A comparative analysis of clustering algorithms: O2 migration in truncated hemoglobin I from transition networks
The ligand migration network for O2-diffusion in truncated Hemoglobin N is analyzed based on three different clustering schemes. For coordinate-based clustering, the conventional k-means and the kinetics-based Markov Clustering (MCL) methods are employed, whereas the locally scaled diffusion map (LS...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Cazade, Pierre-André [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2015 |
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| Schlagwörter: |
Truncated Hemoglobins - metabolism |
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| Übergeordnetes Werk: |
Enthalten in: The journal of chemical physics - Melville, NY : AIP, 1933, 142(2015), 2 |
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| Übergeordnetes Werk: |
volume:142 ; year:2015 ; number:2 |
| Links: |
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| DOI / URN: |
10.1063/1.4904431 |
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OLC1965727824 |
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| 520 | |a The ligand migration network for O2-diffusion in truncated Hemoglobin N is analyzed based on three different clustering schemes. For coordinate-based clustering, the conventional k-means and the kinetics-based Markov Clustering (MCL) methods are employed, whereas the locally scaled diffusion map (LSDMap) method is a collective-variable-based approach. It is found that all three methods agree well in their geometrical definition of the most important docking site, and all experimentally known docking sites are recovered by all three methods. Also, for most of the states, their population coincides quite favourably, whereas the kinetics of and between the states differs. One of the major differences between k-means and MCL clustering on the one hand and LSDMap on the other is that the latter finds one large primary cluster containing the Xe1a, IS1, and ENT states. This is related to the fact that the motion within the state occurs on similar time scales, whereas structurally the state is found to be quite diverse. In agreement with previous explicit atomistic simulations, the Xe3 pocket is found to be a highly dynamical site which points to its potential role as a hub in the network. This is also highlighted in the fact that LSDMap cannot identify this state. First passage time distributions from MCL clusterings using a one- (ligand-position) and two-dimensional (ligand-position and protein-structure) descriptor suggest that ligand- and protein-motions are coupled. The benefits and drawbacks of the three methods are discussed in a comparative fashion and highlight that depending on the questions at hand the best-performing method for a particular data set may differ. | ||
| 650 | 4 | |a Truncated Hemoglobins - metabolism | |
| 650 | 4 | |a Truncated Hemoglobins - chemistry | |
| 650 | 4 | |a Oxygen - metabolism | |
| 650 | 4 | |a Nitric Oxide - metabolism | |
| 700 | 1 | |a Zheng, Wenwei |4 oth | |
| 700 | 1 | |a Prada-Gracia, Diego |4 oth | |
| 700 | 1 | |a Berezovska, Ganna |4 oth | |
| 700 | 1 | |a Rao, Francesco |4 oth | |
| 700 | 1 | |a Clementi, Cecilia |4 oth | |
| 700 | 1 | |a Meuwly, Markus |4 oth | |
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10.1063/1.4904431 doi PQ20160617 (DE-627)OLC1965727824 (DE-599)GBVOLC1965727824 (PRQ)c817-8cdfad26a8d690a33851c7ac3c60261f9f3d116246382ea3c3a0335b8f24905e0 (KEY)0048355920150000142000200000comparativeanalysisofclusteringalgorithmso2migrati DE-627 ger DE-627 rakwb eng 540 530 DNB Cazade, Pierre-André verfasserin aut A comparative analysis of clustering algorithms: O2 migration in truncated hemoglobin I from transition networks 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The ligand migration network for O2-diffusion in truncated Hemoglobin N is analyzed based on three different clustering schemes. For coordinate-based clustering, the conventional k-means and the kinetics-based Markov Clustering (MCL) methods are employed, whereas the locally scaled diffusion map (LSDMap) method is a collective-variable-based approach. It is found that all three methods agree well in their geometrical definition of the most important docking site, and all experimentally known docking sites are recovered by all three methods. Also, for most of the states, their population coincides quite favourably, whereas the kinetics of and between the states differs. One of the major differences between k-means and MCL clustering on the one hand and LSDMap