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Accelerated discovery of superoxide-dismutase nanozymes via high-throughput computational screening.

ABSTRACT: The activity of nanomaterials (NMs) in catalytically scavenging superoxide anions mimics that of superoxide dismutase (SOD). Although dozens of NMs have been demonstrated to possess such activity, the underlying principles are unclear, hindering the discovery of NMs as the novel SOD mimics. In this work, we use density functional theory calculations to study the thermodynamics and kinetics of the catalytic processes, and we develop two principles, namely, an energy level principle and an adsorption energy principle, for the activity. The first principle quantitatively describes the role of the intermediate frontier molecular orbital in transferring electrons for catalysis. The second one quantitatively describes the competition between the desired catalytic reaction and undesired side reactions. The ability of the principles to predict the SOD-like activities of metal-organic frameworks were verified by experiments. Both principles can be easily implemented in computer programs to computationally screen NMs with the intrinsic SOD-like activity.

SUBMITTER: Wang Z

PROVIDER: S-EPMC8616946 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

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Accelerated discovery of superoxide-dismutase nanozymes via high-throughput computational screening.

Wang Zhenzhen Z Wu Jiangjiexing J Zheng Jia-Jia JJ Shen Xiaomei X Yan Liang L Wei Hui H Gao Xingfa X Zhao Yuliang Y

Nature communications 20211125 1

The activity of nanomaterials (NMs) in catalytically scavenging superoxide anions mimics that of superoxide dismutase (SOD). Although dozens of NMs have been demonstrated to possess such activity, the underlying principles are unclear, hindering the discovery of NMs as the novel SOD mimics. In this work, we use density functional theory calculations to study the thermodynamics and kinetics of the catalytic processes, and we develop two principles, namely, an energy level principle and an adsorpt ...[more]

PMID: 34824234

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Project description: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.

Dataset Information

Accelerated discovery of superoxide-dismutase nanozymes via high-throughput computational screening.

Publications

Accelerated discovery of superoxide-dismutase nanozymes via high-throughput computational screening.

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