Extending BigSMILES to non-covalent bonds in supramolecular polymer assemblies

Weizhong Zou, Alexis Martell Monterroza, Yunxin Yao, S. Cem Millik, Morgan M. Cencer, Nathan J. Rebello, Haley K. Beech, Melody A. Morris, Tzyy Shyang Lin, Cleotilde S. Castano, Julia A. Kalow, Stephen L. Craig, Alshakim Nelson, Jeffrey S. Moore, Bradley D. Olsen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

As a machine-recognizable representation of polymer connectivity, BigSMILES line notation extends SMILES from deterministic to stochastic structures. The same framework that allows BigSMILES to accommodate stochastic covalent connectivity can be extended to non-covalent bonds, enhancing its value for polymers, supramolecular materials, and colloidal chemistry. Non-covalent bonds are captured through the inclusion of annotations to pseudo atoms serving as complementary binding pairs, minimal key/value pairs to elaborate other relevant attributes, and indexes to specify the pairing among potential donors and acceptors or bond delocalization. Incorporating these annotations into BigSMILES line notation enables the representation of four common classes of non-covalent bonds in polymer science: electrostatic interactions, hydrogen bonding, metal-ligand complexation, and π-π stacking. The principal advantage of non-covalent BigSMILES is the ability to accommodate a broad variety of non-covalent chemistry with a simple user-orientated, semi-flexible annotation formalism. This goal is achieved by encoding a universal but non-exhaustive representation of non-covalent or stochastic bonding patterns through syntax for (de)protonated and delocalized state of bonding as well as nested bonds for correlated bonding and multi-component mixture. By allowing user-defined descriptors in the annotation expression, further applications in data-driven research can be envisioned to represent chemical structures in many other fields, including polymer nanocomposite and surface chemistry.

Original languageEnglish (US)
Pages (from-to)12045-12055
Number of pages11
JournalChemical Science
Volume13
Issue number41
DOIs
StatePublished - Sep 15 2022

Funding

This work was supported by the NSF Center for the Chemistry of Molecularly Optimized Networks (MONET; Award CHE-2116298). We are grateful for useful discussions with Dr. Dylan Walsh (Massachusetts Institute of Technology) and Dr. Yang Hsia (University of Washington, Seattle) on non-covalent chemistry and use of SMILES notation in polymer science, respectively.

ASJC Scopus subject areas

  • General Chemistry

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