Evidence map›Paper›PMID 35201444›Full record

ArticleJournal of molecular modeling2022

Simulating chalcogen bonding using molecular mechanics: a pseudoatom approach to model ebselen.

Thomas Fellowes, Jonathan M White

Open access · hybridAbstract read
In one paragraph

Article in Journal of molecular modeling, 2022. 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
0.5field-weighted citation impact, top 44% 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, 4 citations in OpenAlex.

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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.

Thomas FellowesBio21 Institute and School of Chemistry, University of Melbourne, Parkville, Australia. fellowes@student.unimelb.edu.au.ORCID http://orcid.org/0000-0002-6389-6049
Jonathan M WhiteBio21 Institute and School of Chemistry, University of Melbourne, Parkville, Australia.ORCID http://orcid.org/0000-0002-0707-6257
The University of Melbourne · AU

Funding

Australian Research Council LE170100065Australian Research Council LE170100200
6 · The paper itself

Abstract

The organoselenium compound ebselen has recently been investigated as a treatment for COVID-19; however, efforts to model ebselen in silico have been hampered by the lack of an efficient and accurate method to assess its binding to biological macromolecules. We present here a Generalized Amber Force Field modification which incorporates classical parameters for the selenium atom in ebselen, as well as a positively charged pseudoatom to simulate the σ-hole, a quantum mechanical phenomenon that dominates the chemistry of ebselen. Our approach is justified using an energy decomposition analysis of a number of density functional theory-optimized structures, which shows that the σ-hole interaction is primarily electrostatic in origin. Finally, our model is verified by conducting molecular dynamics simulations on a number of simple complexes, as well as the clinically relevant enzyme SOD1 (superoxide dismutase), which is known to bind to ebselen. Graphical Abstract Ebselen is an organoselenium drug that has shown promise for the treatment of a number of conditions. Computational modelling of drug-target complexes is commonly performed to determine the likely mechanism of action, however this is difficult in the case of ebselen, as an important mode of interaction is not simulated using current techniques. We present here an extension to common methods, which accurately captures this interaction.

Indexed as

Chalcogen bondingEbselenGROMACSMolecular mechanics.σ-hole

Identifiers

PMID35201444
PMCPMC8867462
OpenAlexW4220701133

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.