Small, volume 18, issue 12, pages 2105673
DiZyme: Open‐Access Expandable Resource for Quantitative Prediction of Nanozyme Catalytic Activity
Publication type: Journal Article
Publication date: 2022-01-14
General Chemistry
Biotechnology
General Materials Science
Biomaterials
Abstract
Enzymes suffer from high cost, complex purification, and low stability. Development of low-cost artificial enzymes of comparative or higher effectiveness is desired. Given its complexity, it is desired to presume their activities prior to experiments. While computational approaches demonstrate success in modeling nanozyme activities, they require assumptions about the system to be made. Machine learning (ML) is an alternative approach towards data-driven material property prediction achieving high performance even on multicomponent complex systems. Despite the growing demand for customized nanozymes, there is no open access nanozyme database. Here, a user-friendly expandable database of >300 existing inorganic nanozymes is developed by data collection from >100 articles. Data analysis is performed to reveal the features responsible for catalytic activities of nanozymes, and new descriptors are proposed for its ML-assisted prediction. A random forest regression (RFR) model for evaluation of nanozyme peroxidase activity is developed and optimized by correlation-based feature selection and hyperparameter tuning, achieving performance up to R2 = 0.796 for Kcat and R2 = 0.627 for Km . Experiment-confirmed unknown nanozyme activity prediction is also demonstrated. Moreover, the DiZyme expandable, open-access resource containing the database, predictive algorithm, and visualization tool is developed to boost novel nanozyme discovery worldwide (https://dizyme.net).
Citations by journals
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4
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Advanced Materials
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4 publications, 18.18%
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Small
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3 publications, 13.64%
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Nanoscale
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2 publications, 9.09%
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1 publication, 4.55%
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Nano Letters
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1 publication, 4.55%
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ACS Materials Letters
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1 publication, 4.55%
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Journal of Materials Chemistry B
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Journal of Materials Chemistry B
1 publication, 4.55%
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Analytical Chemistry
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Analytical Chemistry
1 publication, 4.55%
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ACS Nano
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ACS Nano
1 publication, 4.55%
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Journal of Physical Chemistry Letters
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Journal of Physical Chemistry Letters
1 publication, 4.55%
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Nano-Micro Letters
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Nano-Micro Letters
1 publication, 4.55%
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Food Chemistry
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1 publication, 4.55%
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Materials Advances
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Materials Advances
1 publication, 4.55%
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Biomaterials Science
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Biomaterials Science
1 publication, 4.55%
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4
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Citations by publishers
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8
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Wiley
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Wiley
8 publications, 36.36%
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American Chemical Society (ACS)
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American Chemical Society (ACS)
5 publications, 22.73%
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Royal Society of Chemistry (RSC)
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Royal Society of Chemistry (RSC)
5 publications, 22.73%
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Elsevier
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Elsevier
2 publications, 9.09%
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Springer Nature
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Springer Nature
1 publication, 4.55%
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- We do not take into account publications that without a DOI.
- Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
- Statistics recalculated weekly.
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Razlivina J. et al. DiZyme: Open‐Access Expandable Resource for Quantitative Prediction of Nanozyme Catalytic Activity // Small. 2022. Vol. 18. No. 12. p. 2105673.
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Razlivina J., Serov N., Shapovalova O., Vinogradov V. DiZyme: Open‐Access Expandable Resource for Quantitative Prediction of Nanozyme Catalytic Activity // Small. 2022. Vol. 18. No. 12. p. 2105673.
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TY - JOUR
DO - 10.1002/smll.202105673
UR - https://doi.org/10.1002%2Fsmll.202105673
TI - DiZyme: Open‐Access Expandable Resource for Quantitative Prediction of Nanozyme Catalytic Activity
T2 - Small
AU - Razlivina, Julia
AU - Serov, Nikita
AU - Shapovalova, Olga
AU - Vinogradov, Vladimir
PY - 2022
DA - 2022/01/14 00:00:00
PB - Wiley
SP - 2105673
IS - 12
VL - 18
SN - 1613-6810
SN - 1613-6829
ER -
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@article{2022_Razlivina,
author = {Julia Razlivina and Nikita Serov and Olga Shapovalova and Vladimir Vinogradov},
title = {DiZyme: Open‐Access Expandable Resource for Quantitative Prediction of Nanozyme Catalytic Activity},
journal = {Small},
year = {2022},
volume = {18},
publisher = {Wiley},
month = {jan},
url = {https://doi.org/10.1002%2Fsmll.202105673},
number = {12},
pages = {2105673},
doi = {10.1002/smll.202105673}
}
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Razlivina, Julia, et al. “DiZyme: Open‐Access Expandable Resource for Quantitative Prediction of Nanozyme Catalytic Activity.” Small, vol. 18, no. 12, Jan. 2022, p. 2105673. https://doi.org/10.1002%2Fsmll.202105673.