Dual ligand-targeted Pluronic P123 polymeric micelles enhance the therapeutic effect of breast cancer with bone metastases.

Bone metastasis secondary to breast cancer negatively impacts patient quality of life and survival. The treatment of bone metastases is challenging since many anticancer drugs are not effectively delivered to the bone to exert a therapeutic effect. To improve the treatment efficacy, we developed Pluronic P123 (P123)-based polymeric micelles dually decorated with alendronate (ALN) and cancer-specific phage protein DMPGTVLP (DP-8) for targeted drug delivery to breast cancer bone metastases. Doxorubicin (DOX) was selected as the anticancer drug and was encapsulated into the hydrophobic core of the micelles with a high drug loading capacity (3.44%). The DOX-loaded polymeric micelles were spherical, 123 nm in diameter on average, and exhibited a narrow size distribution. The in vitro experiments demonstrated that a pH decrease from 7.4 to 5.0 markedly accelerated DOX release. The micelles were well internalized by cultured breast cancer cells and the cell death rate of micelle-treated breast cancer cells was increased compared to that of free DOX-treated cells. Rapid binding of the micelles to hydroxyapatite (HA) microparticles indicated their high affinity for bone. P123-ALN/DP-8@DOX inhibited tumor growth and reduced bone resorption in a 3D cancer bone metastasis model. In vivo experiments using a breast cancer bone metastasis nude model demonstrated increased accumulation of the micelles in the tumor region and considerable antitumor activity with no organ-specific histological damage and minimal systemic toxicity. In conclusion, our study provided strong evidence that these pH-sensitive dual ligand-targeted polymeric micelles may be a successful treatment strategy for breast cancer bone metastasis.

Correlation Between ImageJ and Conventional Manual Scoring Methods for Programmed Death-Ligand 1 Immuno-Histochemically Stained Sections.

Background: One of the most frequently used methods for quantifying PD-L1 (programmed cell death-ligand 1) expression in tumor tissue is IHC (immunohistochemistry). This may predict the patient's response to anti-PD1/PD-L1 therapy in cancer. Methods: ImageJ software was used to score IHC-stained sections for PD-L1 and compare the results with the conventional manual method. Results: In diffuse large B cell lymphoma, no significant difference between the scores obtained by the conventional method and ImageJ scores obtained using the option "RGB" or "Brightness/Contrast." On the other hand, a significant difference was found between the conventional and HSB scoring methods. ImageJ faced some challenges in analyzing head and neck squamous cell carcinoma tissues because of tissue heterogenicity. A significant difference was found between the conventional and ImageJ scores using HSB or RGB but not with the "Brightness/Contrast" option. Scores obtained by ImageJ analysis after taking images using 20 × objective lens gave significantly higher readings compared to 40 × magnification. A significant difference between camera-captured images' scores and scanner whole slide images' scores was observed. Conclusion: ImageJ can be used to score homogeneous tissues. In the case of highly heterogeneous tissues, it is advised to use the conventional method rather than ImageJ scoring.

A combination of virtual screening, molecular dynamics simulation, MM/PBSA, ADMET, and DFT calculations to identify a potential DPP4 inhibitor.

DPP4 inhibitors can control glucose homeostasis by increasing the level of GLP-1 incretins hormone due to dipeptidase mimicking. Despite the potent effects of DPP4 inhibitors, these compounds cause unwanted toxicity attributable to their effect on other enzymes. As a result, it seems essential to find novel and DPP4 selective compounds. In this study, we introduce a potent and selective DPP4 inhibitor via structure-based virtual screening, molecular docking, molecular dynamics simulation, MM/PBSA calculations, DFT analysis, and ADMET profile. The screened compounds based on similarity with FDA-approved DPP4 inhibitors were docked towards the DPP4 enzyme. The compound with the highest docking score, ZINC000003015356, was selected. For further considerations, molecular docking studies were performed on selected ligands and FDA-approved drugs for DPP8 and DPP9 enzymes. Molecular dynamics simulation was run during 200 ns and the analysis of RMSD, RMSF, Rg, PCA, and hydrogen bonding were performed. The MD outputs showed stability of the ligand-protein complex compared to available drugs in the market. The total free binding energy obtained for the proposed DPP4 inhibitor was more negative than its co-crystal ligand (N7F). ZINC000003015356 confirmed the role of the five Lipinski rule and also, have low toxicity parameter according to properties. Finally, DFT calculations indicated that this compound is sufficiently soft.

