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Carbohydrate-derived amphiphilic macromolecules: a biophysical structural characterization and analysis of binding behaviors to model membranes.

Martin AA, Tomasini M, Kholodovych V, Gu L, Sommerfeld SD, Uhrich KE, Murthy NS, Welsh WJ, Moghe PV - J Funct Biomater (2015)

Bottom Line: QCM-D measurements with Voigt viscoelastic model analysis enabled the quantitation of the mass gain and rate of interaction between the AM and the lipid bilayer surface.Thus, this study yielded insights about variations in the functional activity of AM materials with minute compositional or stereochemical differences based on membrane binding, which has translational potential for transplanting these materials in vivo.More broadly, it demonstrates an integrated computational-experimental approach, which can offer a promising strategy for the in silico design and screening of therapeutic candidate materials.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmacology, Rutgers University, Piscataway, 675 Hoes Lane, Piscataway, NJ 08854, USA. adrianamartin7@gmail.com.

ABSTRACT
The design and synthesis of enhanced membrane-intercalating biomaterials for drug delivery or vascular membrane targeting is currently challenged by the lack of screening and prediction tools. The present work demonstrates the generation of a Quantitative Structural Activity Relationship model (QSAR) to make a priori predictions. Amphiphilic macromolecules (AMs) "stealth lipids" built on aldaric and uronic acids frameworks attached to poly(ethylene glycol) (PEG) polymer tails were developed to form self-assembling micelles. In the present study, a defined set of novel AM structures were investigated in terms of their binding to lipid membrane bilayers using Quartz Crystal Microbalance with Dissipation (QCM-D) experiments coupled with computational coarse-grained molecular dynamics (CG MD) and all-atom MD (AA MD) simulations. The CG MD simulations capture the insertion dynamics of the AM lipophilic backbones into the lipid bilayer with the PEGylated tail directed into bulk water. QCM-D measurements with Voigt viscoelastic model analysis enabled the quantitation of the mass gain and rate of interaction between the AM and the lipid bilayer surface. Thus, this study yielded insights about variations in the functional activity of AM materials with minute compositional or stereochemical differences based on membrane binding, which has translational potential for transplanting these materials in vivo. More broadly, it demonstrates an integrated computational-experimental approach, which can offer a promising strategy for the in silico design and screening of therapeutic candidate materials.

No MeSH data available.


Related in: MedlinePlus

Three-dimensional scores plot of the AMs (A–J) in Principal Component space for PCA1, PCA2, and PCA3. The AMs divided into specific subclusters (denoted by circles) based on similar physicochemical features. Decomposition of the PCA loadings into the original descriptors found major contributions by the calculated log octanol/water partition coefficient (slogP); the total hydrophobic surface area (ASA_H); and the total polar surface area (ASA_P).
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jfb-06-00171-f009: Three-dimensional scores plot of the AMs (A–J) in Principal Component space for PCA1, PCA2, and PCA3. The AMs divided into specific subclusters (denoted by circles) based on similar physicochemical features. Decomposition of the PCA loadings into the original descriptors found major contributions by the calculated log octanol/water partition coefficient (slogP); the total hydrophobic surface area (ASA_H); and the total polar surface area (ASA_P).

Mentions: The QSAR model employs statistical regression methods to correlate changes in the values of specific calculated molecular descriptors of the AMs with changes in the corresponding experimentally measured binding affinity (Figure 9). Development of the eventual QSAR model ensues in two phases, known as training (model building) and testing (model validation). The training set consisted of ten AMs. Partial least squares (PLS) regression was employed to build a linear regression model. The initial model was tested internally using leave-1-out cross validation. The physicochemical features of the AMs were successfully discerned by physicochemical descriptor modeling. Figure 9 shows clusters of AMs possessing similar characteristics for structural and conformational comparison. Physicochemical descriptors are used to account for properties of the macromolecule serving as numerical descriptions or characterizations of structural features of the AMs including composition, spatial organization and surface area accessibility (Figure 9).


