Small Molecule NF-kB Inhibitors as Immune Potentiators for Enhancement of Vaccine Adjuvants

Moser, Brittany; Escalante-Buendia, Yoseline; Steinhardt, Rachel C.; Rosenberger, Matthew G.; Cassaidy, Britteny; Naorem, Nihesh; Chon, Alfred C.; Nguyen, M. Hong; Tran, Ngoctran; Esser‐Kahn, Aaron P.

doi:10.26434/chemrxiv.10043138

Cited by 2 publications

(4 citation statements)

References 8 publications

(8 reference statements)

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“…18 Although these adjuvants can be potent activators of immune responses, a well-known limitation of current popular adjuvants is excessive and uncontrolled inammation. 1,11,19 This has motivated efforts to discover novel adjuvants with reduced inammation proles, 20,21 but it has proved challenging to develop novel PRR agonists capable of specically tuning the level of stimulation in inammatory pathways without disrupting the desired stimulation along immune activation pathways.…”

Section: Introductionmentioning

confidence: 99%

“…20 As compared to peptides like SN50, small molecules present attractive candidates for immunomodulators due to their better synthetic accessibility and reduced potential for immunogenicity. To this end, Moser et al 21 also demonstrated that a small molecule NF-kB inhibitor honokiol and its derivatives can be used as immunomodulators with similar functions to SN50. More recently, we conducted a targeted experimental screen of a small molecule library of ∼3000 compounds, many of which were known to inuence the immune system, to discover, aer removing cytotoxic compounds using the same viability lter as applied in the present study, novel molecules capable of suppressing NF-kB activity by up to 9-fold, elevating NF-kB activity by up to 7-fold and elevating IRF activity by up to 7-fold.…”

Section: Introductionmentioning

confidence: 99%

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Data-driven discovery of innate immunomodulators via machine learning-guided high throughput screening

Tang,

Kim,

et al. 2023

Chem. Sci.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Data-driven discovery of innate immunomodulators via machine learning-guided high throughput screening

Tang,

Kim,

et al. 2023

Chem. Sci.

View full text Add to dashboard Cite

show abstract

“…18 Although these adjuvants can be potent activators of immune responses, a well-known limitation of current popular adjuvants is excessive and uncontrolled inflammation. 1,11,19 This has motivated efforts to discover novel adjuvants with reduced inflammation profiles, 20,21 but it has proved challenging to develop novel PRR agonists capable of specifically tuning the level of stimulation in inflammatory pathways without disrupting the desired stimulation along immune activation pathways.…”

Section: Introductionmentioning

confidence: 99%

“…20 As compared to peptides like SN50, small molecules present attractive candidates for immunomodulators due to their better synthetic accessibility and reduced potential for immunogenicity. To this end, Moser et al 21 also demonstrated that a small molecule NF-κB inhibitor honokiol and its derivatives can be used as immunomodulators with similar functions to SN50. More recently, we conducted a targeted experimental screen of a small molecule library of ∼3000 compounds, many of which were known to influence the immune system, to discover, after removing cytotoxic compounds using the same viability filter as applied in this study, novel molecules capable of suppressing NF-κB activity by up to 9-fold, elevating NF-κB activity by up to 7-fold and elevating IRF activity by up to 7-fold.…”

Section: Introductionmentioning

confidence: 99%

Data-driven discovery of innate immunomodulators via machine learning-guided high throughput screening

Tang

Kim

et al. 2023

Preprint

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The innate immune response is vital for the success of prophylactic vaccines and immunotherapies. Control of signaling in innate immune pathways can improve prophylactic vaccines by inhibiting unfavorable systemic inflammation and immunotherapies by enhancing immune stimulation. In this work, we developed a machine learning-enabled active learning pipeline to guide in vitro experimental screening and discovery of small molecule immunomodulators that improve immune responses by altering the signaling activity of innate immune responses stimulated by traditional pattern recognition receptor agonists. Molecules were tested by in vitro high throughput screening (HTS) where we measured modulation of the nuclear factor κ-light-chain-enhancer of activated B-cells (NF-κB) and the interferon regulatory factors (IRF) pathways. These data were used to train data-driven predictive models linking molecular structure to modulation of the NF-κB and IRF responses using deep representational learning, Gaussian process regression, and Bayesian optimization. By interleaving successive rounds of model training and in vitro HTS, we performed an active learning-guided traversal of a 139,998 molecule library. After sampling only ~2% of the library, we discovered viable molecules with unprecedented immunomodulatory capacity, including those capable of suppressing NF-κB activity by up to 15-fold, elevating NF-κB activity by up to 5-fold, and elevating IRF activity by up to 6-fold. We extracted chemical design rules identifying particular chemical fragments as principal drivers of specific immunomodulation behaviors. We validated the immunomodulatory effect of a subset of our top candidates by measuring cytokine release profiles. Of these, one molecule induced a 3-fold enhancement in IFN-β production when delivered with a cyclic di-nucleotide stimulator of interferon genes (STING) agonist. In sum, our machine learning-enabled screening approach presents an efficient immunomodulator discovery pipeline that has furnished a library of novel small molecules with a strong capacity to enhance or suppress innate immune signaling pathways to shape and improve prophylactic vaccination and immunotherapies.

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Small Molecule NF-kB Inhibitors as Immune Potentiators for Enhancement of Vaccine Adjuvants

Cited by 2 publications

References 8 publications

Data-driven discovery of innate immunomodulators via machine learning-guided high throughput screening

Data-driven discovery of innate immunomodulators via machine learning-guided high throughput screening

Data-driven discovery of innate immunomodulators via machine learning-guided high throughput screening

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