Calculating Pairwise Similarity of Polymer Ensembles via Earth Mover’s Distance
Name
calculating-pairwise-similarity-of-polymer-ensembles-via-earth-mover-s-distance.pdf
Description
Published version
Size
3.82 MB
Format
Adobe PDF
Checksum (MD5)
e775eb8c9b8199778181b2760b0c2ea1
Author(s)
Shi, Jiale
Walsh, Dylan
Zou, Weizhong
Rebello, Nathan J
Deagen, Michael E
Fransen, Katharina A
Gao, Xian
Olsen, Bradley D
Audus, Debra J
Date Issued
February 14, 2024
Journal
ACS Polymers Au
Publisher
American Chemical Society
Citation
Jiale Shi, Dylan Walsh, Weizhong Zou, Nathan J. Rebello, Michael E. Deagen, Katharina A. Fransen, Xian Gao, Bradley D. Olsen, and Debra J. Audus. ACS Polymers Au 2024 4 (1), 66-76.
Version
Final published version
Abstract
Synthetic polymers, in contrast to small molecules and deterministic biomacromolecules, are typically ensembles composed of polymer chains with varying numbers, lengths, sequences, chemistry, and topologies. While numerous approaches exist for measuring pairwise similarity among small molecules and sequence-defined biomacromolecules, accurately determining the pairwise similarity between two polymer ensembles remains challenging. This work proposes the earth mover's distance (EMD) metric to calculate the pairwise similarity score between two polymer ensembles. EMD offers a greater resolution of chemical differences between polymer ensembles than the averaging method and provides a quantitative numeric value representing the pairwise similarity between polymer ensembles in alignment with chemical intuition. The EMD approach for assessing polymer similarity enhances the development of accurate chemical search algorithms within polymer databases and can improve machine learning techniques for polymer design, optimization, and property prediction.
MIT Department
Massachusetts Institute of Technology. Department of Chemical Engineering
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivatives
Persistent DSpace Link
DOI of Published Version
10.1021/acspolymersau.3c00029
