Quantum computing for faster enzyme discovery and engineering

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F25%3A00082341" target="_blank" >RIV/00159816:_____/25:00082341 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21230/25:00388547 RIV/68407700:21730/25:00388547 RIV/00216224:14310/25:00142669

Výsledek na webu

<a href="https://www.nature.com/articles/s41929-025-01410-w" target="_blank" >https://www.nature.com/articles/s41929-025-01410-w</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41929-025-01410-w" target="_blank" >10.1038/s41929-025-01410-w</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Quantum computing for faster enzyme discovery and engineering

Popis výsledku v původním jazyce

Quantum computing, by leveraging the unique principles of quantum mechanics, offers transformative potential for biocatalysis and related disciplines. Compared to classical algorithms, quantum algorithms deliver immense acceleration to quantum computers, making them suited for tackling computationally challenging problems such as simulating many-body biomolecular systems or enzyme-catalysed chemical reactions. However, current quantum hardware is constrained by noise, limited qubit coherence and high error rates, restricting its capacity to model complex biochemical phenomena. Here we explore the rapidly advancing landscape of quantum computing and its future applications in the discovery and rational engineering of biocatalysts. We identify key areas where quantum algorithms could surpass classical limitations, including the quantum chemistry-based design of biocatalysts with enhanced catalytic activity or selectivity, parallelized mining of novel enzymes, accurate ancestral sequence reconstruction, and combinatorial in silico protein evolution. Overcoming current hardware limitations could unlock transformative advances in both fundamental enzymology and industrial bioprocessing.

Název v anglickém jazyce

Quantum computing for faster enzyme discovery and engineering

Popis výsledku anglicky

Quantum computing, by leveraging the unique principles of quantum mechanics, offers transformative potential for biocatalysis and related disciplines. Compared to classical algorithms, quantum algorithms deliver immense acceleration to quantum computers, making them suited for tackling computationally challenging problems such as simulating many-body biomolecular systems or enzyme-catalysed chemical reactions. However, current quantum hardware is constrained by noise, limited qubit coherence and high error rates, restricting its capacity to model complex biochemical phenomena. Here we explore the rapidly advancing landscape of quantum computing and its future applications in the discovery and rational engineering of biocatalysts. We identify key areas where quantum algorithms could surpass classical limitations, including the quantum chemistry-based design of biocatalysts with enhanced catalytic activity or selectivity, parallelized mining of novel enzymes, accurate ancestral sequence reconstruction, and combinatorial in silico protein evolution. Overcoming current hardware limitations could unlock transformative advances in both fundamental enzymology and industrial bioprocessing.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Nature Catalysis

ISSN

2520-1158

e-ISSN

2520-1158

Svazek periodika

8

Číslo periodika v rámci svazku

9

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

9

Strana od-do

872-880

Kód UT WoS článku

001580461500004

EID výsledku v databázi Scopus

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