Greedy 3-Point Search (G3PS)—A Novel Algorithm for Pharmacophore Alignment
Chemical features of small molecules can be abstracted to 3D pharmacophore models, which are easy to generate, interpret, and adapt by medicinal chemists. Three-dimensional pharmacophores can be used to efficiently match and align molecules according to their chemical feature pattern, which facilita...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Molecules |
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| Online Access: | https://www.mdpi.com/1420-3049/26/23/7201 |
| _version_ | 1827674803269533696 |
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| author | Christian Permann Thomas Seidel Thierry Langer |
| author_facet | Christian Permann Thomas Seidel Thierry Langer |
| author_sort | Christian Permann |
| collection | DOAJ |
| description | Chemical features of small molecules can be abstracted to 3D pharmacophore models, which are easy to generate, interpret, and adapt by medicinal chemists. Three-dimensional pharmacophores can be used to efficiently match and align molecules according to their chemical feature pattern, which facilitates the virtual screening of even large compound databases. Existing alignment methods, used in computational drug discovery and bio-activity prediction, are often not suitable for finding matches between pharmacophores accurately as they purely aim to minimize RMSD or maximize volume overlap, when the actual goal is to match as many features as possible within the positional tolerances of the pharmacophore features. As a consequence, the obtained alignment results are often suboptimal in terms of the number of geometrically matched feature pairs, which increases the false-negative rate, thus negatively affecting the outcome of virtual screening experiments. We addressed this issue by introducing a new alignment algorithm, Greedy 3-Point Search (G3PS), which aims at finding optimal alignments by using a matching-feature-pair maximizing search strategy while at the same time being faster than competing methods. |
| first_indexed | 2024-03-10T04:48:22Z |
| format | Article |
| id | doaj.art-6d8c1b4139f74df999f102d7cf2a6a95 |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-03-10T04:48:22Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-6d8c1b4139f74df999f102d7cf2a6a952023-11-23T02:48:53ZengMDPI AGMolecules1420-30492021-11-012623720110.3390/molecules26237201Greedy 3-Point Search (G3PS)—A Novel Algorithm for Pharmacophore AlignmentChristian Permann0Thomas Seidel1Thierry Langer2Department of Pharmaceutical Sciences, University of Vienna, Althanstrasse 14, 1090 Vienna, AustriaDepartment of Pharmaceutical Sciences, University of Vienna, Althanstrasse 14, 1090 Vienna, AustriaDepartment of Pharmaceutical Sciences, University of Vienna, Althanstrasse 14, 1090 Vienna, AustriaChemical features of small molecules can be abstracted to 3D pharmacophore models, which are easy to generate, interpret, and adapt by medicinal chemists. Three-dimensional pharmacophores can be used to efficiently match and align molecules according to their chemical feature pattern, which facilitates the virtual screening of even large compound databases. Existing alignment methods, used in computational drug discovery and bio-activity prediction, are often not suitable for finding matches between pharmacophores accurately as they purely aim to minimize RMSD or maximize volume overlap, when the actual goal is to match as many features as possible within the positional tolerances of the pharmacophore features. As a consequence, the obtained alignment results are often suboptimal in terms of the number of geometrically matched feature pairs, which increases the false-negative rate, thus negatively affecting the outcome of virtual screening experiments. We addressed this issue by introducing a new alignment algorithm, Greedy 3-Point Search (G3PS), which aims at finding optimal alignments by using a matching-feature-pair maximizing search strategy while at the same time being faster than competing methods.https://www.mdpi.com/1420-3049/26/23/7201pharmacophore alignmentpharmacophore modellingvirtual screeninggreedy algorithmdrug design |
| spellingShingle | Christian Permann Thomas Seidel Thierry Langer Greedy 3-Point Search (G3PS)—A Novel Algorithm for Pharmacophore Alignment Molecules pharmacophore alignment pharmacophore modelling virtual screening greedy algorithm drug design |
| title | Greedy 3-Point Search (G3PS)—A Novel Algorithm for Pharmacophore Alignment |
| title_full | Greedy 3-Point Search (G3PS)—A Novel Algorithm for Pharmacophore Alignment |
| title_fullStr | Greedy 3-Point Search (G3PS)—A Novel Algorithm for Pharmacophore Alignment |
| title_full_unstemmed | Greedy 3-Point Search (G3PS)—A Novel Algorithm for Pharmacophore Alignment |
| title_short | Greedy 3-Point Search (G3PS)—A Novel Algorithm for Pharmacophore Alignment |
| title_sort | greedy 3 point search g3ps a novel algorithm for pharmacophore alignment |
| topic | pharmacophore alignment pharmacophore modelling virtual screening greedy algorithm drug design |
| url | https://www.mdpi.com/1420-3049/26/23/7201 |
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