In Silico Peptide Ligation: Iterative Residue Docking and Linking as a New Approach to Predict Protein-Peptide Interactions
Peptide–protein interactions are corner-stones of living functions involved in essential mechanisms, such as cell signaling. Given the difficulty of obtaining direct experimental structural biology data, prediction of those interactions is of crucial interest for the rational development o...
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-04-01
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| Series: | Molecules |
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| Online Access: | https://www.mdpi.com/1420-3049/24/7/1351 |
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| author | Julien Diharce Mickaël Cueto Massimiliano Beltramo Vincent Aucagne Pascal Bonnet |
| author_facet | Julien Diharce Mickaël Cueto Massimiliano Beltramo Vincent Aucagne Pascal Bonnet |
| author_sort | Julien Diharce |
| collection | DOAJ |
| description | Peptide–protein interactions are corner-stones of living functions involved in essential mechanisms, such as cell signaling. Given the difficulty of obtaining direct experimental structural biology data, prediction of those interactions is of crucial interest for the rational development of new drugs, notably to fight diseases, such as cancer or Alzheimer’s disease. Because of the high flexibility of natural unconstrained linear peptides, prediction of their binding mode in a protein cavity remains challenging. Several theoretical approaches have been developed in the last decade to address this issue. Nevertheless, improvements are needed, such as the conformation prediction of peptide side-chains, which are dependent on peptide length and flexibility. Here, we present a novel in silico method, Iterative Residue Docking and Linking (IRDL), to efficiently predict peptide–protein interactions. In order to reduce the conformational space, this innovative method splits peptides into several short segments. Then, it uses the performance of intramolecular covalent docking to rebuild, sequentially, the complete peptide in the active site of its protein target. Once the peptide is constructed, a rescoring step is applied in order to correctly rank all IRDL solutions. Applied on a set of 11 crystallized peptide–protein complexes, the IRDL method shows promising results, since it is able to retrieve experimental binding conformations with a Root Mean Square Deviation (RMSD) below 2 Å in the top five ranked solutions. For some complexes, IRDL method outperforms two other docking protocols evaluated in this study. Hence, IRDL is a new tool that could be used in drug design projects to predict peptide–protein interactions. |
| first_indexed | 2024-12-22T09:42:51Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-12-22T09:42:51Z |
| publishDate | 2019-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-db5e8d951bde4d04a54b19fa9da607d22022-12-21T18:30:37ZengMDPI AGMolecules1420-30492019-04-01247135110.3390/molecules24071351molecules24071351In Silico Peptide Ligation: Iterative Residue Docking and Linking as a New Approach to Predict Protein-Peptide InteractionsJulien Diharce0Mickaël Cueto1Massimiliano Beltramo2Vincent Aucagne3Pascal Bonnet4Institut de Chimie Organique et Analytique (ICOA), UMR CNRS-Université d’Orléans 7311, Université d’Orléans BP 6759, 45067 Orléans Cedex 2, FranceInstitut de Chimie Organique et Analytique (ICOA), UMR CNRS-Université d’Orléans 7311, Université d’Orléans BP 6759, 45067 Orléans Cedex 2, FranceUMR Physiologie de la Reproduction et des Comportements (INRA, UMR85; CNRS, UMR7247; Université de Tours; IFCE), F-37380 Nouzilly, FranceCentre de Biophysique Moléculaire (CNRS UPR4301), Rue Charles Sadron, F-45071 Orléans Cedex 2, FranceInstitut de Chimie Organique et Analytique (ICOA), UMR CNRS-Université d’Orléans 7311, Université d’Orléans BP 6759, 45067 Orléans Cedex 2, FrancePeptide–protein interactions are corner-stones of living functions involved in essential mechanisms, such as cell signaling. Given the difficulty of obtaining direct experimental structural biology data, prediction of those interactions is of crucial interest for the rational development of new drugs, notably to fight diseases, such as cancer or Alzheimer’s disease. Because of the high flexibility of natural unconstrained linear peptides, prediction of their binding mode in a protein cavity remains challenging. Several theoretical approaches have been developed in the last decade to address this issue. Nevertheless, improvements are needed, such as the conformation prediction of peptide side-chains, which are dependent on peptide length and flexibility. Here, we present a novel in silico method, Iterative Residue Docking and Linking (IRDL), to efficiently predict peptide–protein interactions. In order to reduce the conformational space, this innovative method splits peptides into several short segments. Then, it uses the performance of intramolecular covalent docking to rebuild, sequentially, the complete peptide in the active site of its protein target. Once the peptide is constructed, a rescoring step is applied in order to correctly rank all IRDL solutions. Applied on a set of 11 crystallized peptide–protein complexes, the IRDL method shows promising results, since it is able to retrieve experimental binding conformations with a Root Mean Square Deviation (RMSD) below 2 Å in the top five ranked solutions. For some complexes, IRDL method outperforms two other docking protocols evaluated in this study. Hence, IRDL is a new tool that could be used in drug design projects to predict peptide–protein interactions.https://www.mdpi.com/1420-3049/24/7/1351protein–peptide interactioncovalent dockingpeptide conformationmolecular modeling |
| spellingShingle | Julien Diharce Mickaël Cueto Massimiliano Beltramo Vincent Aucagne Pascal Bonnet In Silico Peptide Ligation: Iterative Residue Docking and Linking as a New Approach to Predict Protein-Peptide Interactions Molecules protein–peptide interaction covalent docking peptide conformation molecular modeling |
| title | In Silico Peptide Ligation: Iterative Residue Docking and Linking as a New Approach to Predict Protein-Peptide Interactions |
| title_full | In Silico Peptide Ligation: Iterative Residue Docking and Linking as a New Approach to Predict Protein-Peptide Interactions |
| title_fullStr | In Silico Peptide Ligation: Iterative Residue Docking and Linking as a New Approach to Predict Protein-Peptide Interactions |
| title_full_unstemmed | In Silico Peptide Ligation: Iterative Residue Docking and Linking as a New Approach to Predict Protein-Peptide Interactions |
| title_short | In Silico Peptide Ligation: Iterative Residue Docking and Linking as a New Approach to Predict Protein-Peptide Interactions |
| title_sort | in silico peptide ligation iterative residue docking and linking as a new approach to predict protein peptide interactions |
| topic | protein–peptide interaction covalent docking peptide conformation molecular modeling |
| url | https://www.mdpi.com/1420-3049/24/7/1351 |
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