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@article{1863379,
author = {Vašina, Michal and Velecký, Jan and Planas Iglesias, Joan and Marques, Sérgio Manuel and Škařupová, Jana and Damborský, Jiří and Bednář, David and Mazurenko, Stanislav and Prokop, Zbyněk},
article_location = {NETHERLANDS},
article_number = {April 2022},
doi = {http://dx.doi.org/10.1016/j.addr.2022.114143},
keywords = {Big data; Bioinformatics; Biopharmaceuticals; Biocatalysts; Enzyme characterization; Enzyme diversity; Machine learning; Microfluidics; Rational design},
language = {eng},
issn = {0169-409X},
journal = {ADVANCED DRUG DELIVERY REVIEWS},
title = {Tools for computational design and high-throughput screening of therapeutic enzymes},
url = {https://www.sciencedirect.com/science/article/pii/S0169409X22000333?via%3Dihub},
volume = {183},
year = {2022}
}
TY - JOUR
ID - 1863379
AU - Vašina, Michal - Velecký, Jan - Planas Iglesias, Joan - Marques, Sérgio Manuel - Škařupová, Jana - Damborský, Jiří - Bednář, David - Mazurenko, Stanislav - Prokop, Zbyněk
PY - 2022
TI - Tools for computational design and high-throughput screening of therapeutic enzymes
JF - ADVANCED DRUG DELIVERY REVIEWS
VL - 183
IS - April 2022
SP - 1-16
EP - 1-16
PB - ELSEVIER
SN - 0169409X
KW - Big data
KW - Bioinformatics
KW - Biopharmaceuticals
KW - Biocatalysts
KW - Enzyme characterization
KW - Enzyme diversity
KW - Machine learning
KW - Microfluidics
KW - Rational design
UR - https://www.sciencedirect.com/science/article/pii/S0169409X22000333?via%3Dihub
N2 - Therapeutic enzymes are valuable biopharmaceuticals in various biomedical applications. They have been successfully applied for fibrinolysis, cancer treatment, enzyme replacement therapies, and the treatment of rare diseases. Still, there is a permanent demand to find new or better therapeutic enzymes, which would be sufficiently soluble, stable, and active to meet specific medical needs. Here, we highlight the benefits of coupling computational approaches with high-throughput experimental technologies, which significantly accelerate the identification and engineering of catalytic therapeutic agents. New enzymes can be identified in genomic and metagenomic databases, which grow thanks to next generation sequencing technologies exponentially. Computational design and machine learning methods are being developed to improve catalytically potent enzymes and predict their properties to guide the selection of target enzymes. High-throughput experimental pipelines, increasingly relying on microfluidics, ensure functional screening and biochemical characterization of target enzymes to reach efficient therapeutic enzymes.
ER -
VAŠINA, Michal, Jan VELECKÝ, Joan PLANAS IGLESIAS, Sérgio Manuel MARQUES, Jana ŠKAŘUPOVÁ, Jiří DAMBORSKÝ, David BEDNÁŘ, Stanislav MAZURENKO a Zbyněk PROKOP. Tools for computational design and high-throughput screening of therapeutic enzymes. \textit{ADVANCED DRUG DELIVERY REVIEWS}. NETHERLANDS: ELSEVIER, 2022, roč.~183, April 2022, s.~1-16. ISSN~0169-409X. Dostupné z: https://dx.doi.org/10.1016/j.addr.2022.114143.
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