Dataset Information

Spatially controlled assembly of affinity ligand and enzyme cargo enables targeting ferritin nanocarriers to caveolae.

ABSTRACT: One of the goals of nanomedicine is targeted delivery of therapeutic enzymes to the sub-cellular compartments where their action is needed. Endothelial caveolae-derived endosomes represent an important yet challenging destination for targeting, in part due to smaller size of the entry aperture of caveolae (ca. 30-50?nm). Here, we designed modular, multi-molecular, ferritin-based nanocarriers with uniform size (20?nm diameter) for easy drug-loading and targeted delivery of enzymatic cargo to these specific vesicles. These nanocarriers targeted to caveolar Plasmalemmal Vesicle-Associated Protein (Plvap) deliver superoxide dismutase (SOD) into endosomes in endothelial cells, the specific site of influx of superoxide mediating by such pro-inflammatory signaling as some cytokines and lipopolysaccharide (LPS). Cell studies showed efficient internalization of Plvap-targeted SOD-loaded nanocarriers followed by dissociation from caveolin-containing vesicles and intracellular transport to endosomes. The nanocarriers had a profound protective anti-inflammatory effect in an animal model of LPS-induced inflammation, in agreement with the characteristics of their endothelial uptake and intracellular transport, indicating that these novel, targeted nanocarriers provide an advantageous platform for caveolae-dependent delivery of biotherapeutics.

SUBMITTER: Shuvaev VV

PROVIDER: S-EPMC6487198 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Spatially controlled assembly of affinity ligand and enzyme cargo enables targeting ferritin nanocarriers to caveolae.

Shuvaev Vladimir V VV Khoshnejad Makan M Pulsipher Katherine W KW Kiseleva Raisa Yu RY Arguiri Evguenia E Cheung-Lau Jasmina C JC LeFort Kathleen M KM Christofidou-Solomidou Melpo M Stan Radu V RV Dmochowski Ivan J IJ Muzykantov Vladimir R VR

Biomaterials 20180912

One of the goals of nanomedicine is targeted delivery of therapeutic enzymes to the sub-cellular compartments where their action is needed. Endothelial caveolae-derived endosomes represent an important yet challenging destination for targeting, in part due to smaller size of the entry aperture of caveolae (ca. 30-50 nm). Here, we designed modular, multi-molecular, ferritin-based nanocarriers with uniform size (20 nm diameter) for easy drug-loading and targeted delivery of enzymatic cargo to thes ...[more]

PMID: 30273834

Similar Datasets

Project description:BACKGROUND: Models that are capable of reliably predicting binding affinities for protein-ligand complexes play an important role the field of structure-guided drug design. METHODS: Here, we begin by applying the computational geometry technique of Delaunay tessellation to each set of atomic coordinates for over 1400 diverse macromolecular structures, for the purpose of deriving a four-body statistical potential that serves as a topological scoring function. Next, we identify a second, independent set of three hundred protein-ligand complexes, having both high-resolution structures and known dissociation constants. Two-thirds of these complexes are randomly selected to train a predictive model of binding affinity as follows: two tessellations are generated in each case, one for the entire complex and another strictly for the isolated protein without its bound ligand, and a topological score is computed for each tessellation with the four-body potential. Predicted protein-ligand binding affinity is then based on an empirically derived linear function of the difference between both topological scores, one that appropriately scales the value of this difference. RESULTS: A comparison between experimental and calculated binding affinity values over the two hundred complexes reveals a Pearson's correlation coefficient of r = 0.79 with a standard error of SE = 1.98 kcal/mol. To validate the method, we similarly generated two tessellations for each of the remaining protein-ligand complexes, computed their topological scores and the difference between the two scores for each complex, and applied the previously derived linear transformation of this topological score difference to predict binding affinities. For these one hundred complexes, we again observe a correlation of r = 0.79 (SE = 1.93 kcal/mol) between known and calculated binding affinities. Applying our model to an independent test set of high-resolution structures for three hundred diverse enzyme-inhibitor complexes, each with an experimentally known inhibition constant, also yields a correlation of r = 0.79 (SE = 2.39 kcal/mol) between experimental and calculated binding energies. CONCLUSIONS: Lastly, we generate predictions with our model on a diverse test set of one hundred protein-ligand complexes previously used to benchmark 15 related methods, and our correlation of r = 0.66 between the calculated and experimental binding energies for this dataset exceeds those of the other approaches. Compared with these related prediction methods, our approach stands out based on salient features that include the reliability of our model, combined with the rapidity of the generated predictions, which are less than one second for an average sized complex.

Dataset Information

Spatially controlled assembly of affinity ligand and enzyme cargo enables targeting ferritin nanocarriers to caveolae.

Publications

Spatially controlled assembly of affinity ligand and enzyme cargo enables targeting ferritin nanocarriers to caveolae.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets