Molecular simulations of self-assembling bio-inspired supramolecular systems and their connection to experiments

Summary of main observation and conclusion Physical encapsulation of drugs into polymer micelles is a common method of loading hydrophobic drugs. Methoxy polyethylene glycol‐poly(D,L‐lactide) (mPEG‐PDLLA) is one of the most commonly used drug carrier. At present, whether a carrier is suitable for the loading of a certain drug is determined by drug loading experiments. This process costs a lot of time. Therefore, an efficient predicting method to avoid time‐consuming tests is critical. In this study, we prepared mPEG5k‐PDLLA5k and used it to load a series of drugs. Three parameters were used to test the miscibility of mPEG5k‐PDLLA5k with drugs, including absolute difference in Hildebrand solubility parameters (|Δδ|), Flory–Huggins interaction parameter (χ) and the distance (D value) calculated from the two‐dimensional solubility parameters. We found the two‐dimensional solubility parameters obtained from JB2013 group contribution (GC) method was useful. By comparing the drug loading content (DLC) with the D value, we found that when the D value was less than 5.0 (MJ/m3)1/2, the miscibility of drug and mPEG5k‐PDLLA5k was good and drug loading capability was high; when the D value was more than 8.0 (MJ/m3)1/2, the drug was barely loaded. Thus, this work provided a rationale to qualitatively predict the loading capability of mPEG5k‐PDLLA5k for hydrophobic drugs.

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“…Many computational studies provided insights into the molecular interactions between drugs and carriers . For example, Wu et al .…”

Section: Background and Originality Contentmentioning

confidence: 99%

Predicting the Loading Capability of mPEG‐PDLLA to Hydrophobic Drugs Using Solubility Parameters^†

Sun

Shen

et al. 2020

Chin. J. Chem.

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“…In addition, CG-MD simulations allowed to estimate self-assembling propensity of different peptide sequences for a wide latitude of potential applications. [33][34][35][36] Nonetheless, analytical tools for the quantitative tracking of secondary structure patterns (such as β-structures) over MD trajectories are still lacking. This is an important limitation, given that knowledge of the timedependent formation of secondary structures is crucial for a deeper understanding of the self-assembling phenomenon.…”

Section: Introductionmentioning

confidence: 99%

Elucidating Self‐Assembling Peptide Aggregation via Morphoscanner: A New Tool for Protein‐Peptide Structural Characterization

et al. 2018

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Self‐assembling and molecular folding are ubiquitous in Nature: they drive the organization of systems ranging from living creatures to DNA molecules. Elucidating the complex dynamics underlying these phenomena is of crucial importance. However, a tool for the analysis of the various phenomena involved in protein/peptide aggregation is still missing. Here, an innovative software is developed and validated for the identification and visualization of b‐structuring and b‐sheet formation in both simulated systems and crystal structures of proteins and peptides. The novel software suite, dubbed Morphoscanner, is designed to identify and intuitively represent b‐structuring and b‐sheet formation during molecular dynamics trajectories, paying attention to temporary strand‐strand alignment, suboligomer formation and evolution of local order. Self‐assembling peptides (SAPs) constitute a promising class of biomaterials and an interesting model to study the spontaneous assembly of molecular systems in vitro. With the help of coarse‐grained molecular dynamics the self‐assembling of diverse SAPs is simulated into molten aggregates. When applied to these systems, Morphoscanner highlights different b‐structuring schemes and kinetics related to SAP sequences. It is demonstrated that Morphoscanner is a novel versatile tool designed to probe the aggregation dynamics of self‐assembling systems, adaptable to the analysis of differently coarsened simulations of a variety of biomolecules.

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“…To gain insights into the global arrangement and self‐assembly pathway of the hydrogels, we used long and large‐scale restrained atomistic molecular dynamics (MD) simulations . Initially, we focused on the functionally most favorable hydrogel B24.…”

Section: Resultsmentioning

confidence: 99%

Design Parameters of Tissue‐Engineering Scaffolds at the Atomic Scale

et al. 2019

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Stem‐cell behavior is regulated by the material properties of the surrounding extracellular matrix, which has important implications for the design of tissue‐engineering scaffolds. However, our understanding of the material properties of stem‐cell scaffolds is limited to nanoscopic‐to‐macroscopic length scales. Herein, a solid‐state NMR approach is presented that provides atomic‐scale information on complex stem‐cell substrates at near physiological conditions and at natural isotope abundance. Using self‐assembled peptidic scaffolds designed for nervous‐tissue regeneration, we show at atomic scale how scaffold‐assembly degree, mechanics, and homogeneity correlate with favorable stem cell behavior. Integration of solid‐state NMR data with molecular dynamics simulations reveals a highly ordered fibrillar structure as the most favorable stem‐cell scaffold. This could improve the design of tissue‐engineering scaffolds and other self‐assembled biomaterials.

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Molecular simulations of self-assembling bio-inspired supramolecular systems and their connection to experiments

Abstract: The self-assembly of bio-inspired supramolecular polymers can be unravelled using molecular dynamics simulations combined with experiments.

Cited by 143 publications

References 235 publications

Predicting the Loading Capability of mPEG‐PDLLA to Hydrophobic Drugs Using Solubility Parameters^†

Predicting the Loading Capability of mPEG‐PDLLA to Hydrophobic Drugs Using Solubility Parameters^†

Elucidating Self‐Assembling Peptide Aggregation via Morphoscanner: A New Tool for Protein‐Peptide Structural Characterization

Design Parameters of Tissue‐Engineering Scaffolds at the Atomic Scale

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Molecular simulations of self-assembling bio-inspired supramolecular systems and their connection to experiments

Abstract: The self-assembly of bio-inspired supramolecular polymers can be unravelled using molecular dynamics simulations combined with experiments.

Cited by 143 publications

References 235 publications

Predicting the Loading Capability of mPEG‐PDLLA to Hydrophobic Drugs Using Solubility Parameters†

Predicting the Loading Capability of mPEG‐PDLLA to Hydrophobic Drugs Using Solubility Parameters†

Elucidating Self‐Assembling Peptide Aggregation via Morphoscanner: A New Tool for Protein‐Peptide Structural Characterization

Design Parameters of Tissue‐Engineering Scaffolds at the Atomic Scale

Contact Info

Product

Resources

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Predicting the Loading Capability of mPEG‐PDLLA to Hydrophobic Drugs Using Solubility Parameters^†

Predicting the Loading Capability of mPEG‐PDLLA to Hydrophobic Drugs Using Solubility Parameters^†