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Sapphire-based clustering


Cocina, Francesco; Vitalis, Andreas; Caflisch, Amedeo (2020). Sapphire-based clustering. Journal of Chemical Theory and Computation, 16(10):6383-6396.

Abstract

Molecular dynamics simulations are a popular means to study biomolecules, but it is often difficult to gain insights from the trajectories due to their large size, in both time and number of features. The Sapphire (States And Pathways Projected with HIgh REsolution) plot allows a direct visual inference of the dominant states visited by high-dimensional systems and how they are interconnected in time. Here, we extend this visual inference into a clustering algorithm. Specifically, the automatic procedure derives from the Sapphire plot states that are kinetically homogeneous, structurally annotated, and of tunable granularity. We provide a relative assessment of the kinetic fidelity of the Sapphire-based partitioning in comparison to popular clustering methods. This assessment is carried out on trajectories of n-butane, a β-sheet peptide, and the small protein BPTI. We conclude with an application of our approach to a recent 100 μs trajectory of the main protease of SARS-CoV-2.

Abstract

Molecular dynamics simulations are a popular means to study biomolecules, but it is often difficult to gain insights from the trajectories due to their large size, in both time and number of features. The Sapphire (States And Pathways Projected with HIgh REsolution) plot allows a direct visual inference of the dominant states visited by high-dimensional systems and how they are interconnected in time. Here, we extend this visual inference into a clustering algorithm. Specifically, the automatic procedure derives from the Sapphire plot states that are kinetically homogeneous, structurally annotated, and of tunable granularity. We provide a relative assessment of the kinetic fidelity of the Sapphire-based partitioning in comparison to popular clustering methods. This assessment is carried out on trajectories of n-butane, a β-sheet peptide, and the small protein BPTI. We conclude with an application of our approach to a recent 100 μs trajectory of the main protease of SARS-CoV-2.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Department of Biochemistry
07 Faculty of Science > Department of Biochemistry
Dewey Decimal Classification:570 Life sciences; biology
610 Medicine & health
Scopus Subject Areas:Physical Sciences > Computer Science Applications
Physical Sciences > Physical and Theoretical Chemistry
Language:English
Date:13 October 2020
Deposited On:23 Nov 2020 15:54
Last Modified:23 Nov 2020 16:24
Publisher:American Chemical Society (ACS)
ISSN:1549-9618
Additional Information:This document is the Accepted Manuscript version of a Published Work that appeared in final form in J Chem Theory Comput copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://pubs.acs.org/doi/10.1021/acs.jctc.0c00604
OA Status:Closed
Publisher DOI:https://doi.org/10.1021/acs.jctc.0c00604
PubMed ID:32905698

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Content: Accepted Version
Language: English
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Embargo till: 2021-10-13
Content: Published Version
Language: English
Filetype: PDF - Registered users only
Size: 10MB