Carbohydrate-derived amphiphilic macromolecules: a biophysical structural characterization and analysis of binding behaviors to model membranes.

Martin AA, Tomasini M, Kholodovych V, Gu L, Sommerfeld SD, Uhrich KE, Murthy NS, Welsh WJ, Moghe PV - J Funct Biomater (2015)

Three-dimensional scores plot of the AMs (A–J) in Principal Component space for PCA1, PCA2, and PCA3. The AMs divided into specific subclusters (denoted by circles) based on similar physicochemical features. Decomposition of the PCA loadings into the original descriptors found major contributions by the calculated log octanol/water partition coefficient (slogP); the total hydrophobic surface area (ASA_H); and the total polar surface area (ASA_P).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4493506&req=5

jfb-06-00171-f009: Three-dimensional scores plot of the AMs (A–J) in Principal Component space for PCA1, PCA2, and PCA3. The AMs divided into specific subclusters (denoted by circles) based on similar physicochemical features. Decomposition of the PCA loadings into the original descriptors found major contributions by the calculated log octanol/water partition coefficient (slogP); the total hydrophobic surface area (ASA_H); and the total polar surface area (ASA_P).
Mentions: The QSAR model employs statistical regression methods to correlate changes in the values of specific calculated molecular descriptors of the AMs with changes in the corresponding experimentally measured binding affinity (Figure 9). Development of the eventual QSAR model ensues in two phases, known as training (model building) and testing (model validation). The training set consisted of ten AMs. Partial least squares (PLS) regression was employed to build a linear regression model. The initial model was tested internally using leave-1-out cross validation. The physicochemical features of the AMs were successfully discerned by physicochemical descriptor modeling. Figure 9 shows clusters of AMs possessing similar characteristics for structural and conformational comparison. Physicochemical descriptors are used to account for properties of the macromolecule serving as numerical descriptions or characterizations of structural features of the AMs including composition, spatial organization and surface area accessibility (Figure 9).

Bottom Line: QCM-D measurements with Voigt viscoelastic model analysis enabled the quantitation of the mass gain and rate of interaction between the AM and the lipid bilayer surface.Thus, this study yielded insights about variations in the functional activity of AM materials with minute compositional or stereochemical differences based on membrane binding, which has translational potential for transplanting these materials in vivo.More broadly, it demonstrates an integrated computational-experimental approach, which can offer a promising strategy for the in silico design and screening of therapeutic candidate materials.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmacology, Rutgers University, Piscataway, 675 Hoes Lane, Piscataway, NJ 08854, USA. adrianamartin7@gmail.com.

ABSTRACT
The design and synthesis of enhanced membrane-intercalating biomaterials for drug delivery or vascular membrane targeting is currently challenged by the lack of screening and prediction tools. The present work demonstrates the generation of a Quantitative Structural Activity Relationship model (QSAR) to make a priori predictions. Amphiphilic macromolecules (AMs) "stealth lipids" built on aldaric and uronic acids frameworks attached to poly(ethylene glycol) (PEG) polymer tails were developed to form self-assembling micelles. In the present study, a defined set of novel AM structures were investigated in terms of their binding to lipid membrane bilayers using Quartz Crystal Microbalance with Dissipation (QCM-D) experiments coupled with computational coarse-grained molecular dynamics (CG MD) and all-atom MD (AA MD) simulations. The CG MD simulations capture the insertion dynamics of the AM lipophilic backbones into the lipid bilayer with the PEGylated tail directed into bulk water. QCM-D measurements with Voigt viscoelastic model analysis enabled the quantitation of the mass gain and rate of interaction between the AM and the lipid bilayer surface. Thus, this study yielded insights about variations in the functional activity of AM materials with minute compositional or stereochemical differences based on membrane binding, which has translational potential for transplanting these materials in vivo. More broadly, it demonstrates an integrated computational-experimental approach, which can offer a promising strategy for the in silico design and screening of therapeutic candidate materials.

No MeSH data available.


Related in: MedlinePlus