Applications and Potential of In Silico Approaches for Psychedelic Chemistry
Molecular-level investigations of the Central Nervous System have been revolutionized by the development of computational methods, computing power, and capacity advances. These techniques have enabled researchers to analyze large amounts of data from various sources, including genomics, in vivo, and...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-08-01
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| Series: | Molecules |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1420-3049/28/16/5966 |
| _version_ | 1797583701581758464 |
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| author | Sedat Karabulut Harpreet Kaur James W. Gauld |
| author_facet | Sedat Karabulut Harpreet Kaur James W. Gauld |
| author_sort | Sedat Karabulut |
| collection | DOAJ |
| description | Molecular-level investigations of the Central Nervous System have been revolutionized by the development of computational methods, computing power, and capacity advances. These techniques have enabled researchers to analyze large amounts of data from various sources, including genomics, in vivo, and in vitro drug tests. In this review, we explore how computational methods and informatics have contributed to our understanding of mental health disorders and the development of novel drugs for neurological diseases, with a special focus on the emerging field of psychedelics. In addition, the use of state-of-the-art computational methods to predict the potential of drug compounds and bioinformatic tools to integrate disparate data sources to create predictive models is also discussed. Furthermore, the challenges associated with these methods, such as the need for large datasets and the diversity of in vitro data, are explored. Overall, this review highlights the immense potential of computational methods and informatics in Central Nervous System research and underscores the need for continued development and refinement of these techniques and more inclusion of Quantitative Structure-Activity Relationships (QSARs). |
| first_indexed | 2024-03-10T23:41:33Z |
| format | Article |
| id | doaj.art-7f278a36bcc64e8bb504a76c1b17d6fe |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-03-10T23:41:33Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-7f278a36bcc64e8bb504a76c1b17d6fe2023-11-19T02:22:35ZengMDPI AGMolecules1420-30492023-08-012816596610.3390/molecules28165966Applications and Potential of In Silico Approaches for Psychedelic ChemistrySedat Karabulut0Harpreet Kaur1James W. Gauld2Department of Chemistry and Biochemistry, University of Windsor, Windsor, ON N9B 3P4, CanadaPharmala Biotech, 82 Richmond Street E, Toronto, ON M5C 1P1, CanadaDepartment of Chemistry and Biochemistry, University of Windsor, Windsor, ON N9B 3P4, CanadaMolecular-level investigations of the Central Nervous System have been revolutionized by the development of computational methods, computing power, and capacity advances. These techniques have enabled researchers to analyze large amounts of data from various sources, including genomics, in vivo, and in vitro drug tests. In this review, we explore how computational methods and informatics have contributed to our understanding of mental health disorders and the development of novel drugs for neurological diseases, with a special focus on the emerging field of psychedelics. In addition, the use of state-of-the-art computational methods to predict the potential of drug compounds and bioinformatic tools to integrate disparate data sources to create predictive models is also discussed. Furthermore, the challenges associated with these methods, such as the need for large datasets and the diversity of in vitro data, are explored. Overall, this review highlights the immense potential of computational methods and informatics in Central Nervous System research and underscores the need for continued development and refinement of these techniques and more inclusion of Quantitative Structure-Activity Relationships (QSARs).https://www.mdpi.com/1420-3049/28/16/5966Central Nervous Systemcomputational modelingin silicoserotonindopamineMDMA |
| spellingShingle | Sedat Karabulut Harpreet Kaur James W. Gauld Applications and Potential of In Silico Approaches for Psychedelic Chemistry Molecules Central Nervous System computational modeling in silico serotonin dopamine MDMA |
| title | Applications and Potential of In Silico Approaches for Psychedelic Chemistry |
| title_full | Applications and Potential of In Silico Approaches for Psychedelic Chemistry |
| title_fullStr | Applications and Potential of In Silico Approaches for Psychedelic Chemistry |
| title_full_unstemmed | Applications and Potential of In Silico Approaches for Psychedelic Chemistry |
| title_short | Applications and Potential of In Silico Approaches for Psychedelic Chemistry |
| title_sort | applications and potential of in silico approaches for psychedelic chemistry |
| topic | Central Nervous System computational modeling in silico serotonin dopamine MDMA |
| url | https://www.mdpi.com/1420-3049/28/16/5966 |
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