Evidence map›Paper›PMID 38446738›Full record

ArticleBriefings in bioinformatics2024

A novel approach to study multi-domain motions in JAK1's activation mechanism based on energy landscape.

Shengjie Sun, Georgialina Rodriguez, Gaoshu Zhao, Jason E Sanchez, Wenhan Guo, Dan Du, Omar J Rodriguez Moncivais, Dehua Hu, Jing Liu, Robert Arthur Kirken and 1 more

Open access · goldAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.4field-weighted citation impact, top 6% 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

12 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Integrated modeling of protein and RNA.Briefings in bioinformatics · 2024
    Article
  8. Integrated modeling of protein and RNA.Briefings in bioinformatics · 2024
    Article
  9. Integrated modeling of protein and RNA.Briefings in bioinformatics · 2024
    Article
  10. Integrated modeling of protein and RNA.Briefings in bioinformatics · 2024
    Article
  11. Integrated modeling of protein and RNA.Briefings in bioinformatics · 2024
    Article
  12. Integrated modeling of protein and RNA.Briefings in bioinformatics · 2024
    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

11 authors at 3 institutions in 2 countries.

Shengjie SunDepartment of Biomedical Informatic, School of Life Sciences, Central South University, Changsha 410083, China.
Georgialina RodriguezDepartment of Biological Sciences, The University of Texas at El Paso, 500 W University Ave, TX 79968, USA.
Gaoshu ZhaoGoogle LLC, 1600 Amphitheatre Parkway Mountain View, CA 94043, USA.
Jason E SanchezComputational Science Program, The University of Texas at El Paso, 500 W University Ave, TX 79968, USA.
Wenhan GuoComputational Science Program, The University of Texas at El Paso, 500 W University Ave, TX 79968, USA.
Dan DuComputational Science Program, The University of Texas at El Paso, 500 W University Ave, TX 79968, USA.
Omar J Rodriguez MoncivaisDepartment of Biological Sciences, The University of Texas at El Paso, 500 W University Ave, TX 79968, USA.
Dehua HuDepartment of Biomedical Informatic, School of Life Sciences, Central South University, Changsha 410083, China.
Jing LiuDepartment of Hematology, The Second Xiangya Hospital of Central South University; Molecular Biology Research Center, Center for Medical Genetics, School of Life Sciences, Central South University, Changsha 410083, China.
Robert Arthur KirkenDepartment of Biological Sciences, The University of Texas at El Paso, 500 W University Ave, TX 79968, USA.
Lin LiComputational Science Program, The University of Texas at El Paso, 500 W University Ave, TX 79968, USA.ORCID 0000-0001-6447-2398
The University of Texas at El Paso · USCentral South University · CNGoogle (United States) · US

Funding

UTEP Border Biomedical Research CenterU54MD007592 · NIMHD · UNIVERSITY OF TEXAS EL PASO · PI RENATO J AGUILERA · 2019 to 2026
$35.1M
Developing and applying large-scale simulation approach to understand the mechanisms of kinesins' motilities along microtubulesSC1GM132043 · NIGMS · UNIVERSITY OF TEXAS EL PASO · PI LI, LIN · 2019 to 2022
$1.5M
NIGMS NIH HHS SC1 GM132043NIH HHS SC1GM132043NIMHD NIH HHS 5U54MD007592NIMHD NIH HHS U54 MD007592
6 · The paper itself

Abstract

The family of Janus Kinases (JAKs) associated with the JAK-signal transducers and activators of transcription signaling pathway plays a vital role in the regulation of various cellular processes. The conformational change of JAKs is the fundamental steps for activation, affecting multiple intracellular signaling pathways. However, the transitional process from inactive to active kinase is still a mystery. This study is aimed at investigating the electrostatic properties and transitional states of JAK1 to a fully activation to a catalytically active enzyme. To achieve this goal, structures of the inhibited/activated full-length JAK1 were modelled and the energies of JAK1 with Tyrosine Kinase (TK) domain at different positions were calculated, and Dijkstra's method was applied to find the energetically smoothest path. Through a comparison of the energetically smoothest paths of kinase inactivating P733L and S703I mutations, an evaluation of the reasons why these mutations lead to negative or positive regulation of JAK1 are provided. Our energy analysis suggests that activation of JAK1 is thermodynamically spontaneous, with the inhibition resulting from an energy barrier at the initial steps of activation, specifically the release of the TK domain from the inhibited Four-point-one, Ezrin, Radixin, Moesin-PK cavity. Overall, this work provides insights into the potential pathway for TK translocation and the activation mechanism of JAK1.

Indexed as

Signal TransductionMutationProtein DomainsdelphiDijkstra’s methodelectrostatic potentialenergy landscapeJAK1tyrosine kinase

Identifiers

PMID38446738
PMCPMC10939344
OpenAlexW4392500216

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.