Ligand bias underlies differential signaling of multiple FGFs via FGFR1.

The differential signaling of multiple FGF ligands through a single fibroblast growth factor (FGF) receptor (FGFR) plays an important role in embryonic development. Here, we use quantitative biophysical tools to uncover the mechanism behind differences in FGFR1c signaling in response to FGF4, FGF8, and FGF9, a process which is relevant for limb bud outgrowth. We find that FGF8 preferentially induces FRS2 phosphorylation and extracellular matrix loss, while FGF4 and FGF9 preferentially induce FGFR1c phosphorylation and cell growth arrest. Thus, we demonstrate that FGF8 is a biased FGFR1c ligand, as compared to FGF4 and FGF9. Förster resonance energy transfer experiments reveal a correlation between biased signaling and the conformation of the FGFR1c transmembrane domain dimer. Our findings expand the mechanistic understanding of FGF signaling during development and bring the poorly understood concept of receptor tyrosine kinase ligand bias into the spotlight.

Considerations Around Structure-Based Drug Discovery for KRAS Using DOCK.

Molecular docking is a popular computational tool in drug discovery. Leveraging structural information, docking software predicts binding poses of small molecules to cavities on the surfaces of proteins. Virtual screening for ligand discovery is a useful application of docking software. In this chapter, using the enigmatic KRAS protein as an example system, we endeavor to teach the reader about best practices for performing molecular docking with UCSF DOCK. We discuss methods for virtual screening and docking molecules on KRAS. We present the following six points to optimize our docking setup for prosecuting a virtual screen: protein structure choice, pocket selection, optimization of the scoring function, modification of sampling spheres and sampling procedures, choosing an appropriate portion of chemical space to dock, and the choice of which top scoring molecules to pick for purchase.

1D and 2D NMR for KRAS:Ligand Binding.

Fragment-based screening by ligand-observed 1D NMR and binding interface mapping by protein-observed 2D NMR are popular methods used in drug discovery. These methods allow researchers to detect compound binding over a wide range of affinities and offer a simultaneous assessment of solubility, purity, and chemical formula accuracy of the target compounds and the 15N-labeled protein when examined by 1D and 2D NMR, respectively. These methods can be applied for screening fragment binding to the active (GMPPNP-bound) and inactive (GDP-bound) states of oncogenic KRAS mutants.

Indole-3-carbinol attenuates lipopolysaccharide-induced acute respiratory distress syndrome through activation of AhR: role of CCR2+ monocyte activation and recruitment in the regulation of CXCR2+ neutrophils in the lungs.

Introduction: Indole-3-carbinol (I3C) is found in cruciferous vegetables and used as a dietary supplement. It is known to act as a ligand for aryl hydrocarbon receptor (AhR). In the current study, we investigated the role of AhR and the ability of I3C to attenuate LPS-induced Acute Respiratory Distress Syndrome (ARDS). Methods: To that end, we induced ARDS in wild-type C57BL/6 mice, Ccr2gfp/gfp KI/KO mice (mice deficient in the CCR2 receptor), and LyZcreAhRfl/fl mice (mice deficient in the AhR on myeloid linage cells). Additionally, mice were treated with I3C (65 mg/kg) or vehicle to investigate its efficacy to treat ARDS. Results: I3C decreased the neutrophils expressing CXCR2, a receptor associated with neutrophil recruitment in the lungs. In addition, LPS-exposed mice treated with I3C revealed downregulation of CCR2+ monocytes in the lungs and lowered CCL2 (MCP-1) protein levels in serum and bronchoalveolar lavage fluid. Loss of CCR2 on monocytes blocked the recruitment of CXCR2+ neutrophils and decreased the total number of immune cells in the lungs during ARDS. In addition, loss of the AhR on myeloid linage cells ablated I3C-mediated attenuation of CXCR2+ neutrophils and CCR2+ monocytes in the lungs from ARDS animals. Interestingly, scRNASeq showed that in macrophage/monocyte cell clusters of LPS-exposed mice, I3C reduced the expression of CXCL2 and CXCL3, which bind to CXCR2 and are involved in neutrophil recruitment to the disease site. Discussion: These findings suggest that CCR2+ monocytes are involved in the migration and recruitment of CXCR2+ neutrophils during ARDS, and the AhR ligand, I3C, can suppress ARDS through the regulation of immune cell trafficking.