on the other is that the latter finds one large primary cluster containing the Xe1a, IS1, and ENT states. This is related to the fact that the motion within the state occurs on similar time scales, whereas structurally the state is found to be quite diverse. In agreement with previous explicit atomistic simulations, the Xe3 pocket is found to be a highly dynamical site which points to its potential role as a hub in the network. This is also highlighted in the fact that LSDMap cannot identify this state. First passage time distributions from MCL clusterings using a one- (ligand-position) and two-dimensional (ligand-position and protein-structure) descriptor suggest that ligand- and protein-motions are coupled. The benefits and drawbacks of the three methods are discussed in a comparative fashion and highlight that depending on the questions at hand the best-performing method for a particular data set may differ. Truncated Hemoglobins - metabolism Truncated Hemoglobins - chemistry Oxygen - metabolism Nitric Oxide - metabolism Zheng, Wenwei oth Prada-Gracia, Diego oth Berezovska, Ganna oth Rao, Francesco oth Clementi, Cecilia oth Meuwly, Markus oth Enthalten in The journal of chemical physics Melville, NY : AIP, 1933 142(2015), 2 (DE-627)129079049 (DE-600)3113-6 (DE-576)014411660 0021-9606 nnns volume:142 year:2015 number:2 http://dx.doi.org/10.1063/1.4904431 Volltext http://www.ncbi.nlm.nih.gov/pubmed/25591387 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_21 GBV_ILN_59 GBV_ILN_70 GBV_ILN_2016 GBV_ILN_2279 AR 142 2015 2 |
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10.1063/1.4904431 doi PQ20160617 (DE-627)OLC1965727824 (DE-599)GBVOLC1965727824 (PRQ)c817-8cdfad26a8d690a33851c7ac3c60261f9f3d116246382ea3c3a0335b8f24905e0 (KEY)0048355920150000142000200000comparativeanalysisofclusteringalgorithmso2migrati DE-627 ger DE-627 rakwb eng 540 530 DNB Cazade, Pierre-André verfasserin aut A comparative analysis of clustering algorithms: O2 migration in truncated hemoglobin I from transition networks 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The ligand migration network for O2-diffusion in truncated Hemoglobin N is analyzed based on three different clustering schemes. For coordinate-based clustering, the conventional k-means and the kinetics-based Markov Clustering (MCL) methods are employed, whereas the locally scaled diffusion map (LSDMap) method is a collective-variable-based approach. It is found that all three methods agree well in their geometrical definition of the most important docking site, and all experimentally known docking sites are recovered by all three methods. Also, for most of the states, their population coincides quite favourably, whereas the kinetics of and between the states differs. One of the major differences between k-means and MCL clustering on the one hand and LSDMap on the other is that the latter finds one large primary cluster containing the Xe1a, IS1, and ENT states. This is related to the fact that the motion within the state occurs on similar time scales, whereas structurally the state is found to be quite diverse. In agreement with previous explicit atomistic simulations, the Xe3 pocket is found to be a highly dynamical site which points to its potential role as a hub in the network. This is also highlighted in the fact that LSDMap cannot identify this state. First passage time distributions from MCL clusterings using a one- (ligand-position) and two-dimensional (ligand-position and protein-structure) descriptor suggest that ligand- and protein-motions are coupled. The benefits and drawbacks of the three methods are discussed in a comparative fashion and highlight that depending on the questions at hand the best-performing method for a particular data set may differ. Truncated Hemoglobins - metabolism Truncated Hemoglobins - chemistry Oxygen - metabolism Nitric Oxide - metabolism Zheng, Wenwei oth Prada-Gracia, Diego oth Berezovska, Ganna oth Rao, Francesco oth Clementi, Cecilia oth Meuwly, Markus oth Enthalten in The journal of chemical physics Melville, NY : AIP, 1933 142(2015), 2 (DE-627)129079049 (DE-600)3113-6 (DE-576)014411660 0021-9606 nnns volume:142 year:2015 number:2 http://dx.doi.org/10.1063/1.4904431 Volltext http://www.ncbi.nlm.nih.gov/pubmed/25591387 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_21 GBV_ILN_59 GBV_ILN_70 GBV_ILN_2016 GBV_ILN_2279 AR 142 2015 2 |
