MoleQCage: geometric high-throughput screening for molecular caging prediction

Alexander  Kravberg; Didier Devaurs; Anastasiia Varava; Lydia E. Kavraki; Danica Kragic

doi:10.1021/acs.jcim.4c01419

MoleQCage: geometric high-throughput screening for molecular caging prediction

Alexander Kravberg, Didier Devaurs^*, Anastasiia Varava, Lydia E. Kavraki, Danica Kragic

^*Corresponding author for this work

Computer And Information Sciences

Research output: Contribution to journal › Article › peer-review

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Abstract

Although being able to determine whether a host molecule can enclose a guest molecule and form a caging complex could benefit numerous chemical and medical applications, the experimental discovery of molecular caging complexes has not yet been achieved at scale. Here, we propose MoleQCage, a simple tool for the high-throughput screening of host and guest candidates based on an efficient robotics-inspired geometric algorithm for molecular caging prediction, providing theoretical guarantees and robustness assessment. MoleQCage is distributed as Linux-based software with a graphical user interface and is available online at https://hub.docker.com/r/dantrigne/moleqcage in the form of a Docker container. Documentation and examples are available as Supporting Information and online at https://hub.docker.com/r/dantrigne/moleqcage.

Original language	English
Pages (from-to)	9034–9039
Number of pages	6
Journal	Journal of Chemical Information and Modeling
Volume	64
Issue number	24
Early online date	12 Dec 2024
DOIs	https://doi.org/10.1021/acs.jcim.4c01419
Publication status	Published - 23 Dec 2024

Funding

This research was supported by the Knut and Alice Wallenberg Foundation [A.K., A.V., D.K.]; the Swedish Research Council [A.K., A.V., D.K.]; the Rice University Funds [L.E.K.]; and the Medical Research Council (MRC) [MC_UU_00009/2 to D.D.].

Keywords

MoleQCage
molecular caging complex
high-throughput screening
geometric algorithm

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1021/acs.jcim.4c01419Licence: CC BY 4.0

Kravberg-etal-JCIM-2024-MoleQCage-geometric-high-throughput-screeningFinal published version, 4.75 MBLicence: CC BY 4.0

Cite this

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title = "MoleQCage: geometric high-throughput screening for molecular caging prediction",

abstract = "Although being able to determine whether a host molecule can enclose a guest molecule and form a caging complex could benefit numerous chemical and medical applications, the experimental discovery of molecular caging complexes has not yet been achieved at scale. Here, we propose MoleQCage, a simple tool for the high-throughput screening of host and guest candidates based on an efficient robotics-inspired geometric algorithm for molecular caging prediction, providing theoretical guarantees and robustness assessment. MoleQCage is distributed as Linux-based software with a graphical user interface and is available online at https://hub.docker.com/r/dantrigne/moleqcage in the form of a Docker container. Documentation and examples are available as Supporting Information and online at https://hub.docker.com/r/dantrigne/moleqcage.",

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author = "Alexander Kravberg and Didier Devaurs and Anastasiia Varava and Kavraki, \{Lydia E.\} and Danica Kragic",

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doi = "10.1021/acs.jcim.4c01419",

language = "English",

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pages = "9034–9039",

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AU - Kravberg, Alexander

AU - Devaurs, Didier

AU - Varava, Anastasiia

AU - Kavraki, Lydia E.

AU - Kragic, Danica

PY - 2024/12/23

Y1 - 2024/12/23

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KW - geometric algorithm

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MoleQCage: geometric high-throughput screening for molecular caging prediction

Abstract

Funding

Keywords

UN SDGs

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