The emergence of antimicrobial resistance threatens modern medicine and necessitates more personalized treatment of bacterial infections. Sequencing the whole genome of the pathogen(s) in a clinical sample offers one way to improve clinical microbiology diagnostic services, and has already been adopted for tuberculosis in some countries. A key weakness of a genetics clinical microbiology is it cannot return a result for rare or novel genetic variants and therefore predictive methods are required. Non-synonymous mutations in the S. aureusdfrB gene can be successfully classified as either conferring resistance (or not) by calculating their effect on the binding free energy of the antibiotic, trimethoprim. The underlying approach, alchemical free energy methods, requires large numbers of molecular dynamics simulations to be run. We show that a large number (N = 15) of binding free energies calculated from a series of very short (50 ps) molecular dynamics simulations are able to satisfactorily classify all seven mutations in our clinically derived testset. A result for a single mutation could therefore be returned in less than an hour, thereby demonstrating that this or similar methods are now sufficiently fast and reproducible for clinical use.

抗菌素耐药性的出现威胁到现代医学，并需要对细菌感染进行更个性化的治疗。对临床样品中病原体的整个基因组进行测序提供了一种改善临床微生物学诊断服务的方法，并且在某些国家已经被结核病采用。遗传学临床微生物学的一个关键弱点是它无法返回罕见或新颖遗传变异的结果，因此需要预测方法。金黄色葡萄球菌dfrB中的非同义突变通过计算基因对抗生素甲氧苄啶的结合自由能的影响，可将该基因成功地分类为具有抗药性（或无抗药性）。基本方法是炼金术自由能法，需要运行大量的分子动力学模拟。我们显示，从一系列非常短的（50 ps）分子动力学模拟计算得出的大量（N = 15）结合自由能能够令人满意地对我们临床衍生的测试集中的所有七个突变进行分类。因此，单个突变的结果可以在不到一个小时的时间内返回，从而证明该方法或类似方法现在已经足够快并且可重复用于临床。