Shi, J.
, Walsh, D.
, Zou, W.
, Rebello, N.
, Deagen, M.
, Fransen, K.
, Gao, X.
, Audus, D.
and Olsen, B.
(2024),
Calculating Pairwise Similarity of Polymer Ensembles via Earth Mover's Distance, ACS Polymers Au, [online], https://doi.org/10.1021/acspolymersau.3c00029, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=956582
(Accessed April 27, 2024)
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Calculating Pairwise Similarity of Polymer Ensembles via Earth Mover's Distance
Published
Author(s)
Jiale Shi, Dylan Walsh, Weizhong Zou, Nathan Rebello, Michael Deagen, Katharina Fransen, Xian Gao, , Bradley Olsen
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.Citation
ACS Polymers Au
Pub Type
Journals
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Citation
Created January 10, 2024, Updated February 20, 2024