Identification of the Proteins Determining the Blood Circulation Time of Nanoparticles.

The therapeutic efficacy and adverse impacts of nanoparticles (NPs) are strongly dependent on their systemic circulation time. The corona proteins adsorbed on the NPs determine their plasma half-lives, and hence, it is crucial to identify the proteins shortening or extending their circulation time. In this work, the in vivo circulation time and corona composition of superparamagnetic iron oxide nanoparticles (SPIONs) with different surface charges/chemistries were analyzed over time. SPIONs with neutral and positive charges showed the longest and shortest circulation times, respectively. The most striking observation was that corona-coated NPs with similar opsonin/dysopsonin content showed different circulation times, implying these biomolecules are not the only contributing factors. Long-circulating NPs adsorb higher concentrations of osteopontin, lipoprotein lipase, coagulation factor VII, matrix Gla protein, secreted phosphoprotein 24, alpha-2-HS-glycoprotein, and apolipoprotein C-I, while short-circulating NPs adsorb higher amounts of hemoglobin. Therefore, these proteins may be considered to be determining factors governing the NP systemic circulation time.

An Overview of Nanoparticle Protein Corona Literature.

The protein corona forms spontaneously on nanoparticle surfaces when nanomaterials are introduced into any biological system/fluid. Reliable characterization of the protein corona is, therefore, a vital step in the development of safe and efficient diagnostic and therapeutic nanomedicine products. 2134 published manuscripts on the protein corona are reviewed and a down-selection of 470 papers spanning 2000-2021, comprising 1702 nanoparticle (NP) systems is analyzed. This analysis reveals: i) most corona studies have been conducted on metal and metal oxide nanoparticles; ii) despite their overwhelming presence in clinical practice, lipid-based NPs are underrepresented in protein corona research, iii) studies use new methods to improve reliability and reproducibility in protein corona research; iv) studies use more specific protein sources toward personalized medicine; and v) careful characterization of nanoparticles after corona formation is imperative to minimize the role of aggregation and protein contamination on corona outcomes. As nanoparticles used in biomedicine become increasingly prevalent and biochemically complex, the field of protein corona research will need to focus on developing analytical approaches and characterization techniques appropriate for each unique nanoparticle formulation. Achieving such characterization of the nano-bio interface of nanobiotechnologies will enable more seamless development and safe implementation of nanoparticles in medicine.

The Possible Role of Sex As an Important Factor in Development and Administration of Lipid Nanomedicine-Based COVID-19 Vaccine.

Nanomedicine has demonstrated a substantial role in vaccine development against severe acute respiratory syndrome coronavirus (SARS-CoV-2 and COVID-19). Although nanomedicine-based vaccines have now been validated in millions of individuals worldwide in phase 4 and tracking of sex-disaggregated data on COVID-19 is ongoing, immune responses that underlie COVID-19 disease outcomes have not been clarified yet. A full understanding of sex-role effects on the response to nanomedicine products is essential to building an effective and unbiased response to the pandemic. Here, we exposed model lipid nanoparticles (LNPs) to whole blood of 18 healthy donors (10 females and 8 males) and used flow cytometry to measure cellular uptake by circulating leukocytes. Our results demonstrated significant differences in the uptake of LNP between male and female natural killer (NK) cells. The results of this proof-of-concept study show the importance of recipient sex as a critical factor which enables researchers to better consider sex in the development and administration of vaccines for safer and more-efficient sex-specific outcomes.

Effect of Cell Sex on Uptake of Nanoparticles: The Overlooked Factor at the Nanobio Interface.

Cellular uptake of nanoparticles (NPs) depends on the nature of the nanobio system including the solid nanocomponents ( e. g., physicochemical properties of NPs), nanobio interfaces ( e. g., protein corona composition), and the cellular characteristics ( e. g., cell type). In this study, we document the role of sex in cellular uptake of NPs as an "overlooked" factor in nanobio interface investigations. We demonstrate that cell sex leads to differences in NP uptake between male and female human amniotic stem cells (hAMSCs), with greater uptake by female cells. hAMSCs are one of the earliest sources of somatic stem cells. The experiments were replicated with primary fibroblasts isolated from the salivary gland of adult male and female donors of similar ages, and again the extent of NP uptake was altered by cell sex. However, in contrast to hAMSCs, uptake was greater in male cells. We also found out that female versus male amniotic stem cells exhibited different responses to reprogramming into induced pluripotent stem cells (iPSCs) by the Yamanaka factors. Thus, future studies should consider the effect of sex on the nanobio interactions to optimize clinical translation of NPs and iPSC biology and to help researchers to better design and produce safe and efficient therapeutic sex-specific NPs.

Bypassing Protein Corona Issue on Active Targeting: Zwitterionic Coatings Dictate Specific Interactions of Targeting Moieties and Cell Receptors.

Surface functionalization strategies for targeting nanoparticles (NP) to specific organs, cells, or organelles, is the foundation for new applications of nanomedicine to drug delivery and biomedical imaging. Interaction of NPs with biological media leads to the formation of a biomolecular layer at the surface of NPs so-called as "protein corona". This corona layer can shield active molecules at the surface of NPs and cause mistargeting or unintended scavenging by the liver, kidney, or spleen. To overcome this corona issue, we have designed biotin-cysteine conjugated silica NPs (biotin was employed as a targeting molecule and cysteine was used as a zwitterionic ligand) to inhibit corona-induced mistargeting and thus significantly enhance the active targeting capability of NPs in complex biological media. To probe the targeting yield of our engineered NPs, we employed both modified silicon wafer substrates with streptavidin (i.e., biotin receptor) to simulate a target and a cell-based model platform using tumor cell lines that overexpress biotin receptors. In both cases, after incubation with human plasma (thus forming a protein corona), cellular uptake/substrate attachment of the targeted NPs with zwitterionic coatings were significantly higher than the same NPs without zwitterionic coating. Our results demonstrated that NPs with a zwitterionic surface can considerably facilitate targeting yield of NPs and provide a promising new type of nanocarriers in biological applications.

4D-LQTA-QSAR and docking study on potent Gram-negative specific LpxC inhibitors: a comparison to CoMFA modeling.

A quasi 4D-QSAR has been carried out on a series of potent Gram-negative LpxC inhibitors. This approach makes use of the molecular dynamics (MD) trajectories and topology information retrieved from the GROMACS package. This new methodology is based on the generation of a conformational ensemble profile, CEP, for each compound instead of only one conformation, followed by the calculation intermolecular interaction energies at each grid point considering probes and all aligned conformations resulting from MD simulations. These interaction energies are independent variables employed in a QSAR analysis. The comparison of the proposed methodology to comparative molecular field analysis (CoMFA) formalism was performed. This methodology explores jointly the main features of CoMFA and 4D-QSAR models. Step-wise multiple linear regression was used for the selection of the most informative variables. After variable selection, multiple linear regression (MLR) and partial least squares (PLS) methods used for building the regression models. Leave-N-out cross-validation (LNO), and Y-randomization were performed in order to confirm the robustness of the model in addition to analysis of the independent test set. Best models provided the following statistics: [Formula in text] (PLS) and [Formula in text] (MLR). Docking study was applied to investigate the major interactions in protein-ligand complex with CDOCKER algorithm. Visualization of the descriptors of the best model helps us to interpret the model from the chemical point of view, supporting the applicability of this new approach in rational drug design.