dc.contributor.author | Raevsky O.A. | |
dc.contributor.author | Mukhametov A. | |
dc.contributor.author | Grigorev V.Y. | |
dc.contributor.author | Ustyugov A. | |
dc.contributor.author | Tsay S.-C. | |
dc.contributor.author | Hwu R.J.-R. | |
dc.contributor.author | Yarla N.S. | |
dc.contributor.author | Barreto G.E. | |
dc.contributor.author | Aliev G. | |
dc.contributor.author | Bachurin S.O. | |
dc.date.accessioned | 2020-09-02T22:26:30Z | |
dc.date.available | 2020-09-02T22:26:30Z | |
dc.date.issued | 2018 | |
dc.identifier | 10.2174/0929867324666170920154111 | |
dc.identifier.citation | 25, 39, 5293-5314 | |
dc.identifier.issn | 09298673 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12728/5939 | |
dc.description | The discovery of drugs for diseases of the central nervous system (CNS) faces high attrition rates in clinical trials. Neural diseases are extremely complex in nature and typically associated with multiple drug targets. A conception of multi-target directed ligands (MTDL), widely applied to the discovery of cancer pharmaceuticals, may be a perspective solution for CNS diseases. Special bioinformatics approaches have been developed which can assist the medicinal chemists in identification and structural optimization of MTDL. In this review, we analyze the current status of the development of multi-target approaches in quantitative structure-activity relationships (mt-QSAR) for CNS drug discovery; and describes applications of multi-target approaches in molecular modelling (which can be called mt-MM), as well as perspectives for multi-target approaches in bioinformatics in relation to Alzheimer’s disease. © 2018 Bentham Science Publishers. | |
dc.language.iso | en | |
dc.publisher | Bentham Science Publishers B.V. | |
dc.subject | Alzheimer’s disease | |
dc.subject | Bioinformatics | |
dc.subject | Cheminformatics | |
dc.subject | Molecular modelling | |
dc.subject | MTDL | |
dc.subject | Multi-target | |
dc.subject | QSAR | |
dc.subject | central nervous system agents | |
dc.subject | ligand | |
dc.subject | central nervous system agents | |
dc.subject | algorithm | |
dc.subject | Alzheimer disease | |
dc.subject | bioinformatics | |
dc.subject | computer aided design | |
dc.subject | drug design | |
dc.subject | drug targeting | |
dc.subject | human | |
dc.subject | methodology | |
dc.subject | molecular docking | |
dc.subject | molecular model | |
dc.subject | nonhuman | |
dc.subject | process optimization | |
dc.subject | quantitative structure activity relation | |
dc.subject | Review | |
dc.subject | Alzheimer disease | |
dc.subject | biology | |
dc.subject | central nervous system disease | |
dc.subject | chemistry | |
dc.subject | pathology | |
dc.subject | Alzheimer Disease | |
dc.subject | Central Nervous System Agents | |
dc.subject | Central Nervous System Diseases | |
dc.subject | Computational Biology | |
dc.subject | Drug Design | |
dc.subject | Humans | |
dc.subject | Ligands | |
dc.subject | Models, Molecular | |
dc.subject | Quantitative Structure-Activity Relationship | |
dc.title | Applications of multi-target computer-aided methodologies in molecular design of CNS drugs | |
dc.type | Review | |