De novo prediction of explicit water molecule positions by a novel algorithm within the protein design software MUMBO
Abstract By mediating interatomic interactions, water molecules play a major role in protein–protein, protein–DNA and protein–ligand interfaces, significantly affecting affinity and specificity. This notwithstanding, explicit water molecules are usually not considered in protein design software beca...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-10-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-43659-w |
| _version_ | 1797453055191416832 |
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| author | Mark Kriegel Yves A. Muller |
| author_facet | Mark Kriegel Yves A. Muller |
| author_sort | Mark Kriegel |
| collection | DOAJ |
| description | Abstract By mediating interatomic interactions, water molecules play a major role in protein–protein, protein–DNA and protein–ligand interfaces, significantly affecting affinity and specificity. This notwithstanding, explicit water molecules are usually not considered in protein design software because of high computational costs. To challenge this situation, we analyzed the binding characteristics of 60,000 waters from high resolution crystal structures and used the observed parameters to implement the prediction of water molecules in the protein design and side chain-packing software MUMBO. To reduce the complexity of the problem, we incorporated water molecules through the solvation of rotamer pairs instead of relying on solvated rotamer libraries. Our validation demonstrates the potential of our algorithm by achieving recovery rates of 67% for bridging water molecules and up to 86% for fully coordinated waters. The efficacy of our algorithm is highlighted further by the prediction of 3 different proteinligand complexes. Here, 91% of water-mediated interactions between protein and ligand are correctly predicted. These results suggest that the new algorithm could prove highly beneficial for structure-based protein design, particularly for the optimization of ligand-binding pockets or protein–protein interfaces. |
| first_indexed | 2024-03-09T15:17:24Z |
| format | Article |
| id | doaj.art-403b5606d9794305a3ad887b9c87b35c |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-09T15:17:24Z |
| publishDate | 2023-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-403b5606d9794305a3ad887b9c87b35c2023-11-26T12:59:38ZengNature PortfolioScientific Reports2045-23222023-10-0113111410.1038/s41598-023-43659-wDe novo prediction of explicit water molecule positions by a novel algorithm within the protein design software MUMBOMark Kriegel0Yves A. Muller1Division of Biotechnology, Department of Biology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)Division of Biotechnology, Department of Biology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)Abstract By mediating interatomic interactions, water molecules play a major role in protein–protein, protein–DNA and protein–ligand interfaces, significantly affecting affinity and specificity. This notwithstanding, explicit water molecules are usually not considered in protein design software because of high computational costs. To challenge this situation, we analyzed the binding characteristics of 60,000 waters from high resolution crystal structures and used the observed parameters to implement the prediction of water molecules in the protein design and side chain-packing software MUMBO. To reduce the complexity of the problem, we incorporated water molecules through the solvation of rotamer pairs instead of relying on solvated rotamer libraries. Our validation demonstrates the potential of our algorithm by achieving recovery rates of 67% for bridging water molecules and up to 86% for fully coordinated waters. The efficacy of our algorithm is highlighted further by the prediction of 3 different proteinligand complexes. Here, 91% of water-mediated interactions between protein and ligand are correctly predicted. These results suggest that the new algorithm could prove highly beneficial for structure-based protein design, particularly for the optimization of ligand-binding pockets or protein–protein interfaces.https://doi.org/10.1038/s41598-023-43659-w |
| spellingShingle | Mark Kriegel Yves A. Muller De novo prediction of explicit water molecule positions by a novel algorithm within the protein design software MUMBO Scientific Reports |
| title | De novo prediction of explicit water molecule positions by a novel algorithm within the protein design software MUMBO |
| title_full | De novo prediction of explicit water molecule positions by a novel algorithm within the protein design software MUMBO |
| title_fullStr | De novo prediction of explicit water molecule positions by a novel algorithm within the protein design software MUMBO |
| title_full_unstemmed | De novo prediction of explicit water molecule positions by a novel algorithm within the protein design software MUMBO |
| title_short | De novo prediction of explicit water molecule positions by a novel algorithm within the protein design software MUMBO |
| title_sort | de novo prediction of explicit water molecule positions by a novel algorithm within the protein design software mumbo |
| url | https://doi.org/10.1038/s41598-023-43659-w |
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