Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins
Background Docking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Devaurs, Didier [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2019 |
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| Übergeordnetes Werk: |
Enthalten in: BMC cell biology - London : BioMed Central, 2000, 20(2019), 1 vom: 05. Sept. |
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| Übergeordnetes Werk: |
volume:20 ; year:2019 ; number:1 ; day:05 ; month:09 |
| Links: |
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| DOI / URN: |
10.1186/s12860-019-0218-z |
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SPR026940590 |
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| 520 | |a Background Docking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling of a large ligand is also often considered a challenge because of its underlying combinatorial complexity. In this study, we evaluate the impact of using parallelized and incremental paradigms on the accuracy and performance of conformational sampling when docking large ligands. We use five datasets of protein-ligand complexes involving ligands that could not be accurately docked by classical protein-ligand docking tools in previous similar studies. Results Our computational evaluation shows that simply increasing the amount of conformational sampling performed by a protein-ligand docking tool, such as Vina, by running it for longer is rarely beneficial. Instead, it is more efficient and advantageous to run several short instances of this docking tool in parallel and group their results together, in a straightforward parallelized docking protocol. Even greater accuracy and efficiency are achieved by our parallelized incremental meta-docking tool, DINC, showing the additional benefits of its incremental paradigm. Using DINC, we could accurately reproduce the vast majority of the protein-ligand complexes we considered. Conclusions Our study suggests that, even when trying to dock large ligands to proteins, the conformational sampling of the ligand should no longer be considered an issue, as simple docking protocols using existing tools can solve it. Therefore, scoring should currently be regarded as the biggest unmet challenge in molecular docking. | ||
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10.1186/s12860-019-0218-z doi (DE-627)SPR026940590 (SPR)s12860-019-0218-z-e DE-627 ger DE-627 rakwb eng Devaurs, Didier verfasserin aut Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Background Docking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling of a large ligand is also often considered a challenge because of its underlying combinatorial complexity. In this study, we evaluate the impact of using parallelized and incremental paradigms on the accuracy and performance of conformational sampling when docking large ligands. We use five datasets of protein-ligand complexes involving ligands that could not be accurately docked by classical protein-ligand docking tools in previous similar studies. Results Our computational evaluation shows that simply increasing the amount of conformational sampling performed by a protein-ligand docking tool, such as Vina, by running it for longer is rarely beneficial. Instead, it is more efficient and advantageous to run several short instances of this docking tool in parallel and group their results together, in a straightforward parallelized docking protocol. Even greater accuracy and efficiency are achieved by our parallelized incremental meta-docking tool, DINC, showing the additional benefits of its incremental paradigm. Using DINC, we could accurately reproduce the vast majority of the protein-ligand complexes we considered. Conclusions Our study suggests that, even when trying to dock large ligands to proteins, the conformational sampling of the ligand should no longer be considered an issue, as simple docking protocols using existing tools can solve it. Therefore, scoring should currently be regarded as the biggest unmet challenge in molecular docking. Molecular docking (dpeaa)DE-He213 Protein-ligand docking (dpeaa)DE-He213 Protein-peptide docking (dpeaa)DE-He213 Conformational sampling (dpeaa)DE-He213 Scoring (dpeaa)DE-He213 Parallelism (dpeaa)DE-He213 Incremental protocol (dpeaa)DE-He213 Antunes, Dinler A aut Hall-Swan, Sarah aut Mitchell, Nicole aut Moll, Mark aut Lizée, Gregory aut Kavraki, Lydia E (orcid)0000-0003-0699-8038 aut Enthalten in BMC cell biology London : BioMed Central, 2000 20(2019), 1 vom: 05. Sept. (DE-627)326644830 (DE-600)2041486-9 1471-2121 nnns volume:20 year:2019 number:1 day:05 month:09 https://dx.doi.org/10.1186/s12860-019-0218-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_22 GBV_ILN_2003 GBV_ILN_2008 GBV_ILN_2021 GBV_ILN_4305 AR 20 2019 1 05 09 |
