BigSMILES: A Structurally-Based Line Notation for Describing Macromolecules.

Published

Journal Article

Having a compact yet robust structurally based identifier or representation system is a key enabling factor for efficient sharing and dissemination of research results within the chemistry community, and such systems lay down the essential foundations for future informatics and data-driven research. While substantial advances have been made for small molecules, the polymer community has struggled in coming up with an efficient representation system. This is because, unlike other disciplines in chemistry, the basic premise that each distinct chemical species corresponds to a well-defined chemical structure does not hold for polymers. Polymers are intrinsically stochastic molecules that are often ensembles with a distribution of chemical structures. This difficulty limits the applicability of all deterministic representations developed for small molecules. In this work, a new representation system that is capable of handling the stochastic nature of polymers is proposed. The new system is based on the popular "simplified molecular-input line-entry system" (SMILES), and it aims to provide representations that can be used as indexing identifiers for entries in polymer databases. As a pilot test, the entries of the standard data set of the glass transition temperature of linear polymers (Bicerano, 2002) were converted into the new BigSMILES language. Furthermore, it is hoped that the proposed system will provide a more effective language for communication within the polymer community and increase cohesion between the researchers within the community.

Full Text

Duke Authors

Cited Authors

  • Lin, T-S; Coley, CW; Mochigase, H; Beech, HK; Wang, W; Wang, Z; Woods, E; Craig, SL; Johnson, JA; Kalow, JA; Jensen, KF; Olsen, BD

Published Date

  • September 12, 2019

Published In

Volume / Issue

  • 5 / 9

Start / End Page

  • 1523 - 1531

PubMed ID

  • 31572779

Pubmed Central ID

  • 31572779

Electronic International Standard Serial Number (EISSN)

  • 2374-7951

International Standard Serial Number (ISSN)

  • 2374-7943

Digital Object Identifier (DOI)

  • 10.1021/acscentsci.9b00476

Language

  • eng