Stereoisomeric Pam2CS based TLR2 agonists: synthesis, structural modelling and activity as vaccine adjuvants.

Lipopeptides including diacylated Pam2CSK4 as well as triacylated Pam3CSK4 act as ligands of toll-like receptor (TLR)-2, a promising target for the development of vaccine adjuvants. The highly investigated Pam2CSK4 and Pam3CSK4, despite their aqueous solubility have not performed well as vaccine adjuvants which may be attributable to potential denaturation of protein antigens by these cationic surfactant-like lipopeptides. In the present investigation, we synthesized (R), (S) and racemic Pam2CS(OMe) analogs and their N-acetyl derivatives without the tetralysine component to systematically investigate the effect of stereochemistry at the thio-glycerol lipopeptide core of these lipopeptide based TLR2 agonists. The resulting compounds were compared using TLR2 reporter cell-based assays and the ability of the synthesized lipopeptides to stimulate cytokine production (IL-6, IL-10 and TNF-α) by freshly collected human PBMCs and CD40 and CD86 expressions by mouse spleen cells was also investigated. Notably, few synthesized lipopeptides were found to be potent TLR2/6 agonists, inducing cytokine production and upregulating CD40 and CD86 expressions. The TLR2/6 agonistic lipopeptides were further assessed for vaccine adjuvant effects in mice. The results confirmed that the R-stereochemistry at the thio-glycerol lipopeptide core was preferred for maximal TLR2/6 activity, as reflected in Th1 immune deviation, higher antibody levels and enhanced vaccine protection against a lethal influenza challenge.

Toll-like receptor-7/8 agonist kill Leishmania amazonensis by acting as pro-oxidant and pro-inflammatory agent.

OBJECTIVES: Evaluation of the anti-Leishmanial activity of imidazoquinoline-based TLR7/8 agonists. METHODS: TLR7/8-active imidazoquinolines (2 and 3) were synthesized and assessed for activity against Leishmania amazonensis-intracellular amastigotes using mouse peritoneal macrophages. The production of reactive oxygen species (ROS), nitric oxide (NO) and cytokines was determined in infected and non-infected macrophages. KEY FINDINGS: The imidazoquinolines, 2 and 3, were primarily agonists of TLR7 with compound 3 also showing modest TLR8 activity. Docking studies showed them to occupy the same binding pocket on TLR7 and 8 as the known agonists, imiquimod and resiquimod. Compounds 2 and 3 inhibited the growth of L. amazonensis-intracellular amastigotes with the most potent compound (3, IC50 = 5.93 µM) having an IC50 value close to miltefosine (IC50 = 4.05 µM), a known anti-Leishmanial drug. Compound 3 induced macrophages to produce ROS, NO and inflammatory cytokines that likely explain the anti-Leishmanial effects. CONCLUSIONS: This study shows that activating TLR7 using compounds 2 or 3 induces anti-Leishmanial activity associated with induction of free radicals and inflammatory cytokines able to kill the parasites. While 2 and 3 had a very narrow cytotoxicity window for macrophages, this identifies the possibility to further develop this chemical scaffold to less cytotoxic TLR7/8 agonist for potential use as anti-Leishmanial drug.

BBIQ, a pure TLR7 agonist, is an effective influenza vaccine adjuvant.

Better adjuvants are needed for vaccines against seasonal influenza. TLR7 agonists are potent activators of innate immune responses and thereby may be promising adjuvants. Among the imidazoquinoline compounds, 1-benzyl-2-butyl-1H-imidazo[4,5-c]quinolin-4-amine (BBIQ) was reported to be a highly active TLR7 agonist but has remained relatively unexplored because of its commercial unavailability. Indeed, in silico molecular modeling studies predicted that BBIQ had a higher TLR7 docking score and binding free energy than imiquimod, the gold standard TLR7 agonist. To circumvent the availability issue, we developed an improved and higher yield method to synthesize BBIQ. Testing BBIQ on human and mouse TLR7 reporter cell lines confirmed it to be TLR7 specific with significantly higher potency than imiquimod. To test its adjuvant potential, BBIQ or imiquimod were admixed with recombinant influenza hemagglutinin protein and administered to mice as two intramuscular immunizations 2 weeks apart. Serum anti-influenza IgG responses assessed by ELISA 2 weeks after the second immunization confirmed that the mice that received vaccine admixed with BBIQ had significantly higher anti-influenza IgG1 and IgG2c responses than mice immunized with antigen alone or admixed with imiquimod. This confirmed BBIQ to be a TLR7-specific adjuvant able to enhance humoral immune responses.

