. The docking will start with a set of possible complexes generated by state of the art programs and thus successful plays can yield predicted structures superior to those automatically generated.THE DOCKIT GAME - We will design DockIt so that it is fun to play by exploiting the latest technology and design from the casual games industry. We will develop DockIt for a range of platforms including tablets, smartphones and PCs thereby ensuring wide take-up. A user will be able to adjust the relative position of the two proteins and to change the shape of each protein. The approaches to alter the proteins will be encoded as a set of recipes which the user can employ. We will provide a scoring function to feedback to the players an estimate of the quality of the predicted structure.RELEASE OF DOCKIT - We will release DockIt for use by the academic community and to the general public. Our strategy to publicise DockIt is to work with our partners, collaborators and industry contacts to promote DockIt via their extensive player databases, for example by inclusion in newsletters. The docking targets will include those for which the solution is known and those where DockIt is used to solve a real-world biological problem. Players will download a possible complex from the host server and then change its shape to predict the best complex which will then be returned to the server. Results from different players will be pooled and we will identify the best prediction. Players will be supported by the presence of a tutorial which will provide progressive steps to learn the game. There will be E-mail support and a social network group will be established (e.g. Google+, FaceBook, LinkedIn and Twitter).DISSEMINATION - DockIt will be disseminated to the scientific community and the general public. We will make presentations at scientific conferences and publish technical papers. We will issue a press release aimed at the games together with popular science magazines. We will also target TV, Radio, the educational press and trade bodies. We envisage that DockIt could be used at schools and universities in teaching.