Tools for computational design and high-throughput screening of
therapeutic enzymes

J 2022

Tools for computational design and high-throughput screening of therapeutic enzymes

VAŠINA, Michal; Jan VELECKÝ; Joan PLANAS IGLESIAS; Sérgio Manuel MARQUES; Jana ŠKAŘUPOVÁ et. al.

Základní údaje

Originální název

Tools for computational design and high-throughput screening of therapeutic enzymes

Autoři

VAŠINA, Michal; Jan VELECKÝ ; Joan PLANAS IGLESIAS; Sérgio Manuel MARQUES; Jana ŠKAŘUPOVÁ; Jiří DAMBORSKÝ; David BEDNÁŘ; Stanislav MAZURENKO a Zbyněk PROKOP

Vydání

ADVANCED DRUG DELIVERY REVIEWS, NETHERLANDS, ELSEVIER, 2022, 0169-409X

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30104 Pharmacology and pharmacy

Stát vydavatele

Nizozemské království

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 16.100

Kód RIV

RIV/00216224:14310/22:00126167

Organizační jednotka

Přírodovědecká fakulta

DOI

https://doi.org/10.1016/j.addr.2022.114143

UT WoS

000793483600005

EID Scopus

2-s2.0-85125134958

Klíčová slova anglicky

Big data; Bioinformatics; Biopharmaceuticals; Biocatalysts; Enzyme characterization; Enzyme diversity; Machine learning; Microfluidics; Rational design

Štítky

14314010, 143180, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 26. 2. 2025 14:34, Mgr. Marie Novosadová Šípková, DiS.

Anotace

V originále

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.

Návaznosti

EF17_043/0009632, projekt VaV

Název: CETOCOEN Excellence

EF19_073/0016943, projekt VaV

Název: Interní grantová agentura Masarykovy univerzity

GJ20-15915Y, projekt VaV

Název: Studium molekulováho rozpoznávání a vývoj nových softwarových nástrojů pro identifikaci a design přístupových cest v proteinech

Investor: Grantová agentura ČR, Studium molekulováho rozpoznávání a vývoj nových softwarových nástrojů pro identifikaci a design přístupových cest v proteinech

LM2018121, projekt VaV

Název: Výzkumná infrastruktura RECETOX (Akronym: RECETOX RI)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, RECETOX RI

857560, interní kód MU
(Kód CEP: EF17_043/0009632)

Název: CETOCOEN Excellence (Akronym: CETOCOEN Excellence)

Investor: Evropská unie, CETOCOEN Excellence, Spreading excellence and widening participation

90131, velká výzkumná infrastruktura

Název: ELIXIR-CZ II

Citovat

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. ADVANCED DRUG DELIVERY REVIEWS. NETHERLANDS: ELSEVIER, 2022, roč. 183, April 2022, s. 1-16. ISSN 0169-409X. Dostupné z: https://doi.org/10.1016/j.addr.2022.114143.

@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 = {https://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://doi.org/10.1016/j.addr.2022.114143.

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