Department of Biochemistry &Molecular Biophysics, Washington University School of Medicine, 660 South Euclid Avenue, St Louis, Missouri 63110, USA.
Department of Chemistry, Washington University in St Louis, One Brookings Drive, St Louis, Missouri 63130, USA.
Nat Commun. 2016 Oct 6;7:12965. doi: 10.1038/ncomms12965.
TEM β-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models to identify hidden conformations and explore their role in determining TEM's specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprinting and confirm our models' prediction that increased cefotaxime activity correlates with reduced Ω-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design.
TEM β-内酰胺酶使细菌具有抗多种抗生素的能力，并能迅速对新药产生活性。然而，晶体结构的差异并不能轻易解释功能的变化。我们采用马尔可夫状态模型来识别隐藏构象，并探索它们在决定 TEM 特异性中的作用。我们将这些模型与现有的药物设计工具相结合，创建了一种新的技术，称为玻尔兹曼对接，通过考虑构象异质性，更好地预测 TEM 的特异性。使用我们的 MSM，我们确定了与头孢噻肟活性相关的隐藏状态。为了实验检测我们预测的隐藏状态，我们使用快速质谱足迹法，并证实了我们的模型预测，即增加头孢噻肟的活性与减少Ω环的灵活性相关。最后，我们设计了新的变体来稳定隐藏的头孢噻肟酶状态，并发现它们的种群可以预测头孢噻肟在体外和体内的活性。因此，我们预计该框架在药物和蛋白质设计中有许多应用。