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10.1063/1.4904431 doi PQ20160617 (DE-627)OLC1965727824 (DE-599)GBVOLC1965727824 (PRQ)c817-8cdfad26a8d690a33851c7ac3c60261f9f3d116246382ea3c3a0335b8f24905e0 (KEY)0048355920150000142000200000comparativeanalysisofclusteringalgorithmso2migrati DE-627 ger DE-627 rakwb eng 540 530 DNB Cazade, Pierre-André verfasserin aut A comparative analysis of clustering algorithms: O2 migration in truncated hemoglobin I from transition networks 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The ligand migration network for O2-diffusion in truncated Hemoglobin N is analyzed based on three different clustering schemes. For coordinate-based clustering, the conventional k-means and the kinetics-based Markov Clustering (MCL) methods are employed, whereas the locally scaled diffusion map (LSDMap) method is a collective-variable-based approach. It is found that all three methods agree well in their geometrical definition of the most important docking site, and all experimentally known docking sites are recovered by all three methods. Also, for most of the states, their population coincides quite favourably, whereas the kinetics of and between the states differs. One of the major differences between k-means and MCL clustering on the one hand and LSDMap on the other is that the latter finds one large primary cluster containing the Xe1a, IS1, and ENT states. This is related to the fact that the motion within the state occurs on similar time scales, whereas structurally the state is found to be quite diverse. In agreement with previous explicit atomistic simulations, the Xe3 pocket is found to be a highly dynamical site which points to its potential role as a hub in the network. This is also highlighted in the fact that LSDMap cannot identify this state. First passage time distributions from MCL clusterings using a one- (ligand-position) and two-dimensional (ligand-position and protein-structure) descriptor suggest that ligand- and protein-motions are coupled. The benefits and drawbacks of the three methods are discussed in a comparative fashion and highlight that depending on the questions at hand the best-performing method for a particular data set may differ. Truncated Hemoglobins - metabolism Truncated Hemoglobins - chemistry Oxygen - metabolism Nitric Oxide - metabolism Zheng, Wenwei oth Prada-Gracia, Diego oth Berezovska, Ganna oth Rao, Francesco oth Clementi, Cecilia oth Meuwly, Markus oth Enthalten in The journal of chemical physics Melville, NY : AIP, 1933 142(2015), 2 (DE-627)129079049 (DE-600)3113-6 (DE-576)014411660 0021-9606 nnns volume:142 year:2015 number:2 http://dx.doi.org/10.1063/1.4904431 Volltext http://www.ncbi.nlm.nih.gov/pubmed/25591387 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_21 GBV_ILN_59 GBV_ILN_70 GBV_ILN_2016 GBV_ILN_2279 AR 142 2015 2 |
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10.1063/1.4904431 doi PQ20160617 (DE-627)OLC1965727824 (DE-599)GBVOLC1965727824 (PRQ)c817-8cdfad26a8d690a33851c7ac3c60261f9f3d116246382ea3c3a0335b8f24905e0 (KEY)0048355920150000142000200000comparativeanalysisofclusteringalgorithmso2migrati DE-627 ger DE-627 rakwb eng 540 530 DNB Cazade, Pierre-André verfasserin aut A comparative analysis of clustering algorithms: O2 migration in truncated hemoglobin I from transition networks 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The ligand migration network for O2-diffusion in truncated Hemoglobin N is analyzed based on three different clustering schemes. For coordinate-based clustering, the conventional k-means and the kinetics-based Markov Clustering (MCL) methods are employed, whereas the locally scaled diffusion map (LSDMap) method is a collective-variable-based approach. It is found that all three methods agree well in their geometrical definition of the most important docking site, and all experimentally known docking sites are recovered by all three methods. Also, for most of the states, their population coincides quite favourably, whereas the kinetics of and between the states differs. One of the major differences between k-means and MCL clustering on the one hand and LSDMap on the other is that the latter finds one large primary cluster containing the Xe1a, IS1, and ENT states. This is related to the fact that the motion within the state occurs on similar time scales, whereas structurally the state is found to be quite diverse. In agreement with previous explicit atomistic simulations, the Xe3 pocket is found to be a highly dynamical site which points to its potential role as a hub in the network. This is also highlighted in the fact that LSDMap cannot identify this state. First passage time distributions from MCL clusterings using a one- (ligand-position) and two-dimensional (ligand-position and protein-structure) descriptor suggest