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10.1186/s12860-019-0218-z doi (DE-627)SPR026940590 (SPR)s12860-019-0218-z-e DE-627 ger DE-627 rakwb eng Devaurs, Didier verfasserin aut Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Background Docking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling of a large ligand is also often considered a challenge because of its underlying combinatorial complexity. In this study, we evaluate the impact of using parallelized and incremental paradigms on the accuracy and performance of conformational sampling when docking large ligands. We use five datasets of protein-ligand complexes involving ligands that could not be accurately docked by classical protein-ligand docking tools in previous similar studies. Results Our computational evaluation shows that simply increasing the amount of conformational sampling performed by a protein-ligand docking tool, such as Vina, by running it for longer is rarely beneficial. Instead, it is more efficient and advantageous to run several short instances of this docking tool in parallel and group their results together, in a straightforward parallelized docking protocol. Even greater accuracy and efficiency are achieved by our parallelized incremental meta-docking tool, DINC, showing the additional benefits of its incremental paradigm. Using DINC, we could accurately reproduce the vast majority of the protein-ligand complexes we considered. Conclusions Our study suggests that, even when trying to dock large ligands to proteins, the conformational sampling of the ligand should no longer be considered an issue, as simple docking protocols using existing tools can solve it. Therefore, scoring should currently be regarded as the biggest unmet challenge in molecular docking. Molecular docking (dpeaa)DE-He213 Protein-ligand docking (dpeaa)DE-He213 Protein-peptide docking (dpeaa)DE-He213 Conformational sampling (dpeaa)DE-He213 Scoring (dpeaa)DE-He213 Parallelism (dpeaa)DE-He213 Incremental protocol (dpeaa)DE-He213 Antunes, Dinler A aut Hall-Swan, Sarah aut Mitchell, Nicole aut Moll, Mark aut Lizée, Gregory aut Kavraki, Lydia E (orcid)0000-0003-0699-8038 aut Enthalten in BMC cell biology London : BioMed Central, 2000 20(2019), 1 vom: 05. Sept. (DE-627)326644830 (DE-600)2041486-9 1471-2121 nnns volume:20 year:2019 number:1 day:05 month:09 https://dx.doi.org/10.1186/s12860-019-0218-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_22 GBV_ILN_2003 GBV_ILN_2008 GBV_ILN_2021 GBV_ILN_4305 AR 20 2019 1 05 09 |
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10.1186/s12860-019-0218-z doi (DE-627)SPR026940590 (SPR)s12860-019-0218-z-e DE-627 ger DE-627 rakwb eng Devaurs, Didier verfasserin aut Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Background Docking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling of a large ligand is also often considered a challenge because of its underlying combinatorial complexity. In this study, we evaluate the impact of using parallelized and incremental paradigms on the accuracy and performance of conformational sampling when docking large ligands. We use five datasets of protein-ligand complexes involving ligands that could not be accurately docked by classical protein-ligand docking tools in previous similar studies. Results Our computational evaluation shows that simply increasing the amount of conformational sampling performed by a protein-ligand docking tool, such as Vina, by running it for longer is rarely beneficial. Instead, it is more efficient and advantageous to run several short instances of this docking tool in parallel and group their results together, in a straightforward parallelized docking protocol. Even greater accuracy and efficiency are achieved by our parallelized incremental meta-docking tool, DINC, showing the additional benefits of its incremental paradigm. Using DINC, we could accurately reproduce the vast majority of the protein-ligand complexes we considered. Conclusions Our study suggests that, even when trying to dock large ligands to proteins, the conformational sampling of the ligand should no longer be considered an issue, as simple docking protocols using existing tools can solve it. Therefore, scoring should currently be regarded as the biggest unmet challenge in molecular docking. Molecular docking (dpeaa)DE-He213 Protein-ligand docking (dpeaa)DE-He213 Protein-peptide docking (dpeaa)DE-He213 Conformational sampling (dpeaa)DE-He213 Scoring (dpeaa)DE-He213 Parallelism (dpeaa)DE-He213 Incremental protocol (dpeaa)DE-He213 Antunes, Dinler A aut Hall-Swan, Sarah aut Mitchell, Nicole aut Moll, Mark aut Lizée, Gregory aut Kavraki, Lydia E (orcid)0000-0003-0699-8038 aut Enthalten in BMC cell biology London : BioMed Central, 2000 20(2019), 1 vom: 05. Sept. (DE-627)326644830 (DE-600)2041486-9 1471-2121 nnns volume:20 year:2019 number:1 day:05 month:09 https://dx.doi.org/10.1186/s12860-019-0218-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_22 GBV_ILN_2003 GBV_ILN_2008 GBV_ILN_2021 GBV_ILN_4305 AR 20 2019 1 05 09 |
