AUTHOR=Nikolic Katarina , Mavridis Lazaros , Djikic Teodora , Vucicevic Jelica , Agbaba Danica , Yelekci Kemal , Mitchell John B. O. 

TITLE=Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 10 - 2016

YEAR=2016

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2016.00265

DOI=10.3389/fnins.2016.00265

ISSN=1662-453X

ABSTRACT=The diverse cerebral mechanisms implicated in CNS (Central Nervous System) diseases together with the heterogeneous and overlapping nature of phenotypes indicated that multitarget strategies may be appropriate for the improved treatment of complex brain diseases. Understanding how the neurotransmitter systems interact is also important in optimizing therapeutic strategies. Pharmacological intervention on one target will often influence another one, such as the well-established serotonin-dopamine interaction or the dopamine-glutamate interaction. It is now accepted that drug action can involve plural targets and that polypharmacological interaction with multiple targets, to address disease in more subtle and effective ways, is a key concept for development of novel drug candidates against complex CNS diseases. A Mmulti-target therapeutic strategy for Alzheimer`s disease resulted in the development of very effective Multi-Target Designed Ligands (MTDL) that act on both the cholinergic and monoaminergic systems, and also retard the progression of neurodegeneration by inhibiting amyloid aggregation. Many compounds already in databases have been investigated as ligands for multiple targets in drug-discovery programs. A probabilistic method, the Parzen-Rosenblatt Window approach, was used to build a “predictor” model using data collected from the ChEMBL database. The model can be used to predict both the primary pharmaceutical target and off-targets of a compound based on its structure. TMining this information data could can provide experimental informationbe very useful for building pharmacophores and developing 3D-QSAR models for activity evaluation at the selected targets. 
Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. Based on all these findings, it is assumed concluded that multipotent ligands targeting AChE/MAO-A/MAO-B and also D1-R/D2-R/5-HT2aHT2A-R/H3-R are promising novel drug candidates with improved efficacy and withand safety beneficial neuroleptic and procognitive activities in treatment of Alzheimer’s and related neurodegenerative diseases. 
Structural information for drug targets permits virtual docking and virtual screening investigations and exploration of the molecular determinants of binding, hence to facilitateing drugthe design of multi-targeted drugs. The crystal structures and models of enzymes of the monoaminergic and cholinergic systems have been used to investigate the structural origins of target selectivity and to identify molecular determinants, in order to design MTDLs.