Reconfigurable Peptide Analogs of Apolipoprotein A-I Reveal Tunable Features of Nanodisc Assembly.

Nanodisc (ND)-forming membrane scaffold proteins or peptides developed from apolipoprotein A-I (apoA-I) have led to considerable promise in structural biology and therapeutic applications. However, the rationale and regularity characteristics in peptide sequence design remain inconclusive. Here, we proposed a consensus-based normalization approach through the reversed engineering of apoA-IΔ1-45 to design reconfigurable apoA-I peptide analogs (APAs) for tunable ND assembly. We present extensive morphological validations and computational simulation analyses on divergent APA-NDs that are generated by our method. Fifteen divergent APAs were generated accordingly to study the assembly machinery of NDs. We show that APA designs exhibit multifactorial influence in terms of varying APA tandem repeats, sequence composition, and lipid-to-APA ratio to form tunable diameters of NDs. There is a strong positive correlation between DMPC-to-APA ratios and ND diameters. Longer APA with more tandem repeats tends to yield higher particle size homogeneity. Our results also suggest proline is a dispensable residue for the APA-ND formation. Interestingly, proline-rich substitution not only provides an inward-bending effect in forming smaller NDs but also induces the cumulative chain flexibility that enables larger ND formation at higher lipid ratios. Additionally, proline-tryptophan residues in APAs play a dominant role in forming larger NDs. Molecular simulation shows that enriched basic and acidic residues in APAs evoke abundant hydrogen-bond and salt bridge networks to reinforce the structural stability of APA-NDs. Together, our findings provide a rational basis for understanding APA design. The proposed model could be extended to other apolipoproteins for desired ND engineering.

Melittin Tryptophan Substitution with a Fluorescent Amino Acid Reveals the Structural Basis of Selective Antitumor Effect and Subcellular Localization in Tumor Cells.

Melittin is a membrane-active peptide with strong anticancer activity against various cancers. Despite decades of research, the role of the singular Trp in the anticancer activity and selectivity of melittin remains poorly understood. Here, we propose a theranostic solution based on the substitution of Trp19 with a noncanonical fluorescent amino acid (DapAMCA). The introduction of DapAMCA residue in melittin stabilized the helical structure of the peptide, as evaluated by circular dichroism spectra and molecular dynamics simulations. In vitro hemolytic and anticancer activity assays revealed that introducing DapAMCA residue in melittin changed its mode of action with the cell membrane, resulting in reduced hemolytic toxicity and an improved the selectivity index (SI), with up to a five-fold increase compared to melittin. In vitro fluorescence imaging of DapAMCA-labeled melittin (MELFL) in cancer cells demonstrated high membrane-penetrating activity, with strong nuclear and nucleolar localization ability. These findings provide implications for novel anticancer therapies based on Trp-substituted designs and nuclear/nucleolar targeted therapy.

An in Silico Approach to Reveal the Nanodisc Formulation of Doxorubicin.

Molecular dynamic behaviors of nanodisc (ND) formulations of free doxorubicin (DOX) and DOX conjugated lipid prodrug molecules were investigated by molecular dynamics (MD) simulations. We have unveiled how formulation design affects the drug release profile and conformational stability of ND assemblies. Our simulation results indicate that free DOX molecules loaded in the ND system experienced rapid dissociation due to the unfavorable orientation of DOX attached to the lipid surface. It is found that DOX tends to form aggregates with higher drug quantities. In contrast, lipidated DOX-prodrugs incorporated in ND formulations exhibited sufficient ND conformational stability. The drug loading capacity is dependent on the type of lipid molecules grafted on the DOX-prodrug, and the drug loading quantities in a fixed area of NDs follow the order: DOX-BMPH-MP > DOX-BMPH-TC > DOX-BMPH-PTE. To gain further insight into the dynamic characteristics of ND formulations governed by different kinds of lipidation, we investigated the conformational variation of ND components, intermolecular interactions, the solvent accessible surface area, and individual MSP1 residue flexibility. We found that the global conformational stability of DOX-prodrug-loaded ND assemblies is influenced by the molecular flexibility and lipidated forms of DOX-prodrug. We also found that the spontaneous self-aggregation of DOX-prodrugs with increasing quantities on ND could reduce the membrane fluidity and enhance the conformational stability of ND formulations.

Nano-bio interfaces effect of two-dimensional nanomaterials and their applications in cancer immunotherapy.

The field of two-dimensional (2D) nanomaterial-based cancer immunotherapy combines research from multiple subdisciplines of material science, nano-chemistry, in particular nano-biological interactions, immunology, and medicinal chemistry. Most importantly, the "biological identity" of nanomaterials governed by bio-molecular corona in terms of bimolecular types, relative abundance, and conformation at the nanomaterial surface is now believed to influence blood circulation time, bio-distribution, immune response, cellular uptake, and intracellular trafficking. A better understanding of nano-bio interactions can improve utilization of 2D nano-architectures for cancer immunotherapy and immunotheranostics, allowing them to be adapted or modified to treat other immune dysregulation syndromes including autoimmune diseases or inflammation, infection, tissue regeneration, and transplantation. The manuscript reviews the biological interactions and immunotherapeutic applications of 2D nanomaterials, including understanding their interactions with biological molecules of the immune system, summarizes and prospects the applications of 2D nanomaterials in cancer immunotherapy.

De novo Design of G Protein-Coupled Receptor 40 Peptide Agonists for Type 2 Diabetes Mellitus Based on Artificial Intelligence and Site-Directed Mutagenesis.

G protein-coupled receptor 40 (GPR40), one of the G protein-coupled receptors that are available to sense glucose metabolism, is an attractive target for the treatment of type 2 diabetes mellitus (T2DM). Despite many efforts having been made to discover small-molecule agonists, there is limited research focus on developing peptides acting as GPR40 agonists to treat T2DM. Here, we propose a novel strategy for peptide design to generate and determine potential peptide agonists against GPR40 efficiently. A molecular fingerprint similarity (MFS) model combined with a deep neural network (DNN) and convolutional neural network was applied to predict the activity of peptides constructed by unnatural amino acids (UAAs). Site-directed mutagenesis (SDM) further optimized the peptides to form specific favorable interactions, and subsequent flexible docking showed the details of the binding mechanism between peptides and GPR40. Molecular dynamics (MD) simulations further verified the stability of the peptide-protein complex. The R-square of the machine learning model on the training set and the test set reached 0.87 and 0.75, respectively; and the three candidate peptides showed excellent performance. The strategy based on machine learning and SDM successfully searched for an optimal design with desirable activity comparable with the model agonist in phase III clinical trials.