Department of Biochemistry, Indian Institute of Science, Bangalore, 560012, India.
J Biomol Struct Dyn. 2013;31(1):44-58. doi: 10.1080/07391102.2012.691361. Epub 2012 Jul 18.
Resistance to therapy limits the effectiveness of drug treatment in many diseases. Drug resistance can be considered as a successful outcome of the bacterial struggle to survive in the hostile environment of a drug-exposed cell. An important mechanism by which bacteria acquire drug resistance is through mutations in the drug target. Drug resistant strains (multi-drug resistant and extensively drug resistant) of Mycobacterium tuberculosis are being identified at alarming rates, increasing the global burden of tuberculosis. An understanding of the nature of mutations in different drug targets and how they achieve resistance is therefore important. An objective of this study is to first decipher sequence as well as structural bases for the observed resistance in known drug resistant mutants and then to predict positions in each target that are more prone to acquiring drug resistant mutations. A curated database containing hundreds of mutations in the 38 drug targets of nine major clinical drugs, associated with resistance is studied here. Mutations have been classified into those that occur in the binding site itself, those that occur in residues interacting with the binding site and those that occur in outer zones. Structural models of the wild type and mutant forms of the target proteins have been analysed to seek explanations for reduction in drug binding. Stability analysis of an entire array of 19 mutations at each of the residues for each target has been computed using structural models. Conservation indices of individual residues, binding sites and whole proteins are computed based on sequence conservation analysis of the target proteins. The analyses lead to insights about which positions in the polypeptide chain have a higher propensity to acquire drug resistant mutations. Thus critical insights can be obtained about the effect of mutations on drug binding, in terms of which amino acid positions and therefore which interactions should not be heavily relied upon, which in turn can be translated into guidelines for modifying the existing drugs as well as for designing new drugs. The methodology can serve as a general framework to study drug resistant mutants in other micro-organisms as well.
耐药性限制了许多疾病中药物治疗的效果。耐药性可以被认为是细菌在暴露于药物的细胞的恶劣环境中生存斗争的成功结果。细菌获得耐药性的一个重要机制是药物靶标发生突变。结核分枝杆菌（Mycobacterium tuberculosis）的耐药菌株（多药耐药和广泛耐药）正在以惊人的速度被发现，这增加了全球结核病负担。因此，了解不同药物靶标突变的性质及其如何产生耐药性非常重要。本研究的目的之一是首先破译已知耐药突变体中观察到的耐药性的序列和结构基础，然后预测每个靶标中更容易获得耐药突变的位置。这里研究了一个包含九种主要临床药物的 38 个药物靶标中数百个突变的经过精心整理的数据库，这些突变与耐药性有关。突变分为发生在结合部位本身的突变、发生在与结合部位相互作用的残基中的突变以及发生在外围区域的突变。对野生型和突变型靶蛋白结构模型进行了分析，以寻找降低药物结合的原因。使用结构模型计算了每个靶标中每个残基的 19 个突变的整个阵列的稳定性分析。根据靶蛋白的序列保守性分析计算了单个残基、结合部位和整个蛋白质的保守指数。这些分析导致了关于多肽链中哪些位置更容易获得耐药性突变的见解。因此，可以深入了解突变对药物结合的影响，包括哪些氨基酸位置以及因此哪些相互作用不应过分依赖，这反过来又可以转化为修改现有药物和设计新药的指导方针。该方法可以作为研究其他微生物中的耐药突变体的一般框架。
