Combining structure and genomics to understand antimicrobial resistance.
Combining structure and genomics to understand antimicrobial resistance.
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DOI：
10.1016/j.csbj.2020.10.017
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发表时间：
2020
影响因子：
6
通讯作者：
Furnham N
中科院分区：
文献类型：
--
作者：
Tunstall T;Portelli S;Phelan J;Clark TG;Ascher DB;Furnham N
针对细菌、病毒和寄生虫病原体的抗微生物药物已经改变了人类和动物的健康。然而，它们的广泛使用（和误用）导致了抗菌素耐药性（AMR）的出现，这对公共卫生和畜牧业构成了潜在的灾难性威胁。抗菌素耐药性的发展有几种途径，既有内在的，也有后天的。一个主要途径是通过编码区域的非同义单核苷酸多态性（nssnp）。使用高通量测序数据的大规模基因组研究为快速检测和应对与AMR相关的基因突变提供了强有力的新方法。然而，这些研究在其机械洞察力方面是有限的。计算工具可以快速和廉价地评估突变对蛋白质功能和进化的影响。随后的见解可以为实验研究提供信息，并指导现有的或新的计算方法。在这里，我们回顾了一系列基于序列和结构的计算工具，重点关注成功用于研究临床重要病原体（特别是结核分枝杆菌）中药物靶点突变效应的工具。将基因组结果与突变的生物物理效应相结合，可以帮助揭示耐药性发展的分子基础和后果。此外，我们总结了如何应用这种对耐药性的机制理解来限制抗菌素耐药性的影响。
Antimicrobials against bacterial, viral and parasitic pathogens have transformed human and animal health. Nevertheless, their widespread use (and misuse) has led to the emergence of antimicrobial resistance (AMR) which poses a potentially catastrophic threat to public health and animal husbandry. There are several routes, both intrinsic and acquired, by which AMR can develop. One major route is through non-synonymous single nucleotide polymorphisms (nsSNPs) in coding regions. Large scale genomic studies using high-throughput sequencing data have provided powerful new ways to rapidly detect and respond to such genetic mutations linked to AMR. However, these studies are limited in their mechanistic insight. Computational tools can rapidly and inexpensively evaluate the effect of mutations on protein function and evolution. Subsequent insights can then inform experimental studies, and direct existing or new computational methods. Here we review a range of sequence and structure-based computational tools, focussing on tools successfully used to investigate mutational effect on drug targets in clinically important pathogens, particularly Mycobacterium tuberculosis. Combining genomic results with the biophysical effects of mutations can help reveal the molecular basis and consequences of resistance development. Furthermore, we summarise how the application of such a mechanistic understanding of drug resistance can be applied to limit the impact of AMR.
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