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10.1186/s12860-019-0218-z doi (DE-627)SPR026940590 (SPR)s12860-019-0218-z-e DE-627 ger DE-627 rakwb eng Devaurs, Didier verfasserin aut Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Background Docking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling of a large ligand is also often considered a challenge because of its underlying combinatorial complexity. In this study, we evaluate the impact of using parallelized and incremental paradigms on the accuracy and performance of conformational sampling when docking large ligands. We use five datasets of protein-ligand complexes involving ligands that could not be accurately docked by classical protein-ligand docking tools in previous similar studies. Results Our computational evaluation shows that simply increasing the amount of conformational sampling performed by a protein-ligand docking tool, such as Vina, by running it for longer is rarely beneficial. Instead, it is more efficient and advantageous to run several short instances of this docking tool in parallel and group their results together, in a straightforward parallelized docking protocol. Even greater accuracy and efficiency are achieved by our parallelized incremental meta-docking tool, DINC, showing the additional benefits of its incremental paradigm. Using DINC, we could accurately reproduce the vast majority of the protein-ligand complexes we considered. Conclusions Our study suggests that, even when trying to dock large ligands to proteins, the conformational sampling of the ligand should no longer be considered an issue, as simple docking protocols using existing tools can solve it. Therefore, scoring should currently be regarded as the biggest unmet challenge in molecular docking. Molecular docking (dpeaa)DE-He213 Protein-ligand docking (dpeaa)DE-He213 Protein-peptide docking (dpeaa)DE-He213 Conformational sampling (dpeaa)DE-He213 Scoring (dpeaa)DE-He213 Parallelism (dpeaa)DE-He213 Incremental protocol (dpeaa)DE-He213 Antunes, Dinler A aut Hall-Swan, Sarah aut Mitchell, Nicole aut Moll, Mark aut Lizée, Gregory aut Kavraki, Lydia E (orcid)0000-0003-0699-8038 aut Enthalten in BMC cell biology London : BioMed Central, 2000 20(2019), 1 vom: 05. Sept. (DE-627)326644830 (DE-600)2041486-9 1471-2121 nnns volume:20 year:2019 number:1 day:05 month:09 https://dx.doi.org/10.1186/s12860-019-0218-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_22 GBV_ILN_2003 GBV_ILN_2008 GBV_ILN_2021 GBV_ILN_4305 AR 20 2019 1 05 09 |
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10.1186/s12860-019-0218-z doi (DE-627)SPR026940590 (SPR)s12860-019-0218-z-e DE-627 ger DE-627 rakwb eng Devaurs, Didier verfasserin aut Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s) 2019 Background Docking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling of a large ligand is also often considered a challenge because of its underlying combinatorial complexity. In this study, we evaluate the impact of using parallelized and incremental paradigms on the accuracy and performance of conformational sampling when docking large ligands. We use five datasets of protein-ligand complexes involving ligands that could not be accurately docked by classical protein-ligand docking tools in previous similar studies. Results Our computational evaluation shows that simply increasing the amount of conformational sampling performed by a protein-ligand docking tool, such as Vina, by running it for longer is rarely beneficial. Instead, it is more efficient and advantageous to run several short instances of this docking tool in parallel and group their results together, in a straightforward parallelized docking protocol. Even greater accuracy and efficiency are achieved by our parallelized incremental meta-docking tool, DINC, showing the additional benefits of its incremental paradigm. Using DINC, we could accurately reproduce the vast majority of the protein-ligand complexes we considered. Conclusions Our study suggests that, even when trying to dock large ligands to proteins, the conformational sampling of the ligand should no longer be considered an issue, as simple docking protocols using existing tools can solve it. Therefore, scoring should currently be regarded as the biggest unmet challenge in molecular docking. Molecular docking (dpeaa)DE-He213 Protein-ligand docking (dpeaa)DE-He213 Protein-peptide docking (dpeaa)DE-He213 Conformational sampling (dpeaa)DE-He213 Scoring (dpeaa)DE-He213 Parallelism (dpeaa)DE-He213 Incremental protocol (dpeaa)DE-He213 Antunes, Dinler A aut Hall-Swan, Sarah aut Mitchell, Nicole aut Moll, Mark aut Lizée, Gregory aut Kavraki, Lydia E (orcid)0000-0003-0699-8038 aut Enthalten in BMC cell biology London : BioMed Central, 2000 20(2019), 1 vom: 05. Sept. (DE-627)326644830 (DE-600)2041486-9 1471-2121 nnns volume:20 year:2019 number:1 day:05 month:09 https://dx.doi.org/10.1186/s12860-019-0218-z kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_22 GBV_ILN_2003 GBV_ILN_2008 GBV_ILN_2021 GBV_ILN_4305 AR 20 2019 1 05 09 |
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Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins Molecular docking (dpeaa)DE-He213 Protein-ligand docking (dpeaa)DE-He213 Protein-peptide docking (dpeaa)DE-He213 Conformational sampling (dpeaa)DE-He213 Scoring (dpeaa)DE-He213 Parallelism (dpeaa)DE-He213 Incremental protocol (dpeaa)DE-He213 |
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Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins |
