Identification of Natural Compounds against Neurodegenerative Diseases Using In Silico Techniques
The aim of this study was to identify new potentially active compounds for three protein targets, tropomyosin receptor kinase A (TrkA), N-methyl-d-aspartate (NMDA) receptor, and leucine-rich repeat kinase 2 (LRRK2), that are related to various neurodegenerative diseases such as Alzheimer’s...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-07-01
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| Series: | Molecules |
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| Online Access: | http://www.mdpi.com/1420-3049/23/8/1847 |
| _version_ | 1811231788443369472 |
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| author | Larisa Ivanova Mati Karelson Dimitar A. Dobchev |
| author_facet | Larisa Ivanova Mati Karelson Dimitar A. Dobchev |
| author_sort | Larisa Ivanova |
| collection | DOAJ |
| description | The aim of this study was to identify new potentially active compounds for three protein targets, tropomyosin receptor kinase A (TrkA), N-methyl-d-aspartate (NMDA) receptor, and leucine-rich repeat kinase 2 (LRRK2), that are related to various neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and neuropathic pain. We used a combination of machine learning methods including artificial neural networks and advanced multilinear techniques to develop quantitative structure–activity relationship (QSAR) models for all target proteins. The models were applied to screen more than 13,000 natural compounds from a public database to identify active molecules. The best candidate compounds were further confirmed by docking analysis and molecular dynamics simulations using the crystal structures of the proteins. Several compounds with novel scaffolds were predicted that could be used as the basis for development of novel drug inhibitors related to each target. |
| first_indexed | 2024-04-12T10:50:59Z |
| format | Article |
| id | doaj.art-6172f5c60a67482eaf81174299be8e50 |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-04-12T10:50:59Z |
| publishDate | 2018-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-6172f5c60a67482eaf81174299be8e502022-12-22T03:36:14ZengMDPI AGMolecules1420-30492018-07-01238184710.3390/molecules23081847molecules23081847Identification of Natural Compounds against Neurodegenerative Diseases Using In Silico TechniquesLarisa Ivanova0Mati Karelson1Dimitar A. Dobchev2Institute of Chemistry, University of Tartu, Ravila 14a, 50411 Tartu, EstoniaInstitute of Chemistry, University of Tartu, Ravila 14a, 50411 Tartu, EstoniaInstitute of Chemistry, University of Tartu, Ravila 14a, 50411 Tartu, EstoniaThe aim of this study was to identify new potentially active compounds for three protein targets, tropomyosin receptor kinase A (TrkA), N-methyl-d-aspartate (NMDA) receptor, and leucine-rich repeat kinase 2 (LRRK2), that are related to various neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and neuropathic pain. We used a combination of machine learning methods including artificial neural networks and advanced multilinear techniques to develop quantitative structure–activity relationship (QSAR) models for all target proteins. The models were applied to screen more than 13,000 natural compounds from a public database to identify active molecules. The best candidate compounds were further confirmed by docking analysis and molecular dynamics simulations using the crystal structures of the proteins. Several compounds with novel scaffolds were predicted that could be used as the basis for development of novel drug inhibitors related to each target.http://www.mdpi.com/1420-3049/23/8/1847natural compoundsartificial neural networksmolecular dockingTrkANMDALRRK2molecular dynamicsCADD |
| spellingShingle | Larisa Ivanova Mati Karelson Dimitar A. Dobchev Identification of Natural Compounds against Neurodegenerative Diseases Using In Silico Techniques Molecules natural compounds artificial neural networks molecular docking TrkA NMDA LRRK2 molecular dynamics CADD |
| title | Identification of Natural Compounds against Neurodegenerative Diseases Using In Silico Techniques |
| title_full | Identification of Natural Compounds against Neurodegenerative Diseases Using In Silico Techniques |
| title_fullStr | Identification of Natural Compounds against Neurodegenerative Diseases Using In Silico Techniques |
| title_full_unstemmed | Identification of Natural Compounds against Neurodegenerative Diseases Using In Silico Techniques |
| title_short | Identification of Natural Compounds against Neurodegenerative Diseases Using In Silico Techniques |
| title_sort | identification of natural compounds against neurodegenerative diseases using in silico techniques |
| topic | natural compounds artificial neural networks molecular docking TrkA NMDA LRRK2 molecular dynamics CADD |
| url | http://www.mdpi.com/1420-3049/23/8/1847 |
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