Nacher Jose C, Schwartz Jean-Marc
Department of Complex Systems, Future University-Hakodate, Hokkaido 041-8655, Japan.
BMC Pharmacol. 2008 Mar 4;8:5. doi: 10.1186/1471-2210-8-5.
Network science is already making an impact on the study of complex systems and offers a promising variety of tools to understand their formation and evolution in many disparate fields from technological networks to biological systems. Even though new high-throughput technologies have rapidly been generating large amounts of genomic data, drug design has not followed the same development, and it is still complicated and expensive to develop new single-target drugs. Nevertheless, recent approaches suggest that multi-target drug design combined with a network-dependent approach and large-scale systems-oriented strategies create a promising framework to combat complex multi-genetic disorders like cancer or diabetes.
We here investigate the human network corresponding to the interactions between all US approved drugs and human therapies, defined by known relationships between drugs and their therapeutic applications. Our results show that the average paths in this drug-therapy network are shorter than three steps, indicating that distant therapies are separated by a surprisingly low number of chemical compounds. We also identify a sub-network composed by drugs with high centrality measures in the drug-therapy network, which represent the structural backbone of this system and act as hubs routing information between distant parts of the network.
These findings provide for the first time a global map of the large-scale organization of all known drugs and associated therapies, bringing new insights on possible strategies for future drug development. Special attention should be given to drugs which combine the two properties of (a) having a high centrality value in the drug-therapy network and (b) acting on multiple molecular targets in the human system.
网络科学已对复杂系统的研究产生影响，并提供了一系列有前景的工具，以理解从技术网络到生物系统等许多不同领域中复杂系统的形成和演化。尽管新的高通量技术已迅速产生大量基因组数据，但药物设计却未跟上同样的发展步伐，开发新的单靶点药物仍然复杂且昂贵。然而，最近的方法表明，多靶点药物设计结合网络依赖方法和大规模系统导向策略，为对抗癌症或糖尿病等复杂多基因疾病创造了一个有前景的框架。
我们在此研究了与所有美国批准药物和人类疗法之间相互作用相对应的人类网络，该网络由药物与其治疗应用之间的已知关系定义。我们的结果表明，该药物 - 治疗网络中的平均路径长度短于三步，这表明距离较远的疗法之间仅由数量惊人少的化合物分隔。我们还识别出一个由药物治疗网络中具有高中心性度量的药物组成的子网，这些药物代表了该系统的结构主干，并充当在网络遥远部分之间传递信息的枢纽。
这些发现首次提供了所有已知药物和相关疗法大规模组织的全局图谱，为未来药物开发的可能策略带来了新见解。应特别关注兼具以下两个特性的药物：（a）在药物 - 治疗网络中具有高中心性值；（b）作用于人类系统中的多个分子靶点。
