Evidence map›Paper›PMID 36447514›Full record

ArticlePeerJ2022

A multi-reference poly-conformational method for

Vadim Alexandrov, Alexander Kirpich, Omar Kantidze, Yuriy Gankin

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 33% 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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 1 institution in 1 country.

Vadim AlexandrovLiquid Algo LLC, Hopewell Junction, NY, United States of America.
Alexander KirpichDepartment of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA, United States of America.
Omar KantidzeQuantori, Cambridge, MA, United States of America.
Yuriy GankinQuantori, Cambridge, MA, United States of America.
Georgia State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This work presents a novel computational multi-reference poly-conformational algorithm for design, optimization, and repositioning of pharmaceutical compounds. Methods: The algorithm searches for candidates by comparing similarities between conformers of the same compound and identifies target compounds, whose conformers are collectively close to the conformers of each compound in the reference set. Reference compounds may possess highly variable MoAs, which directly, and simultaneously, shape the properties of target candidate compounds. Results: The algorithm functionality has been case study validated

Indexed as

COVID-19SARS-CoV-2Drug RepositioningHumansLigandsMolecular ConformationPharmaceutical PreparationsLigandsPharmaceutical PreparationsComputational frameworkConformersIn silicoLigand-basedMulti-referencePoly-conformationalSARSCOV- 2Structure-basedValidationVirtual library

Identifiers

PMID36447514
PMCPMC9701500
OpenAlexW4309848854

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.