Structure and mechanisms of transport of human Asc1/CD98hc amino acid transporter.

Recent cryoEM studies elucidated details of the structural basis for the substrate selectivity and translocation of heteromeric amino acid transporters. However, Asc1/CD98hc is the only neutral heteromeric amino acid transporter that can function through facilitated diffusion, and the only one that efficiently transports glycine and D-serine, and thus has a regulatory role in the central nervous system. Here we use cryoEM, ligand-binding simulations, mutagenesis, transport assays, and molecular dynamics to define human Asc1/CD98hc determinants for substrate specificity and gain insights into the mechanisms that govern substrate translocation by exchange and facilitated diffusion. The cryoEM structure of Asc1/CD98hc is determined at 3.4-3.8 Å resolution, revealing an inward-facing semi-occluded conformation. We find that Ser 246 and Tyr 333 are essential for Asc1/CD98hc substrate selectivity and for the exchange and facilitated diffusion modes of transport. Taken together, these results reveal the structural bases for ligand binding and transport features specific to human Asc1.

Tumor-derived exosomal PD-L1: a new perspective in PD-1/PD-L1 therapy for lung cancer.

Exosomes play a crucial role in facilitating intercellular communication within organisms. Emerging evidence indicates that a distinct variant of programmed cell death ligand-1 (PD-L1), found on the surface of exosomes, may be responsible for orchestrating systemic immunosuppression that counteracts the efficacy of anti-programmed death-1 (PD-1) checkpoint therapy. Specifically, the presence of PD-L1 on exosomes enables them to selectively target PD-1 on the surface of CD8+ T cells, leading to T cell apoptosis and impeding T cell activation or proliferation. This mechanism allows tumor cells to evade immune pressure during the effector stage. Furthermore, the quantification of exosomal PD-L1 has the potential to serve as an indicator of the dynamic interplay between tumors and immune cells, thereby suggesting the promising utility of exosomes as biomarkers for both cancer diagnosis and PD-1/PD-L1 inhibitor therapy. The emergence of exosomal PD-L1 inhibitors as a viable approach for anti-tumor treatment has garnered significant attention. Depleting exosomal PD-L1 may serve as an effective adjunct therapy to mitigate systemic immunosuppression. This review aims to elucidate recent insights into the role of exosomal PD-L1 in the field of immune oncology, emphasizing its potential as a diagnostic, prognostic, and therapeutic tool in lung cancer.

A chemical proteomics approach for global mapping of functional lysines on cell surface of living cell.

Cell surface proteins are responsible for many crucial physiological roles, and they are also the major category of drug targets as the majority of therapeutics target membrane proteins on the surface of cells to alter cellular signaling. Despite its great significance, ligand discovery against membrane proteins has posed a great challenge mainly due to the special property of their natural habitat. Here, we design a new chemical proteomic probe OPA-S-S-alkyne that can efficiently and selectively target the lysines exposed on the cell surface and develop a chemical proteomics strategy for global analysis of surface functionality (GASF) in living cells. In total, we quantified 2639 cell surface lysines in Hela cell and several hundred residues with high reactivity were discovered, which represents the largest dataset of surface functional lysine sites to date. We discovered and validated that hyper-reactive lysine residues K382 on tyrosine kinase-like orphan receptor 2 (ROR2) and K285 on Endoglin (ENG/CD105) are at the protein interaction interface in co-crystal structures of protein complexes, emphasizing the broad potential functional consequences of cell surface lysines and GASF strategy is highly desirable for discovering new active and ligandable sites that can be functionally interrogated for drug discovery.

Inferring molecular inhibition potency with AlphaFold predicted structures.

Even though in silico drug ligand-based methods have been successful in predicting interactions with known target proteins, they struggle with new, unassessed targets. To address this challenge, we propose an approach that integrates structural data from AlphaFold 2 predicted protein structures into machine learning models. Our method extracts 3D structural protein fingerprints and combines them with ligand structural data to train a single machine learning model. This model captures the relationship between ligand properties and the unique structural features of various target proteins, enabling predictions for never before tested molecules and protein targets. To assess our model, we used a dataset of 144 Human G-protein Coupled Receptors (GPCRs) with over 140,000 measured inhibition constants (Ki) values. Results strongly suggest that our approach performs as well as state-of-the-art ligand-based methods. In a second modeling approach that used 129 targets for training and a separate test set of 15 different protein targets, our model correctly predicted interactions for 73% of targets, with explained variances exceeding 0.50 in 22% of cases. Our findings further verified that the usage of experimentally determined protein structures produced models that were statistically indistinct from the Alphafold synthetic structures. This study presents a proteo-chemometric drug screening approach that uses a simple and scalable method for extracting protein structural information for usage in machine learning models capable of predicting protein-molecule interactions even for orphan targets.

