Opportunities and Challenges for In Silico Drug Discovery at Delta Opioid Receptors
The delta opioid receptor is a Gi-protein-coupled receptor (GPCR) with a broad expression pattern both in the central nervous system and the body. The receptor has been investigated as a potential target for a multitude of significant diseases including migraine, alcohol use disorder, ischemia, and...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Pharmaceuticals |
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| Online Access: | https://www.mdpi.com/1424-8247/15/7/873 |
| _version_ | 1827604644847681536 |
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| author | Yazan J. Meqbil Richard M. van Rijn |
| author_facet | Yazan J. Meqbil Richard M. van Rijn |
| author_sort | Yazan J. Meqbil |
| collection | DOAJ |
| description | The delta opioid receptor is a Gi-protein-coupled receptor (GPCR) with a broad expression pattern both in the central nervous system and the body. The receptor has been investigated as a potential target for a multitude of significant diseases including migraine, alcohol use disorder, ischemia, and neurodegenerative diseases. Despite multiple attempts, delta opioid receptor-selective molecules have not been translated into the clinic. Yet, the therapeutic promise of the delta opioid receptor remains and thus there is a need to identify novel delta opioid receptor ligands to be optimized and selected for clinical trials. Here, we highlight recent developments involving the delta opioid receptor, the closely related mu and kappa opioid receptors, and in the broader area of the GPCR drug discovery research. We focus on the validity and utility of the available delta opioid receptor structures. We also discuss the increased ability to perform ultra-large-scale docking studies on GPCRs, the rise in high-resolution cryo-EM structures, and the increased prevalence of machine learning and artificial intelligence in drug discovery. Overall, we pose that there are multiple opportunities to enable in silico drug discovery at the delta opioid receptor to identify novel delta opioid modulators potentially with unique pharmacological properties, such as biased signaling. |
| first_indexed | 2024-03-09T06:04:01Z |
| format | Article |
| id | doaj.art-25a70c9ce2f242af91ec9b40af684843 |
| institution | Directory Open Access Journal |
| issn | 1424-8247 |
| language | English |
| last_indexed | 2024-03-09T06:04:01Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Pharmaceuticals |
| spelling | doaj.art-25a70c9ce2f242af91ec9b40af6848432023-12-03T12:05:44ZengMDPI AGPharmaceuticals1424-82472022-07-0115787310.3390/ph15070873Opportunities and Challenges for In Silico Drug Discovery at Delta Opioid ReceptorsYazan J. Meqbil0Richard M. van Rijn1Department of Medicinal Chemistry and Molecular Pharmacology, Computational Interdisciplinary Graduate Program, Purdue University, West Lafayette, IN 47907, USADepartment of Medicinal Chemistry and Molecular Pharmacology, Purdue Institute for Drug Discovery, Purdue Institute for Neuroscience, Purdue University, West Lafayette, IN 47907, USAThe delta opioid receptor is a Gi-protein-coupled receptor (GPCR) with a broad expression pattern both in the central nervous system and the body. The receptor has been investigated as a potential target for a multitude of significant diseases including migraine, alcohol use disorder, ischemia, and neurodegenerative diseases. Despite multiple attempts, delta opioid receptor-selective molecules have not been translated into the clinic. Yet, the therapeutic promise of the delta opioid receptor remains and thus there is a need to identify novel delta opioid receptor ligands to be optimized and selected for clinical trials. Here, we highlight recent developments involving the delta opioid receptor, the closely related mu and kappa opioid receptors, and in the broader area of the GPCR drug discovery research. We focus on the validity and utility of the available delta opioid receptor structures. We also discuss the increased ability to perform ultra-large-scale docking studies on GPCRs, the rise in high-resolution cryo-EM structures, and the increased prevalence of machine learning and artificial intelligence in drug discovery. Overall, we pose that there are multiple opportunities to enable in silico drug discovery at the delta opioid receptor to identify novel delta opioid modulators potentially with unique pharmacological properties, such as biased signaling.https://www.mdpi.com/1424-8247/15/7/873mutagenesisartificial intelligencecomputer-aided drug designmolecular dynamic simulationbiased signalingG protein-coupled receptor |
| spellingShingle | Yazan J. Meqbil Richard M. van Rijn Opportunities and Challenges for In Silico Drug Discovery at Delta Opioid Receptors Pharmaceuticals mutagenesis artificial intelligence computer-aided drug design molecular dynamic simulation biased signaling G protein-coupled receptor |
| title | Opportunities and Challenges for In Silico Drug Discovery at Delta Opioid Receptors |
| title_full | Opportunities and Challenges for In Silico Drug Discovery at Delta Opioid Receptors |
| title_fullStr | Opportunities and Challenges for In Silico Drug Discovery at Delta Opioid Receptors |
| title_full_unstemmed | Opportunities and Challenges for In Silico Drug Discovery at Delta Opioid Receptors |
| title_short | Opportunities and Challenges for In Silico Drug Discovery at Delta Opioid Receptors |
| title_sort | opportunities and challenges for in silico drug discovery at delta opioid receptors |
| topic | mutagenesis artificial intelligence computer-aided drug design molecular dynamic simulation biased signaling G protein-coupled receptor |
| url | https://www.mdpi.com/1424-8247/15/7/873 |
| work_keys_str_mv | AT yazanjmeqbil opportunitiesandchallengesforinsilicodrugdiscoveryatdeltaopioidreceptors AT richardmvanrijn opportunitiesandchallengesforinsilicodrugdiscoveryatdeltaopioidreceptors |