Transition state analysis to guide drug discovery.

迫切需要找到更好的方法来发现药物。三分之一的临床药物靶向g蛋白偶联受体（gpcr）。当GPCR被药物激活时，它会改变其结构形状（构象）。激活通过一系列结构中间体进行。中间构象的途径决定了由药物受体复合物激活的细胞内信号通路。目前还不可能预测药物是否会发出信号（疗效）以及通过哪种途径（信号偏倚）。我们已经开发了一种计算方法（过渡状态分析），模型中间构象状态作为受体被激活。我们的方法准确预测了药物在两种gpcr上的疗效和偏倚。在商业化之前，我们需要用更广泛的治疗靶点和药物来验证我们的方法。这项技术将加速药物发现，节省时间和金钱，并对最终用户产生重大影响。

There is an urgent need to find better methods to discover drugs. A third of clinical drugs target G-protein-coupled receptors (GPCRs). When a GPCR is activated by a drug, it changes its structural shape (conformation). Activation proceeds via a series of structural intermediates. The pathway of intermediate conformations dictates the intracellular signalling pathway activated by the drug:receptor complex. Currently it is not possible to predict if a drug will signal (efficacy) and by which pathway (signalling bias). We have developed a computational approach (Transistion State Analysis) that models intermediate conformational states as receptors are activated. Our method accurately predicted efficacy and bias of drugs at two GPCRs. Prior to commercialisation, we need to validate our methods using a wider range of therapeutic targets and drugs. This technology will accelerate drug discovery, saving time and money, and have significant end-user impact.