Institute of Systems Biology, Shanghai University, Shanghai 200444, China.
BMC Bioinformatics. 2012 May 8;13 Suppl 7(Suppl 7):S7. doi: 10.1186/1471-2105-13-S7-S7.
Drug combination that consists of distinctive agents is an attractive strategy to combat complex diseases and has been widely used clinically with improved therapeutic effects. However, the identification of efficacious drug combinations remains a non-trivial and challenging task due to the huge number of possible combinations among the candidate drugs. As an important factor, the molecular context in which drugs exert their functions can provide crucial insights into the mechanism underlying drug combinations.
In this work, we present a network biology approach to investigate drug combinations and their target proteins in the context of genetic interaction networks and the related human pathways, in order to better understand the underlying rules of effective drug combinations. Our results indicate that combinatorial drugs tend to have a smaller effect radius in the genetic interaction networks, which is an important parameter to describe the therapeutic effect of a drug combination from the network perspective. We also find that drug combinations are more likely to modulate functionally related pathways.
This study confirms that the molecular networks where drug combinations exert their functions can indeed provide important insights into the underlying rules of effective drug combinations. We hope that our findings can help shortcut the expedition of the future discovery of novel drug combinations.
由不同药物组成的药物联合疗法是对抗复杂疾病的一种极具吸引力的策略，已在临床上广泛应用，并取得了改善治疗效果。然而，由于候选药物之间存在大量可能的组合，因此识别有效的药物组合仍然是一项艰巨而具有挑战性的任务。作为一个重要因素，药物发挥作用的分子背景可以为药物组合的潜在机制提供重要的见解。
在这项工作中，我们提出了一种网络生物学方法来研究遗传相互作用网络和相关人类途径背景下的药物组合及其靶蛋白，以更好地理解有效的药物组合的潜在规则。我们的结果表明，组合药物在遗传相互作用网络中倾向于具有较小的效应半径，这是从网络角度描述药物组合治疗效果的一个重要参数。我们还发现，药物组合更有可能调节功能相关的途径。
这项研究证实，药物组合发挥作用的分子网络确实可以为有效的药物组合的潜在规则提供重要的见解。我们希望我们的发现可以帮助加速未来新型药物组合的发现。