that ligand- and protein-motions are coupled. The benefits and drawbacks of the three methods are discussed in a comparative fashion and highlight that depending on the questions at hand the best-performing method for a particular data set may differ. Truncated Hemoglobins - metabolism Truncated Hemoglobins - chemistry Oxygen - metabolism Nitric Oxide - metabolism Zheng, Wenwei oth Prada-Gracia, Diego oth Berezovska, Ganna oth Rao, Francesco oth Clementi, Cecilia oth Meuwly, Markus oth Enthalten in The journal of chemical physics Melville, NY : AIP, 1933 142(2015), 2 (DE-627)129079049 (DE-600)3113-6 (DE-576)014411660 0021-9606 nnns volume:142 year:2015 number:2 http://dx.doi.org/10.1063/1.4904431 Volltext http://www.ncbi.nlm.nih.gov/pubmed/25591387 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_21 GBV_ILN_59 GBV_ILN_70 GBV_ILN_2016 GBV_ILN_2279 AR 142 2015 2 |
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10.1063/1.4904431 doi PQ20160617 (DE-627)OLC1965727824 (DE-599)GBVOLC1965727824 (PRQ)c817-8cdfad26a8d690a33851c7ac3c60261f9f3d116246382ea3c3a0335b8f24905e0 (KEY)0048355920150000142000200000comparativeanalysisofclusteringalgorithmso2migrati DE-627 ger DE-627 rakwb eng 540 530 DNB Cazade, Pierre-André verfasserin aut A comparative analysis of clustering algorithms: O2 migration in truncated hemoglobin I from transition networks 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier The ligand migration network for O2-diffusion in truncated Hemoglobin N is analyzed based on three different clustering schemes. For coordinate-based clustering, the conventional k-means and the kinetics-based Markov Clustering (MCL) methods are employed, whereas the locally scaled diffusion map (LSDMap) method is a collective-variable-based approach. It is found that all three methods agree well in their geometrical definition of the most important docking site, and all experimentally known docking sites are recovered by all three methods. Also, for most of the states, their population coincides quite favourably, whereas the kinetics of and between the states differs. One of the major differences between k-means and MCL clustering on the one hand and LSDMap on the other is that the latter finds one large primary cluster containing the Xe1a, IS1, and ENT states. This is related to the fact that the motion within the state occurs on similar time scales, whereas structurally the state is found to be quite diverse. In agreement with previous explicit atomistic simulations, the Xe3 pocket is found to be a highly dynamical site which points to its potential role as a hub in the network. This is also highlighted in the fact that LSDMap cannot identify this state. First passage time distributions from MCL clusterings using a one- (ligand-position) and two-dimensional (ligand-position and protein-structure) descriptor suggest that ligand- and protein-motions are coupled. The benefits and drawbacks of the three methods are discussed in a comparative fashion and highlight that depending on the questions at hand the best-performing method for a particular data set may differ. Truncated Hemoglobins - metabolism Truncated Hemoglobins - chemistry Oxygen - metabolism Nitric Oxide - metabolism Zheng, Wenwei oth Prada-Gracia, Diego oth Berezovska, Ganna oth Rao, Francesco oth Clementi, Cecilia oth Meuwly, Markus oth Enthalten in The journal of chemical physics Melville, NY : AIP, 1933 142(2015), 2 (DE-627)129079049 (DE-600)3113-6 (DE-576)014411660 0021-9606 nnns volume:142 year:2015 number:2 http://dx.doi.org/10.1063/1.4904431 Volltext http://www.ncbi.nlm.nih.gov/pubmed/25591387 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-CHE SSG-OLC-PHA SSG-OLC-DE-84 GBV_ILN_21 GBV_ILN_59 GBV_ILN_70 GBV_ILN_2016 GBV_ILN_2279 AR 142 2015 2 |
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A comparative analysis of clustering algorithms: O2 migration in truncated hemoglobin I from transition networks |
