Evidence map›Paper›PMID 42510962›Full record

ArticleCurrent issues in molecular biology2026

Evolutionary Divergence, Predicted Interaction Interface, and Regulatory Specialization of MTB as a Non-Catalytic Scaffold in the Plant m6A Writer Complex.

Hariharan Balasubramaniam, Susiharan Govindasamy Srinivasan, A Santhana Krishna Kumar

Abstract read
In one paragraph

Article in Current issues in molecular biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Hariharan BalasubramaniamBiotechnology Center in Southern Taiwan, Academia Sinica, No. 100, Guiren 13th Road, Guiren District, Tainan 711010, Taiwan.ORCID 0000-0002-8398-8821
Susiharan Govindasamy SrinivasanDepartment of Chemistry, National Sun Yat-sen University, No. 70, Lien-hai Road, Gushan District, Kaohsiung 80424, Taiwan.ORCID 0009-0008-0832-7442
A Santhana Krishna KumarDepartment of Chemistry, National Sun Yat-sen University, No. 70, Lien-hai Road, Gushan District, Kaohsiung 80424, Taiwan.ORCID 0000-0002-1681-4426

Funding

NSTC; NSYSU-KMU NSTC 114-2221-E-110-007; NSTC 115-2221-E-110-052; NSYSU-KMU 115-P17
6 · The paper itself

Abstract

N6-methyladenosine (m6A) is the most prevalent internal modification of eukaryotic mRNA and a central regulator of plant development and stress adaptation. The plant m6A writer complex requires two MT-A70 family proteins, the catalytic subunit MTA70 and its non-catalytic partner MTB, yet the evolutionary basis and structural logic underlying this functional division remain unresolved across land plant lineages. Here, we present an integrative computational analysis of MTA70 and MTB across 15 phylogenetically representative species spanning bryophytes, lycophytes, charophyte algae, monocots, and dicots. Phylogenomic reconstruction resolved three strongly supported clades, namely MTA70, MTB, and an intermediate MTA70-like group, demonstrating that catalytic-to-regulatory divergence predates the separation of major land plant lineages. MTA70 proteins exhibited strict conservation of gene structure, catalytic motifs, and domain architecture, reflecting selective constraint at functionally critical residues, whereas MTB showed extensive divergence in exon-intron organization and surface-exposed residues, consistent with relaxed structural constraints. AlphaFold2-based structural modeling and data-driven protein-protein docking predicted a stable MTA70-MTB heterodimer with a buried surface area of 1435 Å

Indexed as

ABA signalingAlphaFold2epitranscriptomic regulationland plant evolutionm6A writer complexMTA70MTBN6-methyladenosineprotein–protein docking

Identifiers

PMID42510962
PMCPMC13408939

What Socratic holds

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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 Socratic graph.