Evidence map›Paper›PMID 41562299›Full record

ArticleProtein science : a publication of the Protein Society2026

Diversity of FAAL enzymes and prediction of their substrate specificity using FAALPred.

Anne Liong, Leandro de Mattos Pereira, Pedro N Leão

Abstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Diversity of FAAL enzymes and prediction of their substrate specificity using FAALPred.Protein science : a publication of the Protein Society · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Anne LiongInterdisciplinary Centre of Marine and Environmental Research (CIIMAR/CIMAR), University of Porto, Matosinhos, Portugal.
Leandro de Mattos PereiraInterdisciplinary Centre of Marine and Environmental Research (CIIMAR/CIMAR), University of Porto, Matosinhos, Portugal.
Pedro N LeãoInterdisciplinary Centre of Marine and Environmental Research (CIIMAR/CIMAR), University of Porto, Matosinhos, Portugal.ORCID https://orcid.org/0000-0001-5064-9164

Funding

European Research Council 759840European Union's Horizon 2020 952374Fundação para a Ciência e a Tecnologia 2020.08183.BDFundação para a Ciência e a Tecnologia UIDB/04423/2020Fundação para a Ciência e a Tecnologia UIDP/04423/2020Google CPCA - IAC/AV/591374/2023
6 · The paper itself

Abstract

FAALs (fatty acyl-AMP ligases) recruit and incorporate fatty acids during the biosynthesis of secondary metabolites. Their diversity, distribution, and substrate specificity remain poorly understood, which limits functional predictions from sequence data. In this study, we explored the prevalence and diversity of FAAL enzymes across the tree of life and show that these are widely distributed in secondary metabolite-rich bacteria and predominantly in the context of polyketide and non-ribosomal peptide biosynthetic pathways. FAALs were also found to be present in certain archaea and eukaryotic groups. The phylogenetic placement of FAALs was not correlated to the chain length of the fatty acids that they activate and load. Therefore, we developed a bioinformatics and AI workflow (FAALPred) to predict the chain length of the fatty-acid substrate of a given FAAL sequence. The robustness and accuracy of the predictions generated by FAALPred were validated using independent in vitro and in silico data. We anticipate that FAALPred will not only accelerate secondary metabolite structural predictions and subsequent discovery from FAAL-associated pathways but also facilitate engineering of lipoylation. FAALPred is available at https://faalpred.ciimar.up.pt/.

Indexed as

ArchaeaBacteriaBacterial ProteinsComputational BiologyFatty AcidsLigasesPhylogenyPrediction AlgorithmsSubstrate SpecificityBacterial ProteinsFatty AcidsLigasesbiosynthesisfatty acyl‐AMP ligasesmachine learningnatural products

Identifiers

PMID41562299
PMCPMC12820801

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.