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The ligand migration network for O2-diffusion in truncated Hemoglobin N is analyzed based on three different clustering schemes. For coordinate-based clustering, the conventional k-means and the kinetics-based Markov Clustering (MCL) methods are employed, whereas the locally scaled diffusion map (LSDMap) method is a collective-variable-based approach. It is found that all three methods agree well in their geometrical definition of the most important docking site, and all experimentally known docking sites are recovered by all three methods. Also, for most of the states, their population coincides quite favourably, whereas the kinetics of and between the states differs. One of the major differences between k-means and MCL clustering on the one hand and LSDMap on the other is that the latter finds one large primary cluster containing the Xe1a, IS1, and ENT states. This is related to the fact that the motion within the state occurs on similar time scales, whereas structurally the state is found to be quite diverse. In agreement with previous explicit atomistic simulations, the Xe3 pocket is found to be a highly dynamical site which points to its potential role as a hub in the network. This is also highlighted in the fact that LSDMap cannot identify this state. First passage time distributions from MCL clusterings using a one- (ligand-position) and two-dimensional (ligand-position and protein-structure) descriptor suggest that ligand- and protein-motions are coupled. The benefits and drawbacks of the three methods are discussed in a comparative fashion and highlight that depending on the questions at hand the best-performing method for a particular data set may differ. |
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The ligand migration network for O2-diffusion in truncated Hemoglobin N is analyzed based on three different clustering schemes. For coordinate-based clustering, the conventional k-means and the kinetics-based Markov Clustering (MCL) methods are employed, whereas the locally scaled diffusion map (LSDMap) method is a collective-variable-based approach. It is found that all three methods agree well in their geometrical definition of the most important docking site, and all experimentally known docking sites are recovered by all three methods. Also, for most of the states, their population coincides quite favourably, whereas the kinetics of and between the states differs. One of the major differences between k-means and MCL clustering on the one hand and LSDMap on the other is that the latter finds one large primary cluster containing the Xe1a, IS1, and ENT states. This is related to the fact that the motion within the state occurs on similar time scales, whereas structurally the state is found to be quite diverse. In agreement with previous explicit atomistic simulations, the Xe3 pocket is found to be a highly dynamical site which points to its potential role as a hub in the network. This is also highlighted in the fact that LSDMap cannot identify this state. First passage time distributions from MCL clusterings using a one- (ligand-position) and two-dimensional (ligand-position and protein-structure) descriptor suggest that ligand- and protein-motions are coupled. The benefits and drawbacks of the three methods are discussed in a comparative fashion and highlight that depending on the questions at hand the best-performing method for a particular data set may differ. |
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The ligand migration network for O2-diffusion in truncated Hemoglobin N is analyzed based on three different clustering schemes. For coordinate-based clustering, the conventional k-means and the kinetics-based Markov Clustering (MCL) methods are employed, whereas the locally scaled diffusion map (LSDMap) method is a collective-variable-based approach. It is found that all three methods agree well in their geometrical definition of the most important docking site, and all experimentally known docking sites are recovered by all three methods. Also, for most of the states, their population coincides quite favourably, whereas the kinetics of and between the states differs. One of the major differences between k-means and MCL clustering on the one hand and LSDMap on the other is that the latter finds one large primary cluster containing the Xe1a, IS1, and ENT states. This is related to the fact that the motion within the state occurs on similar time scales, whereas structurally the state is found to be quite diverse. In agreement with previous explicit atomistic simulations, the Xe3 pocket is found to be a highly dynamical site which points to its potential role as a hub in the network. This is also highlighted in the fact that LSDMap cannot identify this state. First passage time distributions from MCL clusterings using a one- (ligand-position) and two-dimensional (ligand-position and protein-structure) descriptor suggest that ligand- and protein-motions are coupled. The benefits and drawbacks of the three methods are discussed in a comparative fashion and highlight that depending on the questions at hand the best-performing method for a particular data set may differ. |
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