Structurally based identifiers such as SMILES, molfile and InChI have been shown to be exceptionally useful in modern chemical information and cheminformatics research by enabling the digitalization of small molecules. However, since most existing identifiers are designed under the premise that each chemical species corresponds to one well-defined chemical structure, their applicability to polymers, which are intrinsically stochastic molecules that are usually ensembles of molecules with a distribution of chemical structures, are markedly limited.<br/><br/>To provide support over polymers, a new line notation, BigSMILES, that is built on top of the popular line notation SMILES, is proposed. In BigSMILES, ensembles of polymeric fragments are represented by “stochastic objects” that encodes the chemical structures by specifying the structures of the constituent repeating units and the permissible set of connectivity patterns between the repeating units. This allows efficient and compact representation of the ensemble of possible molecular structures for a polymer based on its fundamental polymerization chemistry. Through a few simple extensions to the SMILES syntax, the new BigSMILES system can easily encode a variety of polymer chemistries, including but not limited to linear polymers formed from chain and step polymerization, including random or block copolymers, branched polymers, polymer networks and ring polymers.<br/><br/>Furthermore, a canonicalization scheme for generating unique BigSMILES strings is also proposed. By making analogies between the chemical structures of linear polymers and regular grammar, chemically equivalent representations for a polymer can be reduced to a canonical form by finding the corresponding minimal deterministic finite automaton (dfa).

BigSMILES: A line notation for macromolecules

ACS Spring Meeting 2021

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.