Discovery of Self-Assembling Small Molecules as Vaccine Adjuvants

Identification of a Self-Assembling Small-Molecule Cancer Vaccine Adjuvant with an Improved Toxicity Profile

Protein or peptide cancer vaccines usually include immune potentiators, so-called adjuvants. However, it remains challenging to identify structurally simple, chemically accessible synthetic molecules that are effective and safe as vaccine adjuvant. Here, we present cholicamideβ (6), a self-assembling small-molecule vaccine adjuvant with an improved toxicity profile and proven efficacy in vivo. We demonstrate that cholicamideβ (6), which is less cytotoxic than its parent compound, forms virus-like particles to potently activate dendritic cells with the concomitant secretion of cytokines. When combined with a peptide antigen, cholicamideβ (6) potentiated the antigen presentation on dendritic cells to induce antigen-specific T cells. As a therapeutic cancer vaccine adjuvant in mice, a mixture of cholicamideβ (6) and a peptide antigen protected mice from the challenges of malignant cancer cells without overt toxicity. Cholicamideβ (6) may offer a translational opportunity as an unprecedented class of small-molecule cancer vaccine adjuvants.

Development of synthetic, self-adjuvanting, and self-assembling anticancer vaccines based on a minimal saponin adjuvant and the tumor-associated MUC1 antigen

The overexpression of aberrantly glycosylated tumor-associated mucin-1 (TA-MUC1) in human cancers makes it a major target for the development of anticancer vaccines derived from synthetic MUC1-(glyco)peptide antigens. However, glycopeptide-based subunit vaccines are weakly immunogenic, requiring adjuvants and/or additional immunopotentiating approaches to generate optimal immune responses. Among these strategies, unimolecular self-adjuvanting vaccine constructs that do not need coadministration of adjuvants or conjugation to carrier proteins emerge as a promising but still underexploited approach. Herein, we report the design, synthesis, immune-evaluation in mice, and NMR studies of new, self-adjuvanting and self-assembling vaccines based on our QS-21-derived minimal adjuvant platform covalently linked to TA-MUC1-(glyco)peptide antigens and a peptide helper T-cell epitope. We have developed a modular, chemoselective strategy that harnesses two distal attachment points on the saponin adjuvant to conjugate the respective components in unprotected form and high yields via orthogonal ligations. In mice, only tri-component candidates but not unconjugated or di-component combinations induced significant TA-MUC1-specific IgG antibodies able to recognize the TA-MUC1 on cancer cells. NMR studies revealed the formation of self-assembled aggregates, in which the more hydrophilic TA-MUC1 moiety gets exposed to the solvent, favoring B-cell recognition. While dilution of the di-component saponin-(Tn)MUC1 constructs resulted in partial aggregate disruption, this was not observed for the more stably-organized tri-component candidates. This higher structural stability in solution correlates with their increased immunogenicity and suggests a longer half-life of the construct in physiological media, which together with the enhanced antigen multivalent presentation enabled by the particulate self-assembly, points to this self-adjuvanting tri-component vaccine as a promising synthetic candidate for further development.

Formulation and Evaluation of Lipidized Imiquimod as an Effective Adjuvant

Adjuvants are essential for the induction of robust immune responses against vaccine antigens. Small-molecule TLR7 agonists hold high potential for this purpose. In this communication, imiquimod (IMQ) bearing a cholesterol lipid moiety derivative, IMQ-Chol, was designed and synthesized as a vaccine adjuvant, which could release parent IMQ molecules in aqueous conditions via amide bond hydrolysis. We performed a series of immunological evaluations by cooperating with the inactivated foot-and-mouth disease virus (FMDV). All of the results confirmed that IMQ-Chol could stimulate the body for a prolonged time to produce strong humoral and cellular immunity with a balanced Th1/Th2 immune response through a TLR7-related MAPK pathway. In addition, the results of the proof-of-concept vaccine indicated IMQ-Chol had a good effect on preventing and treating FMD in pigs.

Machine Learning-Assisted Screening of Herbal Medicine Extracts as Vaccine Adjuvants

Adjuvants are important vaccine components, composed of a variety of chemical and biological materials that enhance the vaccine antigen-specific immune responses by stimulating the innate immune cells in both direct and indirect manners to produce a variety cytokines, chemokines, and growth factors. It has been developed by empirical methods for decades and considered difficult to choose a single screening method for an ideal vaccine adjuvant, due to their diverse biochemical characteristics, complex mechanisms of, and species specificity for their adjuvanticity. We therefore established a robust adjuvant screening strategy by combining multiparametric analysis of adjuvanticity in vivo and immunological profiles in vitro (such as cytokines, chemokines, and growth factor secretion) of various library compounds derived from hot-water extracts of herbal medicines, together with their diverse distribution of nano-sized physical particle properties with a machine learning algorithm. By combining multiparametric analysis with a machine learning algorithm such as rCCA, sparse-PLS, and DIABLO, we identified that human G-CSF and mouse RANTES, produced upon adjuvant stimulation in vitro, are the most robust biological parameters that can predict the adjuvanticity of various library compounds. Notably, we revealed a certain nano-sized particle population that functioned as an independent negative parameter to adjuvanticity. Finally, we proved that the two-step strategy pairing the negative and positive parameters significantly improved the efficacy of screening and a screening strategy applying principal component analysis using the identified parameters. These novel parameters we identified for adjuvant screening by machine learning with multiple biological and physical parameters may provide new insights into the future development of effective and safe adjuvants for human use.

Discovery of a Phase-Separating Small Molecule That Selectively Sequesters Tubulin in Cells

Phase-separated membraneless organelles or biomolecular condensates play diverse functions in cells, however recapturing their characteristics using small organic molecules has been a challenge. In the present study, cell-lysate-based screening of 843 self-assembling small molecules led to the discovery of a simple organic molecule, named huezole, that forms liquid droplets to selectively sequester tubulin. Remarkably, this small molecule enters cultured human cells and prevents cell mitosis by forming tubulin-concentrating condensates in cells. The present study demonstrates the feasibility of producing a synthetic condensate out of non-peptidic small molecules for exogenous control of cellular processes. The modular structure of huezole provides a framework for designing a class of organelle-emulating small molecules.

A non-peptidic small molecule, R-huezole, phase separates to selectively sequester tubulin proteins to control the cell cycle. Its modular structure provides a framework for designing bioactive molecules to mimic membraneless organelles in cells.

Self-assembling small-molecule adjuvants as antigen nano-carriers

Nano-carrier adjuvant for antigens: the co-delivery of antigens and adjuvants and the high degree of antigen presentation are achieved by conjugating peptide antigens with cholicamide, a self-assembling small molecule adjuvant.

Amino acid sequence determines the adjuvant potency of a D-Tetra-Peptide hydrogel

The development of novel vaccine adjuvants is essential for the production of modern vaccines against infectious agents and cancer. We recently reported a supramolecular hydrogel of a self-assembling D-tetra-peptide named...