MARTS-DB: a database of mechanisms and reactions of terpene synthases

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11310%2F25%3A10515591" target="_blank" >RIV/00216208:11310/25:10515591 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/60461373:22310/25:43933041

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=C-fBJcn0wf" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=C-fBJcn0wf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1186/s12859-025-06341-8" target="_blank" >10.1186/s12859-025-06341-8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

MARTS-DB: a database of mechanisms and reactions of terpene synthases

Popis výsledku v původním jazyce

BackgroundTerpene synthases (TPSs) are enzymes that catalyze some of the most complex reactions in nature-the cyclizations of terpenes, which form the carbon backbones to the largest group of natural products, the terpenoids. On average, more than half of the carbon atoms in a terpene scaffold undergo a change in connectivity or configuration during these enzymatic cascades. Understanding TPS reaction mechanisms remains challenging, often requiring intricate computational modeling and isotopic labelling studies. Moreover, the relationship between TPS sequence and catalytic function is difficult to decipher, while data-driven approaches remain limited due to a lack of comprehensive, high-quality data sources.MainWe introduce the Mechanisms And Reactions of Terpene Synthases DataBase (MARTS-DB)-a manually curated, structured, and searchable database that integrates TPS enzymes, the terpenes they produce, and their detailed reaction mechanisms. MARTS-DB includes over 2850 reactions catalyzed by 1432 annotated enzymes from across all domains of life, with reaction mechanisms mapped as stepwise cascades for more than 500 terpenes. Accessible at https://www.marts-db.org, the database provides advanced search functionality and supports full dataset downloads in machine-readable formats. It also encourages community contributions to promote continuous growth.ConclusionUser-friendly and comprehensive, MARTS-DB enables the systematic exploration of TPS catalysis, opening new avenues for computational analysis and machine learning, as recently demonstrated in the prediction of novel TPSs.

Název v anglickém jazyce

MARTS-DB: a database of mechanisms and reactions of terpene synthases

Popis výsledku anglicky

BackgroundTerpene synthases (TPSs) are enzymes that catalyze some of the most complex reactions in nature-the cyclizations of terpenes, which form the carbon backbones to the largest group of natural products, the terpenoids. On average, more than half of the carbon atoms in a terpene scaffold undergo a change in connectivity or configuration during these enzymatic cascades. Understanding TPS reaction mechanisms remains challenging, often requiring intricate computational modeling and isotopic labelling studies. Moreover, the relationship between TPS sequence and catalytic function is difficult to decipher, while data-driven approaches remain limited due to a lack of comprehensive, high-quality data sources.MainWe introduce the Mechanisms And Reactions of Terpene Synthases DataBase (MARTS-DB)-a manually curated, structured, and searchable database that integrates TPS enzymes, the terpenes they produce, and their detailed reaction mechanisms. MARTS-DB includes over 2850 reactions catalyzed by 1432 annotated enzymes from across all domains of life, with reaction mechanisms mapped as stepwise cascades for more than 500 terpenes. Accessible at https://www.marts-db.org, the database provides advanced search functionality and supports full dataset downloads in machine-readable formats. It also encourages community contributions to promote continuous growth.ConclusionUser-friendly and comprehensive, MARTS-DB enables the systematic exploration of TPS catalysis, opening new avenues for computational analysis and machine learning, as recently demonstrated in the prediction of novel TPSs.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10600 - Biological sciences

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název periodika

BMC Bioinformatics

ISSN

1471-2105

e-ISSN

1471-2105

Svazek periodika

27

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

10

Strana od-do

10

Kód UT WoS článku

001660152400001

EID výsledku v databázi Scopus

2-s2.0-105027313674