Evidence map›Paper›PMID 32998394›Full record

ArticlePolymers2020

Cyclic Peptide Inhibitors of the Tsg101 UEV Protein Interactions Refined through Global Docking and Gaussian Accelerated Molecular Dynamics Simulations.

Wen-Wei Lin, Yu-Jen Wang, Cheng-Wen Ko, Tain-Lu Cheng, Yeng-Tseng Wang

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2020. 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
0.3field-weighted citation impact, top 42% 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, 5 citations in OpenAlex.

  1. Article
  2. A Review: The Antiviral Activity of Cyclic Peptides.International journal of peptide research and therapeutics · 2023
    Review
  3. Review
  4. Gaussian accelerated molecular dynamics (GaMD): principles and applications.Wiley interdisciplinary reviews. Computational molecular science
    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

5 authors at 2 institutions in 1 country.

Wen-Wei LinSchool of Post-Baccalaureate Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan.
Yu-Jen WangDepartment of Mechanical and Electromechanical Engineering, National Sun Yat-sen University, Kaohsiung 804, Taiwan.
Cheng-Wen KoDepartment of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung 804, Taiwan.
Tain-Lu ChengDrug Development and Value Creation Research Center, Kaohsiung Medical University, Kaohsiung 807, Taiwan.
Yeng-Tseng WangSchool of Post-Baccalaureate Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan.
National Sun Yat-sen University · TWKaohsiung Medical University · TW

Funding

Kaohsiung Medical University, Taiwan KMU-TC108A03-1Ministry of Science and Technology, Taiwan 109-2113-M-037 -015 -
6 · The paper itself

Abstract

Tsg101 UEV domain proteins are potential targets for virus infection therapy, especially for HIV and Ebola viruses. Peptides are key in curbing virus transmission, and cyclic peptides have a greater survival time than their linear peptides. To date, the accurate prediction of cyclic peptide-protein receptors binding conformations still is challenging because of high peptide flexibility. Here, a useful approach combined the global peptide docking, Gaussian accelerated molecular dynamics (GaMD), two-dimensional (2D) potential of mean force (PMF), normal molecular dynamics (cMD), and solvated interaction energy (SIE) techniques. Then we used this approach to investigate the binding conformations of UEV domain proteins with three cyclic peptides inhibitors. We reported the possible cyclic peptide-UEV domain protein binding conformations via 2D PMF free energy profiles and SIE free energy calculations. The residues Trp145, Tyr147, and Trp148 of the native cyclic peptide (CP1) indeed play essential roles in the cyclic peptides-UEV domain proteins interactions. Our findings might increase the accuracy of cyclic peptide-protein conformational prediction, which may facilitate cyclic peptide inhibitor design. Our approach is expected to further aid in addressing the challenges in cyclic peptide inhibitor design.

Indexed as

cyclic peptidesGaussian accelerated molecular dynamics simulationmolecular dynamicsTsg101 UEV protein

Identifiers

PMID32998394
PMCPMC7650771
OpenAlexW3087905660

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.