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

Thumbnail
2016
2538.pdf (4.161Mb)
Authors
Nikolić, Katarina
Mavridis, Lazaros
Đikić, Teodora
Vučićević, Jelica
Agbaba, Danica
Yelekci, Kemal
Mitchell, John B. O.
Article (Published version)
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Abstract
The diverse cerebral mechanisms implicated in Central Nervous System (CNS) 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 multi-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 ParzenRosenblatt 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. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. Based on all these findings, it is concluded that multipotent ligands targeting AChE/MAO-A/MAO-B and also D-1-R/D-2-R/5-HT2A-R/H-3-R are promising novel drug candidates with improved efficacy and beneficial neuroleptic and procognitive activities in treatment of Alzheimer's and related neurodegenerative diseases. Structural information for drug targets permits docking and virtual screening and exploration of the molecular determinants of binding, hence facilitating the 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.

Source:
Frontiers in Neuroscience, 2016, 10
Publisher:
  • Frontiers Media Sa, Lausanne
Funding / projects:
  • EU COST Action CM 1103

DOI: 10.3389/fnins.2016.00265

ISSN: 1662-453X

PubMed: 27375423

WoS: 000377492500002

Scopus: 2-s2.0-84980369116
[ Google Scholar ]
56
40
URI
https://farfar.pharmacy.bg.ac.rs/handle/123456789/2540
Collections
  • Radovi istraživača / Researchers’ publications
Institution/Community
Pharmacy
TY  - JOUR
AU  - Nikolić, Katarina
AU  - Mavridis, Lazaros
AU  - Đikić, Teodora
AU  - Vučićević, Jelica
AU  - Agbaba, Danica
AU  - Yelekci, Kemal
AU  - Mitchell, John B. O.
PY  - 2016
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/2540
AB  - The diverse cerebral mechanisms implicated in Central Nervous System (CNS) 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 multi-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 ParzenRosenblatt 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. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. Based on all these findings, it is concluded that multipotent ligands targeting AChE/MAO-A/MAO-B and also D-1-R/D-2-R/5-HT2A-R/H-3-R are promising novel drug candidates with improved efficacy and beneficial neuroleptic and procognitive activities in treatment of Alzheimer's and related neurodegenerative diseases. Structural information for drug targets permits docking and virtual screening and exploration of the molecular determinants of binding, hence facilitating the 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.
PB  - Frontiers Media Sa, Lausanne
T2  - Frontiers in Neuroscience
T1  - Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies
VL  - 10
DO  - 10.3389/fnins.2016.00265
ER  - 
@article{
author = "Nikolić, Katarina and Mavridis, Lazaros and Đikić, Teodora and Vučićević, Jelica and Agbaba, Danica and Yelekci, Kemal and Mitchell, John B. O.",
year = "2016",
abstract = "The diverse cerebral mechanisms implicated in Central Nervous System (CNS) 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 multi-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 ParzenRosenblatt 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. Several multi-target ligands were selected for further study, as compounds with possible additional beneficial pharmacological activities. Based on all these findings, it is concluded that multipotent ligands targeting AChE/MAO-A/MAO-B and also D-1-R/D-2-R/5-HT2A-R/H-3-R are promising novel drug candidates with improved efficacy and beneficial neuroleptic and procognitive activities in treatment of Alzheimer's and related neurodegenerative diseases. Structural information for drug targets permits docking and virtual screening and exploration of the molecular determinants of binding, hence facilitating the 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.",
publisher = "Frontiers Media Sa, Lausanne",
journal = "Frontiers in Neuroscience",
title = "Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies",
volume = "10",
doi = "10.3389/fnins.2016.00265"
}
Nikolić, K., Mavridis, L., Đikić, T., Vučićević, J., Agbaba, D., Yelekci, K.,& Mitchell, J. B. O.. (2016). Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies. in Frontiers in Neuroscience
Frontiers Media Sa, Lausanne., 10.
https://doi.org/10.3389/fnins.2016.00265
Nikolić K, Mavridis L, Đikić T, Vučićević J, Agbaba D, Yelekci K, Mitchell JBO. Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies. in Frontiers in Neuroscience. 2016;10.
doi:10.3389/fnins.2016.00265 .
Nikolić, Katarina, Mavridis, Lazaros, Đikić, Teodora, Vučićević, Jelica, Agbaba, Danica, Yelekci, Kemal, Mitchell, John B. O., "Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies" in Frontiers in Neuroscience, 10 (2016),
https://doi.org/10.3389/fnins.2016.00265 . .

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