Departments of Molecular Physiology and of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, United States.
Departments of Molecular Physiology and of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, United States; Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala 75146, Sweden.
Curr Opin Struct Biol. 2018 Oct;52:80-86. doi: 10.1016/j.sbi.2018.09.001. Epub 2018 Sep 19.
Beta-lactamase enzymes mediate the most common forms of gram-negative antibiotic resistance affecting clinical treatment. They also constitute an excellent model system for the difficult problem of understanding how allosteric mutations can augment catalytic activity of already-competent enzymes. Multiple allosteric mutations have been identified that alter catalytic activity or drug-resistance spectrum in class A beta lactamases, but predicting these in advance continues to be challenging. Here, we review computational techniques based on structure and/or molecular simulation to predict such mutations. Structure-based techniques have been particularly helpful in developing graph algorithms for analyzing critical residues in beta-lactamase function, while classical molecular simulation has recently shown the ability to prospectively predict allosteric mutations increasing beta-lactamase activity and drug resistance. These will ultimately achieve the greatest power when combined with simulation methods that model reactive chemistry to calculate activation free energies directly.
β-内酰胺酶介导最常见的革兰氏阴性抗生素耐药形式,影响临床治疗。它们也是理解变构突变如何增强已经有活性的酶的催化活性这一难题的极好模型系统。已经确定了多种变构突变,这些突变改变了 A 类β-内酰胺酶的催化活性或药物耐药谱,但提前预测这些突变仍然具有挑战性。在这里,我们回顾了基于结构和/或分子模拟的计算技术,以预测这些突变。结构基技术在开发用于分析β-内酰胺酶功能的关键残基的图算法方面特别有帮助,而经典的分子模拟最近显示了预测变构突变增加β-内酰胺酶活性和耐药性的能力。当与模拟方法结合使用时,这些方法可以直接计算反应性化学的激活自由能,从而实现最大的效果。