摘要

抗生素耐药性的上升威胁着现代医学;为了对抗它，需要新的诊断方法。测序病原体的全基因组提供了准确确定哪些抗生素将有效治疗患者的潜力。这种方法的一个关键限制是它不能分类罕见的或以前看不见的突变。在这里，我们表明，炼金术自由能的方法，从计算化学的一套行之有效的方法，可以成功地预测金黄色葡萄球菌二氢叶酸还原酶的突变是否赋予甲氧苄氨嘧啶的抗性。我们还通过计算最常见的抗性赋予突变F99Y降低甲氧苄氨嘧啶的结合自由能以及比较预测和实验测得的七种不同突变的最小抑制浓度，来证明该方法在数量上准确。最后，通过考虑每个突变的多达32个自由能计算，我们估计其特异性和灵敏度。

The rise of antibiotic resistance threatens modern medicine; to combat it new diagnostic methods are required. Sequencing the whole genome of a pathogen offers the potential to accurately determine which antibiotics will be effective to treat a patient. A key limitation of this approach is that it cannot classify rare or previously unseen mutations. Here we demonstrate that alchemical free energy methods, a well-established class of methods fromcomputational chemistry, can successfully predict whether mutations in Staphylococcus aureus dihydrofolate reductase confer resistance to trimethoprim. We also show that the method is quantitatively accurate by calculating how much the most common resistance-conferring mutation, F99Y, reduces the binding free energy of trimethoprim and comparing predicted and experimentally measured minimum inhibitory concentrations for seven different mutations. Finally, by considering up to 32 free energy calculations for each mutation, we estimate its specificity and sensitivity.

https://www.sciencedirect.com/science/article/pii/S2451945617304373