Prediction of novel mouse TLR9 agonists using a random forest approach.

BACKGROUND: Toll-like receptor 9 is a key innate immune receptor involved in detecting infectious diseases and cancer. TLR9 activates the innate immune system following the recognition of single-stranded DNA oligonucleotides (ODN) containing unmethylated cytosine-guanine (CpG) motifs. Due to the considerable number of rotatable bonds in ODNs, high-throughput in silico screening for potential TLR9 activity via traditional structure-based virtual screening approaches of CpG ODNs is challenging. In the current study, we present a machine learning based method for predicting novel mouse TLR9 (mTLR9) agonists based on features including count and position of motifs, the distance between the motifs and graphically derived features such as the radius of gyration and moment of Inertia. We employed an in-house experimentally validated dataset of 396 single-stranded synthetic ODNs, to compare the results of five machine learning algorithms. Since the dataset was highly imbalanced, we used an ensemble learning approach based on repeated random down-sampling. RESULTS: Using in-house experimental TLR9 activity data we found that random forest algorithm outperformed other algorithms for our dataset for TLR9 activity prediction. Therefore, we developed a cross-validated ensemble classifier of 20 random forest models. The average Matthews correlation coefficient and balanced accuracy of our ensemble classifier in test samples was 0.61 and 80.0%, respectively, with the maximum balanced accuracy and Matthews correlation coefficient of 87.0% and 0.75, respectively. We confirmed common sequence motifs including 'CC', 'GG','AG', 'CCCG' and 'CGGC' were overrepresented in mTLR9 agonists. Predictions on 6000 randomly generated ODNs were ranked and the top 100 ODNs were synthesized and experimentally tested for activity in a mTLR9 reporter cell assay, with 91 of the 100 selected ODNs showing high activity, confirming the accuracy of the model in predicting mTLR9 activity. CONCLUSION: We combined repeated random down-sampling with random forest to overcome the class imbalance problem and achieved promising results. Overall, we showed that the random forest algorithm outperformed other machine learning algorithms including support vector machines, shrinkage discriminant analysis, gradient boosting machine and neural networks. Due to its predictive performance and simplicity, the random forest technique is a useful method for prediction of mTLR9 ODN agonists.

Influenza immunization during pregnancy: Benefits for mother and infant.

The serious consequences of influenza infection during pregnancy have been recognized for almost a century. In this article, we reviewed the evidence on the immunogenicity, safety and impact of maternal influenza immunization for both mother and child. After vaccination, pregnant women have similar protective titers of anti-influenza antibodies as non-pregnant women, demonstrating that pregnancy does not alter the trivalent inactivated influenza vaccine immune response. Studies from the United States, Europe and resource-constrained regions demonstrate that maternal vaccination is associated with increased anti-influenza antibody concentrations and protection in the newborn child as well as the immunized mother. Given the acceptable safety profile of influenza vaccines and the World Health Organization's recommendation for its use in pregnant women, maternal vaccination with inactivated influenza vaccine is a cost-effective approach to decrease influenza disease in newborns. However, as seen for influenza immunization in the elderly, the protective efficacy of current inactivated vaccines in protection of newborns is 50% at best, indicating significant room for vaccine improvement, which could potentially be achieved by addition of a safe and effective adjuvant. Thus, global deployment of inactivated influenza immunization during pregnancy would have substantial and measurable health benefits for mothers and their newborns.