Peter J Gebicke-Haerter, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, 68159 Mannheim, Germany.
World J Psychiatry. 2016 Mar 22;6(1):66-83. doi: 10.5498/wjp.v6.i1.66.
The multifactorial origin of most chronic disorders of the brain, including schizophrenia, has been well accepted. Consequently, pharmacotherapy would require multi-targeted strategies. This contrasts to the majority of drug therapies used until now, addressing more or less specifically only one target molecule. Nevertheless, quite some searches for multiple molecular targets specific for mental disorders have been undertaken. For example, genome-wide association studies have been conducted to discover new target genes of disease. Unfortunately, these attempts have not fulfilled the great hopes they have started with. Polypharmacology and network pharmacology approaches of drug treatment endeavor to abandon the one-drug one-target thinking. To this end, most approaches set out to investigate network topologies searching for modules, endowed with "important" nodes, such as "hubs" or "bottlenecks", encompassing features of disease networks, and being useful as tentative targets of drug therapies. This kind of research appears to be very promising. However, blocking or inhibiting "important" targets may easily result in destruction of network integrity. Therefore, it is suggested here to study functions of nodes with lower centrality for more subtle impact on network behavior. Targeting multiple nodes with low impact on network integrity by drugs with multiple activities ("dirty drugs") or by several drugs, simultaneously, avoids to disrupt network integrity and may reset deviant dynamics of disease. Natural products typically display multi target functions and therefore could help to identify useful biological targets. Hence, future efforts should consider to combine drug-target networks with target-disease networks using mathematical (graph theoretical) tools, which could help to develop new therapeutic strategies in long-term psychiatric disorders.
大多数脑部慢性疾病(包括精神分裂症)的多因素起源已被广泛接受。因此,药物治疗需要采用多靶点策略。这与迄今为止使用的大多数药物治疗方法形成对比,后者或多或少只针对一个靶标分子。尽管如此,人们还是对寻找针对精神障碍的多个特定分子靶标进行了相当多的研究。例如,已经进行了全基因组关联研究,以发现疾病的新靶标基因。不幸的是,这些尝试并没有实现它们最初带来的巨大期望。药物治疗的多药理学和网络药理学方法试图摒弃一种药物针对一个靶标的思维。为此,大多数方法都致力于研究网络拓扑结构,寻找具有“重要”节点的模块,例如“枢纽”或“瓶颈”,这些节点包含疾病网络的特征,并可用作药物治疗的候选靶点。这种研究方法似乎非常有前途。然而,阻断或抑制“重要”靶标可能很容易导致网络完整性的破坏。因此,这里建议研究具有较低中心性的节点的功能,以对网络行为产生更细微的影响。通过具有多种活性的药物(“脏药”)或同时使用几种药物靶向对网络完整性影响较小的多个节点,可以避免破坏网络完整性,并可能重置疾病的异常动力学。天然产物通常具有多靶点功能,因此可以帮助确定有用的生物学靶标。因此,未来的努力应考虑使用数学(图论)工具将药物靶标网络与靶标疾病网络相结合,这有助于开发长期精神障碍的新治疗策略。