The protein composition of exosomes released by prostate cancer cells is distinctly regulated by androgen receptor-antagonists and -agonist to stimulate growth of target cells.

BACKGROUND: Prostate cancer (PCa) is a prevalent malignancy in men worldwide, ranking as the second leading cause of cancer-related death in Western countries. Various PCa hormone therapies, such as androgen receptor (AR)-antagonists or supraphysiological androgen level (SAL) reduce cancer cell proliferation. However, treated cells may influence the growth of neighboring cells through secreted exosomes in the tumor microenvironment (TME). Here, the change of protein content of exosomes secreted from PCa cells through treatment with different AR-antagonists or SAL has been analyzed. METHODS: Isolation of exosomes via ultracentrifugation of treated human PCa LNCaP cells with AR-agonist and various AR-antagonists; analysis of cellular senescence by detection of senescence associated beta galactosidase activity (SA ß-Gal); Western blotting and immunofluorescence staining; Mass spectrometry (MS-spec) of exosomes and bioinformatic analyses to identify ligand-specific exosomal proteins. Growth assays to analyze influence of exosomes on non-treated cells. RESULTS: MS-spec analysis identified ligand-specific proteins in exosomes. One thousand seventy proteins were up- and 52 proteins downregulated by SAL whereas enzalutamide upregulated 151 proteins and downregulated 42 exosomal proteins. The bioinformatic prediction indicates an up-regulation of pro-proliferative pathways. AR ligands augment hub factors in exosomes that include AKT1, CALM1, PAK2 and CTNND1. Accordingly, functional assays confirmed that the isolated exosomes from AR-ligand treated cells promote growth of untreated PCa cells. CONCLUSION: The data suggest that the cargo of exosomes is controlled by AR-agonist and -antagonists and distinct among the AR-antagonists. Further, exosomes promote growth that might influence the TME. This finding sheds light into the complex interplay between AR signaling and exosome-mediated communication between PCa cells.

In Silico and In Vitro multiple analysis approach for screening naturally derived ligands for red seabream aryl hydrocarbon receptor.