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Background Docking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling of a large ligand is also often considered a challenge because of its underlying combinatorial complexity. In this study, we evaluate the impact of using parallelized and incremental paradigms on the accuracy and performance of conformational sampling when docking large ligands. We use five datasets of protein-ligand complexes involving ligands that could not be accurately docked by classical protein-ligand docking tools in previous similar studies. Results Our computational evaluation shows that simply increasing the amount of conformational sampling performed by a protein-ligand docking tool, such as Vina, by running it for longer is rarely beneficial. Instead, it is more efficient and advantageous to run several short instances of this docking tool in parallel and group their results together, in a straightforward parallelized docking protocol. Even greater accuracy and efficiency are achieved by our parallelized incremental meta-docking tool, DINC, showing the additional benefits of its incremental paradigm. Using DINC, we could accurately reproduce the vast majority of the protein-ligand complexes we considered. Conclusions Our study suggests that, even when trying to dock large ligands to proteins, the conformational sampling of the ligand should no longer be considered an issue, as simple docking protocols using existing tools can solve it. Therefore, scoring should currently be regarded as the biggest unmet challenge in molecular docking. © The Author(s) 2019 |
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Background Docking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling of a large ligand is also often considered a challenge because of its underlying combinatorial complexity. In this study, we evaluate the impact of using parallelized and incremental paradigms on the accuracy and performance of conformational sampling when docking large ligands. We use five datasets of protein-ligand complexes involving ligands that could not be accurately docked by classical protein-ligand docking tools in previous similar studies. Results Our computational evaluation shows that simply increasing the amount of conformational sampling performed by a protein-ligand docking tool, such as Vina, by running it for longer is rarely beneficial. Instead, it is more efficient and advantageous to run several short instances of this docking tool in parallel and group their results together, in a straightforward parallelized docking protocol. Even greater accuracy and efficiency are achieved by our parallelized incremental meta-docking tool, DINC, showing the additional benefits of its incremental paradigm. Using DINC, we could accurately reproduce the vast majority of the protein-ligand complexes we considered. Conclusions Our study suggests that, even when trying to dock large ligands to proteins, the conformational sampling of the ligand should no longer be considered an issue, as simple docking protocols using existing tools can solve it. Therefore, scoring should currently be regarded as the biggest unmet challenge in molecular docking. © The Author(s) 2019 |
| abstract_unstemmed |
Background Docking large ligands, and especially peptides, to protein receptors is still considered a challenge in computational structural biology. Besides the issue of accurately scoring the binding modes of a protein-ligand complex produced by a molecular docking tool, the conformational sampling of a large ligand is also often considered a challenge because of its underlying combinatorial complexity. In this study, we evaluate the impact of using parallelized and incremental paradigms on the accuracy and performance of conformational sampling when docking large ligands. We use five datasets of protein-ligand complexes involving ligands that could not be accurately docked by classical protein-ligand docking tools in previous similar studies. Results Our computational evaluation shows that simply increasing the amount of conformational sampling performed by a protein-ligand docking tool, such as Vina, by running it for longer is rarely beneficial. Instead, it is more efficient and advantageous to run several short instances of this docking tool in parallel and group their results together, in a straightforward parallelized docking protocol. Even greater accuracy and efficiency are achieved by our parallelized incremental meta-docking tool, DINC, showing the additional benefits of its incremental paradigm. Using DINC, we could accurately reproduce the vast majority of the protein-ligand complexes we considered. Conclusions Our study suggests that, even when trying to dock large ligands to proteins, the conformational sampling of the ligand should no longer be considered an issue, as simple docking protocols using existing tools can solve it. Therefore, scoring should currently be regarded as the biggest unmet challenge in molecular docking. © The Author(s) 2019 |
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