A robotics-inspired screening algorithm for molecular caging prediction

Tools

Kravchenko, Oleksandr and Varava, Anastasiia and Pokorny, Florian T. and Devaurs, Didier and Kavraki, Lydia E. and Kragic, Danica (2020) A robotics-inspired screening algorithm for molecular caging prediction. Journal of Chemical Information and Modeling, 60 (3). pp. 1302-1316. ISSN 1549-9596 (https://doi.org/10.1021/acs.jcim.9b00945)

[thumbnail of Kravchenko-etal-JCIM-2020-A-robotics-inspired-screening-algorithm-for-molecular-caging-prediction]
Preview
 Text. Filename: Kravchenko-etal-JCIM-2020-A-robotics-inspired-screening-algorithm-for-molecular-caging-prediction.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (4MB)| Preview

Abstract

We define a molecular caging complex as a pair of molecules in which one molecule (the "host"or "cage") possesses a cavity that can encapsulate the other molecule (the "guest") and prevent it from escaping. Molecular caging complexes can be useful in applications such as molecular shape sorting, drug delivery, and molecular immobilization in materials science, to name just a few. However, the design and computational discovery of new caging complexes is a challenging task, as it is hard to predict whether one molecule can encapsulate another because their shapes can be quite complex. In this paper, we propose a computational screening method that predicts whether a given pair of molecules form a caging complex. Our method is based on a caging verification algorithm that was designed by our group for applications in robotic manipulation. We tested our algorithm on three pairs of molecules that were previously described in a pioneering work on molecular caging complexes and found that our results are fully consistent with the previously reported ones. Furthermore, we performed a screening experiment on a data set consisting of 46 hosts and four guests and used our algorithm to predict which pairs are likely to form caging complexes. Our method is computationally efficient and can be integrated into a screening pipeline to complement experimental techniques.

ORCID iDs

Kravchenko, Oleksandr, Varava, Anastasiia, Pokorny, Florian T., Devaurs, Didier ORCID logoORCID: https://orcid.org/0000-0002-3415-9816, Kavraki, Lydia E. and Kragic, Danica;
CORE (COnnecting REpositories)