Published online Mar 22, 2016. doi: 10.5498/wjp.v6.i1.66
Peer-review started: August 30, 2015
First decision: December 4, 2015
Revised: February 10, 2016
Accepted: February 23, 2016
Article in press: February 24, 2016
Published online: March 22, 2016
Processing time: 67 Days and 7.3 Hours
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.
Core tip: Pharmacotherapies of mental disorders have to take into account their multifactorial origins. Therefore, combinatorial drug therapies have to be devised targeting multiple molecules in disease networks. Mathematical approaches can aid in learning more about molecular interactions in disease networks and, by in silico simulations, discover dynamic changes in network properties. Targeting important nodes by drugs should be avoided to preserve network integrities. Efforts to find efficient combinations of drugs could be supported by more research into compounds contained in herbal extracts.