In silico Druggability Assessment of the NUDIX Hydrolase Protein Family as a Workflow for Target Prioritization
Computational chemistry has now been widely accepted as a useful tool for shortening lead times in early drug discovery. When selecting new potential drug targets, it is important to assess the likelihood of finding suitable starting points for lead generation before pursuing costly high-throughput...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-05-01
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| Series: | Frontiers in Chemistry |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fchem.2020.00443/full |
| _version_ | 1828383124118044672 |
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| author | Maurice Michel Evert J. Homan Elisée Wiita Kia Pedersen Ingrid Almlöf Anna-Lena Gustavsson Thomas Lundbäck Thomas Lundbäck Thomas Helleday Thomas Helleday Ulrika Warpman Berglund |
| author_facet | Maurice Michel Evert J. Homan Elisée Wiita Kia Pedersen Ingrid Almlöf Anna-Lena Gustavsson Thomas Lundbäck Thomas Lundbäck Thomas Helleday Thomas Helleday Ulrika Warpman Berglund |
| author_sort | Maurice Michel |
| collection | DOAJ |
| description | Computational chemistry has now been widely accepted as a useful tool for shortening lead times in early drug discovery. When selecting new potential drug targets, it is important to assess the likelihood of finding suitable starting points for lead generation before pursuing costly high-throughput screening campaigns. By exploiting available high-resolution crystal structures, an in silico druggability assessment can facilitate the decision of whether, and in cases where several protein family members exist, which of these to pursue experimentally. Many of the algorithms and software suites commonly applied for in silico druggability assessment are complex, technically challenging and not always user-friendly. Here we applied the intuitive open access servers of DoGSite, FTMap and CryptoSite to comprehensively predict ligand binding pockets, druggability scores and conformationally active regions of the NUDIX protein family. In parallel we analyzed potential ligand binding sites, their druggability and pocket parameter using Schrödinger's SiteMap. Then an in silico docking cascade of a subset of the ZINC FragNow library using the Glide docking program was performed to assess identified pockets for large-scale small-molecule binding. Subsequently, this initial dual ranking of druggable sites within the NUDIX protein family was benchmarked against experimental hit rates obtained both in-house and by others from traditional biochemical and fragment screening campaigns. The observed correlation suggests that the presented user-friendly workflow of a dual parallel in silico druggability assessment is applicable as a standalone method for decision on target prioritization and exclusion in future screening campaigns. |
| first_indexed | 2024-12-10T04:44:24Z |
| format | Article |
| id | doaj.art-abfd3227d10e4dbfb17b5970d14a429d |
| institution | Directory Open Access Journal |
| issn | 2296-2646 |
| language | English |
| last_indexed | 2024-12-10T04:44:24Z |
| publishDate | 2020-05-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Chemistry |
| spelling | doaj.art-abfd3227d10e4dbfb17b5970d14a429d2022-12-22T02:01:48ZengFrontiers Media S.A.Frontiers in Chemistry2296-26462020-05-01810.3389/fchem.2020.00443506842In silico Druggability Assessment of the NUDIX Hydrolase Protein Family as a Workflow for Target PrioritizationMaurice Michel0Evert J. Homan1Elisée Wiita2Kia Pedersen3Ingrid Almlöf4Anna-Lena Gustavsson5Thomas Lundbäck6Thomas Lundbäck7Thomas Helleday8Thomas Helleday9Ulrika Warpman Berglund10Science for Life Laboratory, Department of Oncology-Pathology, Karolinska Institutet, Stockholm, SwedenScience for Life Laboratory, Department of Oncology-Pathology, Karolinska Institutet, Stockholm, SwedenScience for Life Laboratory, Department of Oncology-Pathology, Karolinska Institutet, Stockholm, SwedenScience for Life Laboratory, Department of Oncology-Pathology, Karolinska Institutet, Stockholm, SwedenScience for Life Laboratory, Department of Oncology-Pathology, Karolinska Institutet, Stockholm, SwedenChemical Biology Consortium Sweden (CBCS), Science for Life Laboratory, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, SwedenChemical Biology Consortium Sweden (CBCS), Science for Life Laboratory, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, SwedenMechanistic Biology and Profiling, Discovery Sciences, R&D, AstraZeneca, Gothenburg, SwedenScience for Life Laboratory, Department of Oncology-Pathology, Karolinska Institutet, Stockholm, SwedenDepartment of Oncology and Metabolism, Sheffield Cancer Centre, University of Sheffield, Sheffield, United KingdomScience for Life Laboratory, Department of Oncology-Pathology, Karolinska Institutet, Stockholm, SwedenComputational chemistry has now been widely accepted as a useful tool for shortening lead times in early drug discovery. When selecting new potential drug targets, it is important to assess the likelihood of finding suitable starting points for lead generation before pursuing costly high-throughput screening campaigns. By exploiting available high-resolution crystal structures, an in silico druggability assessment can facilitate the decision of whether, and in cases where several protein family members exist, which of these to pursue experimentally. Many of the algorithms and software suites commonly applied for in silico druggability assessment are complex, technically challenging and not always user-friendly. Here we applied the intuitive open access servers of DoGSite, FTMap and CryptoSite to comprehensively predict ligand binding pockets, druggability scores and conformationally active regions of the NUDIX protein family. In parallel we analyzed potential ligand binding sites, their druggability and pocket parameter using Schrödinger's SiteMap. Then an in silico docking cascade of a subset of the ZINC FragNow library using the Glide docking program was performed to assess identified pockets for large-scale small-molecule binding. Subsequently, this initial dual ranking of druggable sites within the NUDIX protein family was benchmarked against experimental hit rates obtained both in-house and by others from traditional biochemical and fragment screening campaigns. The observed correlation suggests that the presented user-friendly workflow of a dual parallel in silico druggability assessment is applicable as a standalone method for decision on target prioritization and exclusion in future screening campaigns.https://www.frontiersin.org/article/10.3389/fchem.2020.00443/fulldruggabilitynudixdrug discoveryworkflowmalachite green |
| spellingShingle | Maurice Michel Evert J. Homan Elisée Wiita Kia Pedersen Ingrid Almlöf Anna-Lena Gustavsson Thomas Lundbäck Thomas Lundbäck Thomas Helleday Thomas Helleday Ulrika Warpman Berglund In silico Druggability Assessment of the NUDIX Hydrolase Protein Family as a Workflow for Target Prioritization Frontiers in Chemistry druggability nudix drug discovery workflow malachite green |
| title | In silico Druggability Assessment of the NUDIX Hydrolase Protein Family as a Workflow for Target Prioritization |
| title_full | In silico Druggability Assessment of the NUDIX Hydrolase Protein Family as a Workflow for Target Prioritization |
| title_fullStr | In silico Druggability Assessment of the NUDIX Hydrolase Protein Family as a Workflow for Target Prioritization |
| title_full_unstemmed | In silico Druggability Assessment of the NUDIX Hydrolase Protein Family as a Workflow for Target Prioritization |
| title_short | In silico Druggability Assessment of the NUDIX Hydrolase Protein Family as a Workflow for Target Prioritization |
| title_sort | in silico druggability assessment of the nudix hydrolase protein family as a workflow for target prioritization |
| topic | druggability nudix drug discovery workflow malachite green |
| url | https://www.frontiersin.org/article/10.3389/fchem.2020.00443/full |
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