Evidence map›Paper›PMID 36402831›Full record

ArticleScientific reports2022

Searching glycolate oxidase inhibitors based on QSAR, molecular docking, and molecular dynamic simulation approaches.

Nicolás Cabrera, Sebastián A Cuesta, José R Mora, José Luis Paz, Edgar A Márquez, Patricio J Espinoza-Montero, Yovani Marrero-Ponce, Noel Pérez, Ernesto Contreras-Torres

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 23% 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

6 citing papers in PubMed, 10 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

9 authors at 8 institutions in 7 countries.

Nicolás CabreraDepartment of Biomedical Engineering, Texas A&M University, College Station, TX, 77843, USA.ORCID 0000-0002-9678-6823
Sebastián A CuestaDepartment of Chemistry, Manchester Institute of Biotechnology, The University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK.ORCID 0000-0002-8035-6220
José R MoraInstituto de Simulación Computacional (ISC-USFQ), Departamento de Ingeniería Química, Universidad San Francisco de Quito, Diego de Robles y Vía Interoceánica, 170901, Quito, Ecuador. jrmora@usfq.edu.ec.ORCID 0000-0001-6128-9504
José Luis PazDepartamento Académico de Química Inorgánica, Facultad de Química e Ingeniería Química, Universidad Nacional Mayor de San Marcos, Lima, Perú.ORCID 0000-0002-6177-7919
Edgar A MárquezGrupo de Investigaciones en Química y Biología, Departamento de Química y Biología, Facultad de Ciencias Básicas, Universidad del Norte, Carrera 51B, Km 5, Vía Puerto Colombia, 081007, Barranquilla, Colombia. ebrazon@uninorte.edu.co.ORCID 0000-0002-7503-1528
Patricio J Espinoza-MonteroEscuela de Ciencias Químicas, Pontificia Universidad Católica del Ecuador, 17012184, Quito, Ecuador.ORCID 0000-0003-0592-8652
Yovani Marrero-PonceGrupo de Medicina Molecular y Traslacional (MeM&T), Escuela de Medicina, Colegio de Ciencias de la Salud (COCSA), Universidad San Francisco de Quito (USFQ), Edificio de Especialidades Médicas, Diego de Robles y Vía Interoceánica, 170157, Quito, Pichincha, Ecuador.ORCID 0000-0003-2721-1142
Noel PérezColegio de Ciencias e Ingenierías "El Politécnico", Universidad San Francisco de Quito (USFQ), 170901, Quito, Ecuador.ORCID 0000-0003-3166-745X
Ernesto Contreras-TorresCAM - Basque Center for Applied Mathematics, Mazarredo 14, 48009, Bilbao, Basque Country, Spain.ORCID 0000-0003-4761-1784
Universidad San Francisco de Quito · ECBasque Center for Applied Mathematics · ESCentro de Investigación Científica y de Educación Superior de Ensenada · MXNational University of San Marcos · PEPontificia Universidad Católica del Ecuador · ECTexas A&M University · USUniversidad del Norte · COUniversity of Manchester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Primary hyperoxaluria type 1 (PHT1) treatment is mainly focused on inhibiting the enzyme glycolate oxidase, which plays a pivotal role in the production of glyoxylate, which undergoes oxidation to produce oxalate. When the renal secretion capacity exceeds, calcium oxalate forms stones that accumulate in the kidneys. In this respect, detailed QSAR analysis, molecular docking, and dynamics simulations of a series of inhibitors containing glycolic, glyoxylic, and salicylic acid groups have been performed employing different regression machine learning techniques. Three robust models with less than 9 descriptors-based on a tenfold cross (Q

Indexed as

Molecular Dynamics SimulationQuantitative Structure-Activity RelationshipAlcohol OxidoreductasesMolecular Docking SimulationAlcohol Oxidoreductasesglycollate oxidase

Identifiers

PMID36402831
PMCPMC9675741
OpenAlexW4309659576

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.