Structure-based machine-guided mapping of amyloid sequence space reveals uncharted sequence clusters with higher solubilities
An increasing number of amyloid structures are determined. Here, the authors present the structure-based amyloid core sequence prediction method Cordax that is based on machine learning and allows the detection of aggregation-prone regions with higher solubility, disorder and surface exposure, and f...
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2020-07-01
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Online Access: | https://doi.org/10.1038/s41467-020-17207-3 |
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doaj-2a64a32adfa14ef9a2a2d237d6f0b10b2021-07-04T11:47:16ZengNature Publishing GroupNature Communications2041-17232020-07-0111111310.1038/s41467-020-17207-3Structure-based machine-guided mapping of amyloid sequence space reveals uncharted sequence clusters with higher solubilitiesNikolaos Louros0Gabriele Orlando1Matthias De Vleeschouwer2Frederic Rousseau3Joost Schymkowitz4Switch Laboratory, VIB Center for Brain and Disease ResearchSwitch Laboratory, VIB Center for Brain and Disease ResearchSwitch Laboratory, VIB Center for Brain and Disease ResearchSwitch Laboratory, VIB Center for Brain and Disease ResearchSwitch Laboratory, VIB Center for Brain and Disease ResearchAn increasing number of amyloid structures are determined. Here, the authors present the structure-based amyloid core sequence prediction method Cordax that is based on machine learning and allows the detection of aggregation-prone regions with higher solubility, disorder and surface exposure, and furthermore predicts the structural topology, orientation and overall architecture of the resulting putative fibril core.https://doi.org/10.1038/s41467-020-17207-3 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Nikolaos Louros Gabriele Orlando Matthias De Vleeschouwer Frederic Rousseau Joost Schymkowitz |
spellingShingle |
Nikolaos Louros Gabriele Orlando Matthias De Vleeschouwer Frederic Rousseau Joost Schymkowitz Structure-based machine-guided mapping of amyloid sequence space reveals uncharted sequence clusters with higher solubilities Nature Communications |
author_facet |
Nikolaos Louros Gabriele Orlando Matthias De Vleeschouwer Frederic Rousseau Joost Schymkowitz |
author_sort |
Nikolaos Louros |
title |
Structure-based machine-guided mapping of amyloid sequence space reveals uncharted sequence clusters with higher solubilities |
title_short |
Structure-based machine-guided mapping of amyloid sequence space reveals uncharted sequence clusters with higher solubilities |
title_full |
Structure-based machine-guided mapping of amyloid sequence space reveals uncharted sequence clusters with higher solubilities |
title_fullStr |
Structure-based machine-guided mapping of amyloid sequence space reveals uncharted sequence clusters with higher solubilities |
title_full_unstemmed |
Structure-based machine-guided mapping of amyloid sequence space reveals uncharted sequence clusters with higher solubilities |
title_sort |
structure-based machine-guided mapping of amyloid sequence space reveals uncharted sequence clusters with higher solubilities |
publisher |
Nature Publishing Group |
series |
Nature Communications |
issn |
2041-1723 |
publishDate |
2020-07-01 |
description |
An increasing number of amyloid structures are determined. Here, the authors present the structure-based amyloid core sequence prediction method Cordax that is based on machine learning and allows the detection of aggregation-prone regions with higher solubility, disorder and surface exposure, and furthermore predicts the structural topology, orientation and overall architecture of the resulting putative fibril core. |
url |
https://doi.org/10.1038/s41467-020-17207-3 |
work_keys_str_mv |
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