The aryl hydrocarbon receptor (AHR) is a key ligand-dependent transcription factor that mediates the toxic effects of compounds such as dioxin. Recently, natural ligands of AHR, including flavonoids, have been attracting physiological and toxicological attention as they have been reported to regulate major biological functions such as inflammation and anti-cancer by reducing the toxic effects of dioxin. Additionally, it is known that natural AHR ligands can accumulate in wildlife tissues, such as fish. However, studies in fish have investigated only a few ligands in experimental fish species, and the AHR response of marine fish to natural AHR ligands of various other structures has not been thoroughly investigated. To explore various natural AHR ligands in marine fish, which make up the most fish, it is necessary to develop new screening methods that consider the specificity of marine fish. In this study, we investigated the response of natural ligands by constructing in vitro and in silico experimental systems using red seabream as a model species. We attempted to develop a new predictive model to screen potential ligands that can induce transcriptional activation of red seabream AHR1 and AHR2 (rsAHR1 and rsAHR2). This was achieved through multiple analyses using in silico/ in vitro data and Tox21 big data. First, we constructed an in vitro reporter gene assay of rsAHR1 and rsAHR2 and measured the response of 10 representatives natural AHR ligands in COS-7 cells. The results showed that FICZ, Genistein, Daidzein, I3C, DIM, Quercetin and Baicalin induced the transcriptional activity of rsAHR1 and rsAHR2, while Resveratrol and Retinol did not induce the transcriptional activity of rsAHR isoforms. Comparing the EC50 values of the respective compounds in rsAHR1 and rsAHR2, FICZ, Genistein, and Daidzein exhibited similar isoform responses, but I3C, Baicalin, DIM and Quercetin show the isoform-specific responses. These results suggest that natural AHR ligands have specific profiling and transcriptional activity for each rsAHR isoform. In silico analysis, we constructed homology models of the ligand binding domains (LBDs) of rsAHR1 and rsAHR2 and calculated the docking energies (U_dock values) of natural ligands with measured in vitro transcriptional activity and dioxins reported in previous studies. The results showed a significant correlation (R2=0.74(rsAHR1), R2=0.83(rsAHR2)) between docking energy and transcriptional activity (EC50) value, suggesting that the homology model of rsAHR1 and rsAHR2 can be utilized to predict the potential transactivation of ligands. To broaden the applicability of the homology model to diverse compound structures and validate the correlation with transcriptional activity, we conducted additional analyses utilizing Tox21 big data. We calculated the docking energy values for 1860 chemicals in both rsAHR1 and rsAHR2, which were tested for transcriptional activation in Tox21 data against human AHR. By comparing the U_dock energy values between 775 active compounds and 1085 inactive compounds, a significant difference (p<0.001) was observed between the U_dock energy values in the two groups, suggesting that the U_dock value can be applied to distinguish the activation of compounds. Furthermore, we observed a significant correlation (R2=0.45) between the AC50 of Tox21 database and U_dock values of human AHR model. In conclusion, we calculated equations to translate the results of an in silico prediction model for ligand screening of rsAHR1 and rsAHR2 transactivation. This ligand screening model can be a powerful tool to quantitatively estimate AHR transactivation of major marine agents to which red seabream may be exposed. The study introduces a new screening approach for potential natural AHR ligands in marine fish, based on homology model-docking energy values of rsAHR1 and rsAHR2, with implications for future agonist development and applications bridging in silico and in vitro data.

Osteoprotegerin and receptor activator of the nuclear factor kappa B ligand (RANKL) in healthy pubertal girls - relationships with physical growth and classical bone turnover markers.

Osteoprotegerin (OPG) is a trap receptor for the receptor activator of the nuclear factor kappa B ligand (RANKL). We aimed to determine the OPG and free soluble RANKL (sRANKL) concentrations in girls during puberty and their relationships with pubertal stage, growth rate and serum concentrations of estradiol, as well as classical bone formation (N-terminal propeptide of type I collagen (PINP), bone-specific alkaline phosphatase (BALP), osteocalcin (OC)) and bone resorption (C-terminal telopeptide of type I collagen (CTX)) markers. The semi-longitudinal study involved 88 healthy girls, aged 11.8-13.2 years. Their weight and height were measured twice at one-year intervals. Pubertal stages were assessed using the Tanner (T) scale. Blood samples were taken at the first examination. Serum concentrations of OPG, sRANKL, CTX and BALP were determined by enzyme-linked immunosorbent assay, estradiol and PINP by radioimmunoassay and osteocalcin by immunoradiometric assay. The one-year increase in height and weight of girls in the T2 and T3 pubertal stages was greater than that of girls in the T4 stage (p=0.000, p<0.03). OPG concentrations (T2: 4.04±0.62; T3: 4.31±0.79; T4: 4.46±0.84 pmol/L) sRANKL concentrations (T2: 0.22 (IQR 0.09-0.54); T3: 0.42 (IQR 0.22-0.79); T4: 0.35 (IQR 0.16-1.04) pmol/L) and sRANKL/OPG ratios (T2: 0.05 (IQR 0.03-0.13); T3: 0.11 (IQR 0.05-0.19); T4: 0.09 (IQR 0.05-0.19) did not differ significantly between pubertal stages. Concentrations of PINP, CTX, BALP and OC were higher in girls at T3 stage than at the T4 stage (p=0.000, p=0.001, p=0.046, p=0.038; respectively). Concentrations of sRANKL and OPG did not correlate with body weight, height, growth rate, or concentrations of estradiol, PINP, CTX, BALP and OC. There were correlations between the increase in height over one year and the concentrations of PINP (r=0.499, p=0.000), CTX (r=0.311, p=0.003) and BALP (r=0.224, p=0.036), as well as of estradiol (r=-0.473, p=0.000). Unlike PINP, OC, BALP, CTX or estradiol concentrations, sRANKL and OPG concentrations do not change in girls during puberty. Neither OPG nor sRANKL concentrations correlate with somatic characteristics and classical bone turnover markers concentrations.

