Evidence map›Paper›PMID 37278582›Full record

ArticleProtein science : a publication of the Protein Society2023

High-throughput computational investigation of protein electrostatics and cavity for SAM-dependent methyltransferases.

Christopher Jurich, Zhongyue J Yang

Open access · bronzeAbstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Context-Dependent Chemoselectivity of Aromatic C-Methyltransferases.Chembiochem : a European journal of chemical biology · 2026
    Article
  2. Article
  3. Mutexa: A Computational Ecosystem for Intelligent Protein Engineering.Journal of chemical theory and computation · 2023
    Review
  4. 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

2 authors at 1 institution in 1 country.

Christopher JurichDepartment of Chemistry, Vanderbilt University, Nashville, Tennessee, USA.ORCID 0000-0001-6592-7980
Zhongyue J YangDepartment of Chemistry, Vanderbilt University, Nashville, Tennessee, USA.ORCID 0000-0003-0395-6617
Vanderbilt University · US

Funding

Chemistry-Biology Interface Training GrantT32GM065086 · NIGMS · VANDERBILT UNIVERSITY · PI BACHMANN, BRIAN O, SULIKOWSKI, GARY ALLEN · 2002 to 2022
$7.0M
Developing Computational Tools for Predicting and Designing Function-Enhancing Enzyme VariantsR35GM146982 · NIGMS · VANDERBILT UNIVERSITY · PI Zhongyue Yang · 2022 to 2026
$1.8M
NIGMS NIH HHS R35 GM146982NIGMS NIH HHS T32 GM065086
6 · The paper itself

Abstract

S-adenosyl methionine (SAM)-dependent methyl transferases (MTases) are a ubiquitous class of enzymes catalyzing dozens of essential life processes. Despite targeting a large space of substrates with diverse intrinsic reactivity, SAM MTases have similar catalytic efficiency. While understanding of MTase mechanism has grown tremendously through the integration of structural characterization, kinetic assays, and multiscale simulations, it remains elusive how these enzymes have evolved to fit the diverse chemical needs of their respective substrates. In this work, we performed a high-throughput molecular modeling analysis of 91 SAM MTases to better understand how their properties (i.e., electric field [EF] strength and active site volumes) help achieve similar catalytic efficiency toward substrates of different reactivity. We found that EF strengths have largely adjusted to make the target atom a better methyl acceptor. For MTases that target RNA/DNA and histone proteins, our results suggest that EF strength accommodates formal hybridization state and variation in cavity volume trends with diversity of substrate classes. Metal ions in SAM MTases contribute negatively to EF strength for methyl donation and enzyme scaffolds tend to offset these contributions.

Indexed as

MethyltransferasesS-AdenosylmethionineCatalytic DomainModels, MolecularStatic ElectricityMethyltransferasesS-Adenosylmethioninecavitydescriptorselectrici fieldhigh-throughput molecular modelingmethyltransferasesstatistical analysis

Identifiers

PMID37278582
PMCPMC10273352
OpenAlexW4379509259

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.