Cloud-based methods to predict the druggability of protein-protein interactions: applications to cancer and antimicrobial resistance.

计算模拟使我们能够预测生物分子如何相互作用（粘在一起），以及如果这些相互作用出错，如何导致疾病。如果了解了这一点，就有可能设计出新的药物来防止蛋白质分子之间的这种不必要的相互作用，从而治疗这种疾病。这种方法在癌症治疗和新型抗生素等领域具有巨大的潜力。问题是，这类研究所需的计算机模拟是巨大的——通常它们需要使用世界上最大的超级计算机。然而，新的研究表明，通过将工作分散到可能分布在世界各地的大量小型计算机上，如何完成相同类型的模拟研究。这样的计算机设施——“云”——已经在从商业到社交媒体的各个领域发挥了令人难以置信的重要作用，但这个想法还没有真正影响到计算医学科学。我们的目标是帮助实现这一目标。基于多年来开发计算机软件以帮助生物科学家和化学家轻松使用超级计算机进行研究的经验，我们将开发一个“基于云的计算化学”工具包。这将使世界各地更多的研究人员有可能进行同样的尖端医学研究，到目前为止，只有那些能够使用超级计算机的团队才有可能进行这些研究。我们将测试这个新设备的能力，用它来研究两种特殊的疾病——癌症和抗生素耐药性。在这两种情况下，我们都将以我们的工业合作伙伴UCB Celltech制药公司的研究经验和兴趣为基础。这确保了，如果我们得到一些有希望的结果，理论预测可以迅速在实验室中进行测试，如果它们成立，就可以用于开发针对这些关键健康问题的新药。

Computational simulations allow us to make predictions about how biological molecules interact with (stick to) each other, and how these interactions, if they go wrong, can lead to disease. If this is understood then there is the potential to design new drugs that prevent this unwanted interaction between the protein molecules, and so treat the disease. This approach has great potential in areas as diverse as cancer therapy and new antibiotics. The problem is that the computer simulations needed for this type of study are enormous - typically they require access to the world's largest supercomputers. However, new research has shown how the same type of simulation study can be accomplished by spreading the work over very large numbers of smaller computers which may be spread all around the world. Such computer facilities - "the cloud" - are already incredibly important in fields ranging from business to social media, but the idea hasn't yet really made an impact in computational medical science. Our aim is to help this happen.Building on years of previous experience developing computer software to help biological scientists and chemists easily use supercomputers for their research, we will develop a toolkit for "cloud-based computational chemistry". This will make it possible for far more researchers, all round the world, to do the same sort of cutting-edge medical research that until now was only possible for those groups who could access a supercomputer. We will test the power of this new facility by using it to study two particular diseases - cancer and antibiotic resistance. In both cases we will build on the research experience and interests of our industrial partner, the pharmaceutical company UCB Celltech. This ensures that, should we get some promising results, the theoretical predictions can quickly be tested in the lab, and if they hold up, taken forward into the development of new drugs for these key health problems.