A novel mutation in the NR3C1 gene associated with reversible glucocorticoid resistance.

OBJECTIVE: Glucocorticoid resistance is a rare endocrine disease caused by variants of the NR3C1 gene encoding the glucocorticoid receptor (GR). We identified a novel heterozygous variant (GRR569Q) in a patient with uncommon reversible glucocorticoid resistance syndrome. METHODS: We performed ex vivo functional characterization of the variant in patient fibroblasts and in vitro through transient transfection in undifferentiated HEK 293T cells to assess transcriptional activity, affinity, and nuclear translocation. We studied the impact of the variant on the tertiary structure of the ligand-binding domain through 3D modeling. RESULTS: The patient presented initially with an adrenal adenoma with mild autonomous cortisol secretion and undetectable adrenocorticotropin hormone (ACTH) levels. Six months after surgery, biological investigations showed elevated cortisol and ACTH (urinary free cortisol 114 µg/24 h, ACTH 10.9 pmol/L) without clinical symptoms, evoking glucocorticoid resistance syndrome. Functional characterization of the GRR569Q showed decreased expression of target genes (in response to 100 nM cortisol: SGK1 control +97% vs patient +20%, P < .0001) and impaired nuclear translocation in patient fibroblasts compared to control. Similar observations were made in transiently transfected cells, but higher cortisol concentrations overcame glucocorticoid resistance. GRR569Q showed lower ligand affinity (Kd GRWT: 1.73 nM vs GRR569Q: 4.61 nM). Tertiary structure modeling suggested a loss of hydrogen bonds between H3 and the H1-H3 loop. CONCLUSION: This is the first description of a reversible glucocorticoid resistance syndrome with effective negative feedback on corticotroph cells regarding increased plasma cortisol concentrations due to the development of mild autonomous cortisol secretion.

A division-of-labor mode contributes to the cardioprotective potential of mesenchymal stem/stromal cells in heart failure post myocardial infarction.

Background: Treatment of heart failure post myocardial infarction (post-MI HF) with mesenchymal stem/stromal cells (MSCs) holds great promise. Nevertheless, 2-dimensional (2D) GMP-grade MSCs from different labs and donor sources have different therapeutic efficacy and still in a low yield. Therefore, it is crucial to increase the production and find novel ways to assess the therapeutic efficacy of MSCs. Materials and methods: hUC-MSCs were cultured in 3-dimensional (3D) expansion system for obtaining enough cells for clinical use, named as 3D MSCs. A post-MI HF mouse model was employed to conduct in vivo and in vitro experiments. Single-cell and bulk RNA-seq analyses were performed on 3D MSCs. A total of 125 combination algorithms were leveraged to screen for core ligand genes. Shinyapp and shinycell workflows were used for deploying web-server. Result: 3D GMP-grade MSCs can significantly and stably reduce the extent of post-MI HF. To understand the stable potential cardioprotective mechanism, scRNA-seq revealed the heterogeneity and division-of-labor mode of 3D MSCs at the cellular level. Specifically, scissor phenotypic analysis identified a reported wound-healing CD142+ MSCs subpopulation that is also associated with cardiac protection ability and CD142- MSCs that is in proliferative state, contributing to the cardioprotective function and self-renewal, respectively. Differential expression analysis was conducted on CD142+ MSCs and CD142- MSCs and the differentially expressed ligand-related model was achieved by employing 125 combination algorithms. The present study developed a machine learning predictive model based on 13 ligands. Further analysis using CellChat demonstrated that CD142+ MSCs have a stronger secretion capacity compared to CD142- MSCs and Flow cytometry sorting of the CD142+ MSCs and qRT-PCR validation confirmed the significant upregulation of these 13 ligand factors in CD142+ MSCs. Conclusion: Clinical GMP-grade 3D MSCs could serve as a stable cardioprotective cell product. Using scissor analysis on scRNA-seq data, we have clarified the potential functional and proliferative subpopulation, which cooperatively contributed to self-renewal and functional maintenance for 3D MSCs, named as "division of labor" mode of MSCs. Moreover, a ligand model was robustly developed for predicting the secretory efficacy of MSCs. A user-friendly web-server and a predictive model were constructed and available (https://wangxc.shinyapps.io/3D_MSCs/).

Resonance Raman study of oxoiron(IV) porphyrin π-cation radical complex: Porphyrin ligand effect on ν(Fe=O) frequency.

