Evidence map›Paper›PMID 39110832›Full record

ArticleJournal of chemical theory and computation2024

Dissecting Allosteric Mutations for Antibiotic Resistance by Time-Dependent Linear Response Theory.

P Campitelli, T Modi, S B Ozkan

Abstract read
In one paragraph

Article in Journal of chemical theory and computation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

P CampitelliDepartment of Physics, Center for Biological Physics, Arizona State University, Tempe, Arizona 85287-1504, United States.
T ModiDepartment of Physics, Center for Biological Physics, Arizona State University, Tempe, Arizona 85287-1504, United States.
S B OzkanDepartment of Physics, Center for Biological Physics, Arizona State University, Tempe, Arizona 85287-1504, United States.ORCID 0000-0002-9351-3758

Funding

Using dynamic network models to quantitatively predict changes in binding affinity/specificity that arise from long-range amino acid substitutionsR01GM147635 · NIGMS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI OZKAN, SEFIKA BANU, SWINT-KRUSE, LISKIN · 2022 to 2025
$1.8M
NIGMS NIH HHS R01 GM147635
6 · The paper itself

Abstract

We report a new approach that combines molecular dynamics trajectories with time-dependent linear response theory to compute the time evolution of residue fluctuation responses to force perturbations exerted at functional sites. Applying this new approach to TEM-1 beta-lactamase, we observe that the time-resolved response profiles of allosteric sites to perturbations of TEM-1 active sites are distinct from those of non-allosteric residues. Using Fourier transformations, we convert the time domain response profiles to the frequency domain and demonstrate that the frequency space representation of the perturbation response can capture the mutational behavior of each site when applied to deep sequencing mutational data. Furthermore, we show that classification models built on perturbation responses can accurately identify distal positions that regulate antibiotic resistance. These findings provide insights into the contributions of specific residues to resistance-encoded in time-resolved perturbation response behavior and highlight the importance of this new approach in identifying allosteric mutations, opening avenues for the potential characterization of additional allosteric positions without extensive computational simulations.

Identifiers

PMID39110832
PMCPMC12207895

What OpenQuestion holds

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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.