Evidence map›Paper›PMID 33598096›Full record

ArticleComputational and structural biotechnology journal2021

Hybrid method for representing ions in implicit solvation calculations.

Shengjie Sun, Chitra Karki, Yixin Xie, Yuejiao Xian, Wenhan Guo, Bruce Z Gao, Lin Li

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Solvent effects in anion recognition.Nature reviews. Chemistry · 2024
    Review
  4. Article
  5. Article
  6. HIT-2: Implementing machine learning algorithms to treat bound ions in biomolecules.Computational and structural biotechnology journal · 2023
    Article
  7. Review
  8. Article
  9. HIT web server: A hybrid method to improve electrostatic calculations for biomolecules.Computational and structural biotechnology journal · 2022
    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

7 authors.

Shengjie SunComputational Science Program, University of Texas at El Paso, 500 W University Ave, TX 79968, USA.
Chitra KarkiComputational Science Program, University of Texas at El Paso, 500 W University Ave, TX 79968, USA.
Yixin XieComputational Science Program, University of Texas at El Paso, 500 W University Ave, TX 79968, USA.
Yuejiao XianDepartment of Chemistry, University of Texas at El Paso, 500 W University Ave, TX 79968, USA.
Wenhan GuoComputational Science Program, University of Texas at El Paso, 500 W University Ave, TX 79968, USA.
Bruce Z GaoDepartment of Bioengineering, Clemson University, Clemson, SC 29634, USA.
Lin LiComputational Science Program, University of Texas at El Paso, 500 W University Ave, TX 79968, USA.

Funding

UTEP Border Biomedical Research CenterU54MD007592 · NIMHD · UNIVERSITY OF TEXAS EL PASO · PI Gabriel Andrew Frietze · 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 GM132043NIMHD NIH HHS U54 MD007592
6 · The paper itself

Abstract

Fast and accurate calculations of the electrostatic features of highly charged biomolecules such as DNA, RNA, and highly charged proteins are crucial and challenging tasks. Traditional implicit solvent methods calculate the electrostatic features quickly, but these methods are not able to balance the high net biomolecular charges effectively. Explicit solvent methods add unbalanced ions to neutralize the highly charged biomolecules in molecular dynamic simulations, which require more expensive computing resources. Here we report developing a novel method, Hybridizing Ions Treatment (HIT), which hybridizes the implicit solvent method with an explicit method to realistically calculate the electrostatic potential for highly charged biomolecules. HIT utilizes the ionic distribution from an explicit method to predict the bound ions. The bound ions are then added in the implicit solvent method to perform the electrostatic potential calculations. In this study, two training sets were developed to optimize parameters for HIT. The performance on the testing set demonstrates that HIT significantly improves the electrostatic calculations. Results on molecular motors myosin and kinesin reveal some mechanisms and explain some previous experimental findings. HIT can be widely used to study highly charged biomolecules, including DNA, RNA, molecular motors, and other highly charged biomolecules. The HIT package is available at http://compbio.utep.edu/static/downloads/download_hit.zip.

Indexed as

DelPhiElectrostatic calculationExplicit solvent modelImplicit solvent modelKinesinMyosin

Identifiers

PMID33598096
PMCPMC7847951

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.