Resonance Raman (rR) spectroscopy has been applied to study the nature of the iron-oxo (Fe=O) moiety of oxoiron(IV) porphyrin π-cation radical complex (CompI). While the axial ligand effect on the nature of the Fe=O moiety has been studied with rR spectroscopy, the porphyrin ligand effect has not been studied well. Here, we investigated the porphyrin ligand effect on the Fe=O moiety with rR spectroscopy. The porphyrin ligand effect was modulated by the electron-withdrawing effect of the porphyrin substituent at the meso-position. This study shows that the frequency of the Fe=O stretching band, ν(Fe=O), hardly change even when the electron-withdrawing effect of the porphyrin substituent changes. This result is further supported by theoretical calculation of CompI. The natural atomic charge analysis reveals that the oxo and axial ligands work to buffer the electron-withdrawing effect of the porphyrin substituent. The electron-withdrawing porphyrin substituent shifts an electron population from the ferryl iron to the porphyrin, but the decreased electron population on the ferryl iron is compensated by the shift of the electron population from the oxo ligand and the axial ligand. The shift of the electron population makes the Fe-axial ligand bond length short, but the Fe=O bond length unchanged, resulting in the invariable ν(Fe=O) frequency.

Affinity chromatography for virus-like particle manufacturing: Challenges, solutions, and perspectives.

The increasing medical application of virus-like particles (VLPs), notably vaccines and viral vectors, has increased the demand for commercial VLP production. However, VLP manufacturing has not yet reached the efficiency level achieved for recombinant protein therapeutics, especially in downstream processing. This review provides a comprehensive analysis of the challenges associated with affinity chromatography for VLP purification with respect to the diversity and complexity of VLPs and the associated upstream and downstream processes. The use of engineered affinity ligands and matrices for affinity chromatography is first discussed. Although several representative affinity ligands are currently available for VLP purification, most of them have difficulty in balancing ligand universality, ligand selectivity and mild operation conditions. Then, phage display technology and computer-assisted design are discussed as efficient methods for the rapid discovery of high-affinity peptide ligands. Finally, the VLP purification by affinity chromatography is analyzed. The process is significantly influenced by virus size and variation, ligand type and chromatographic mode. To address the updated regulatory requirements and epidemic outbreaks, technical innovations in affinity chromatography and process intensification and standardization in VLP purification should be promoted to achieve rapid process development and highly efficient VLP manufacturing, and emphasis is given to the discovery of universal ligands, applications of gigaporous matrices and platform technology. It is expected that the information in this review can provide a better understanding of the affinity chromatography methods available for VLP purification and offer useful guidance for the development of affinity chromatography for VLP manufacturing in the decades to come.

Supramolecular Mimotope Peptide Nanofibers Promote Antibody-Ligand Polyvalent and Instantaneous Recognition for Biopharmaceutical Analysis.

Peptide-based supramolecules exhibit great potential in various fields due to their improved target recognition ability and versatile functions. However, they still suffer from numerous challenges for the biopharmaceutical analysis, including poor self-assembly ability, undesirable ligand-antibody binding rates, and formidable target binding barriers caused by ligand crowding. To tackle these issues, a "polyvalent recognition" strategy employing the CD20 mimotope peptide derivative NBD-FFVLR-GS-WPRWLEN (acting on the CDR domains of rituximab) was proposed to develop supramolecular nanofibers for target antibody recognition. These nanofibers exhibited rapid self-assembly within only 1 min and robust stability. Their binding affinity (179 nM) for rituximab surpassed that of the monomeric peptide (7 µM) by over 38-fold, highlighting that high ligand density and potential polyvalent recognition can efficiently overcome the target binding barriers of traditional supramolecules. Moreover, these nanofibers exhibited an amazing "instantaneous capture" rate (within 15 s), a high recovery (93 ± 3%), and good specificity for the target antibody. High-efficiency enrichment of rituximab was achieved from cell culture medium with good recovery and reproducibility. Intriguingly, these peptide nanofibers combined with bottom-up proteomics were successful in tracking the deamidation of asparagine 55 (from 10 to 16%) on the rituximab heavy chain after 21 day incubation in human serum. In summary, this study may open up an avenue for the development of versatile mimotope peptide supramolecules for biorecognition and bioanalysis of biopharmaceuticals.