Wang Zhong-Yi, Zhu Qiang, Zhang Hong-Yu
National Key Laboratory of Crop Genetic Improvement, Center for Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan 430070, PR China.
Curr Comput Aided Drug Des. 2013 Sep;9(3):412-6. doi: 10.2174/15734099113099990030.
The discovery and use of antibacterials represents a primary success of modern pharmaceutical industry. However, the pace of antibacterial discovery was heavily hindered by a series of technical difficulties and the unfavorable economics in recent years. The past decade has witnessed rapid progresses in omics and systems biology, which provided an unprecedented opportunity to accelerate the discovery of antibacterials. In this article, we first summarize the successful use of metabolic network analysis in antibacterial discovery. Then, we reveal that metabolite concentration serves as a useful criterion for selecting antimicrobial targets. The essential enzymes with low substrate concentrations (< 0.5 mM) are more druggable antibacterial targets. Besides, we find that the solubility of clinically used competitive antibacterials is at least 100 times higher than the concentrations of the competed substrates. By the new-proposed criterion, we not only identify some promising antibacterial targets but also explain some perplexing experimental observations as well.
抗菌药物的发现与应用是现代制药行业的一项主要成就。然而，近年来，一系列技术难题和不利的经济因素严重阻碍了抗菌药物的发现进程。过去十年间，组学和系统生物学取得了飞速发展，为加速抗菌药物的发现提供了前所未有的机遇。在本文中，我们首先总结了代谢网络分析在抗菌药物发现中的成功应用。然后，我们揭示代谢物浓度可作为选择抗菌靶点的有用标准。底物浓度低（<0.5 mM）的必需酶是更具药物开发潜力的抗菌靶点。此外，我们发现临床使用的竞争性抗菌药物的溶解度至少比被竞争底物的浓度高100倍。基于新提出的标准，我们不仅确定了一些有前景的抗菌靶点，还解释了一些令人困惑的实验观察结果。
