Work

MoleQCage: Geometric High-Throughput Screening for Molecular Caging Prediction

Year: 2024

Type: article

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.

Source: Journal of Chemical Information and Modeling

DOI: 10.1021/acs.jcim.4c01419

Authors: Alexander Kravberg, Didier Devaurs, Anastasiia Varava, Lydia E. Kavraki, Danica Kragic

Institutions: KTH Royal Institute of Technology, University of Strathclyde, Rice University

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $4,500

Funders: Rice University, Knut och Alice Wallenbergs Stiftelse, Vetenskapsrådet, Medical Research Council