Extending BigSMILES to non-covalent bonds in supramolecular polymer assemblies

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

doi:10.1039/d2sc02257e

Cited by 14 publications

(13 citation statements)

References 63 publications

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“…The first step in generating a similarity score is to generate stochastic polymer graphs. The polymer molecular structure (see Figure a) is converted to a canonical BigSMILES , representation, a structurally based line notation for describing macromolecules (see Figure b), following the priority rules of canonicalization procedures from Lin et al This canonicalization step is essential as it ensures that every polymer has exactly one representation. Without this step, it is possible to generate a similarity score smaller than one for the same polymer, as multiple noncanonical BigSMILES can map to the same polymer.…”

Section: Methodsmentioning

confidence: 99%

Quantifying Pairwise Similarity for Complex Polymers

Shi,

Rebello,

Walsh

et al. 2023

Macromolecules

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Defining the similarity between chemical entities is an essential task in polymer informatics, enabling ranking, clustering, and classification. Despite its importance, the pairwise chemical similarity of polymers remains an open problem. Here, a similarity function for polymers with well-defined backbones is designed based on polymers’ stochastic graph representations generated from canonical BigSMILES, a structurally based line notation for describing macromolecules. The stochastic graph representations are separated into three parts: repeat units, end groups, and polymer topology. The earth mover’s distance is utilized to calculate the similarity of the repeat units and end groups, while the graph edit distance is used to calculate the similarity of the topology. These three values can be linearly or nonlinearly combined to yield an overall pairwise chemical similarity score for polymers that is largely consistent with the chemical intuition of expert users and is adjustable based on the relative importance of different chemical features for a given similarity problem. This method gives a reliable solution to quantitatively calculate the pairwise chemical similarity score for polymers and represents a vital step toward building search engines and quantitative design tools for polymer data.

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Section: Methodsmentioning

confidence: 99%

Quantifying Pairwise Similarity for Complex Polymers

Shi,

Rebello,

Walsh

et al. 2023

Macromolecules

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“…Further advancement in ML methods and molecular descriptors is necessary to quantify the distinct structural architectures of polymer membranes used in separation. Additionally, recently developed numerical representations of polymers, designed for diverse applications, hold potential relevance in describing polymer membranes [183][184][185]. These innovative representations offer opportunities to capture the unique structural characteristics of polymer membranes used in liquid separation processes.…”

Section: Current Challenges and Future Perspectivementioning

confidence: 99%

Recent developments in 3D-printed membranes for water desalination

He,

Yue,

McCutcheon

et al. 2023

J. Phys. Energy

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The recognition of membrane separations as a vital technology platform for enhancing the efficiency of separation processes has been steadily increasing. Concurrently, 3D printing has emerged as an innovative approach to fabricating reverse osmosis (RO) membranes for water desalination and treatment purposes. This method provides a high degree of control over membrane chemistry and structural properties. In particular, when compared to traditional manufacturing techniques, 3D printing holds the potential to expedite customization, a feat that is typically achieved through conventional manufacturing methods but often involves numerous processes and significant costs. This review aims to present the current advancements in membrane manufacturing technology specifically tailored for water desalination purposes, with a particular focus on the development of 3D-printed membranes. A comprehensive analysis of recent progress in 3D-printed membranes is provided. However, conducting experimental work to investigate various influential factors while ensuring consistent results poses a significant challenge. To address this, we explore how membrane manufacturing processes and performance can be effectively pre-designed and guided through the use of molecular dynamics simulations. Finally, this review outlines the challenges faced and presents future perspectives to shed light on research directions for optimizing membrane manufacturing processes and achieving optimal membrane performance.

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“…The most important interactions that lead to gel production in this category are hydrogen bonding, dipolardipolar, and hydrophobic interactions (Anderson et al, 2020;Zhou et al, 2020;Yang et al, 2022). These relatively weak interactions have reversible nature, which means that the substance can turn into a gel in the environment outside the body, then during injection into the body, due to the shear stresses of the injection, the bonds are broken and turn into a sol, and after a while, it returns to the gel state again (Liu et al, 2020;Bai et al, 2022;Zou et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Smart stimuli-responsive injectable gels and hydrogels for drug delivery and tissue engineering applications: A review

Salehi

Naghib

Garshasbi

et al. 2023

Front. Bioeng. Biotechnol.

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Hydrogels are widely used biomaterials in the delivery of therapeutic agents, including drugs, genes, proteins, etc., as well as tissue engineering, due to obvious properties such as biocompatibility and their similarity to natural body tissues. Some of these substances have the feature of injectability, which means that the substance is injected into the desired place in the solution state and then turns into the gel, which makes it possible to administer them from a way with a minimal amount of invasion and eliminate the need for surgery to implant pre-formed materials. Gelation can be caused by a stimulus and/or spontaneously. Suppose this induces due to the effect of one or many stimuli. In that case, the material in question is called stimuli-responsive because it responds to the surrounding conditions. In this context, we introduce the different stimuli that cause gelation and investigate the different mechanisms of the transformation of the solution into the gel in them. Also, we study special structures, such as nano gels or nanocomposite gels.

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Extending BigSMILES to non-covalent bonds in supramolecular polymer assemblies

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...

Cited by 14 publications

References 63 publications

Quantifying Pairwise Similarity for Complex Polymers

Quantifying Pairwise Similarity for Complex Polymers

Recent developments in 3D-printed membranes for water desalination

Smart stimuli-responsive injectable gels and hydrogels for drug delivery and tissue engineering applications: A review

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