Evidence map›Paper›PMID 30484023›Full record

ArticleMolecular diversity2019

Three-dimensional descriptors for aminergic GPCRs: dependence on docking conformation and crystal structure.

Stanisław Jastrzębski, Igor Sieradzki, Damian Leśniak, Jacek Tabor, Andrzej J Bojarski, Sabina Podlewska

Abstract read
In one paragraph

Article in Molecular diversity, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Stanisław JastrzębskiFaculty of Mathematics and Computer Science, Jagiellonian University, S. Łojasiewicza Street 6, 30-048, Kraków, Poland.
Igor SieradzkiFaculty of Mathematics and Computer Science, Jagiellonian University, S. Łojasiewicza Street 6, 30-048, Kraków, Poland.
Damian LeśniakFaculty of Mathematics and Computer Science, Jagiellonian University, S. Łojasiewicza Street 6, 30-048, Kraków, Poland.
Jacek TaborFaculty of Mathematics and Computer Science, Jagiellonian University, S. Łojasiewicza Street 6, 30-048, Kraków, Poland.
Andrzej J BojarskiDepartment of Medicinal Chemistry, Institute of Pharmacology, Polish Academy of Sciences, Smętna Street 12, 31-343, Kraków, Poland.
Sabina PodlewskaDepartment of Medicinal Chemistry, Institute of Pharmacology, Polish Academy of Sciences, Smętna Street 12, 31-343, Kraków, Poland. smusz@if-pan.krakow.pl.ORCID http://orcid.org/0000-0002-2891-5603

Funding

Narodowe Centrum Nauki 2015/18/M/NZ7/00377
6 · The paper itself

Abstract

Three-dimensional descriptors are often used to search for new biologically active compounds, in both ligand- and structure-based approaches, capturing the spatial orientation of molecules. They frequently constitute an input for machine learning-based predictions of compound activity or quantitative structure-activity relationship modeling; however, the distribution of their values and the accuracy of depicting compound orientations might have an impact on the power of the obtained predictive models. In this study, we analyzed the distribution of three-dimensional descriptors calculated for docking poses of active and inactive compounds for all aminergic G protein-coupled receptors with available crystal structures, focusing on the variation in conformations for different receptors and crystals. We demonstrated that the consistency in compound orientation in the binding site is rather not correlated with the affinity itself, but is more influenced by other factors, such as the number of rotatable bonds and crystal structure used for docking studies. The visualizations of the descriptors distributions were prepared and made available online at http://chem.gmum.net/vischem_stability , which enables the investigation of chemical structures referring to particular data points depicted in the figures. Moreover, the performed analysis can assist in choosing crystal structure for docking studies, helping in selection of conditions providing the best discrimination between active and inactive compounds in machine learning-based experiments.

Indexed as

Molecular Docking SimulationAminesCrystallography, X-RayLigandsMachine LearningProtein ConformationReceptors, G-Protein-CoupledAminesLigandsReceptors, G-Protein-CoupledAminergic GPCRsCrystal structureDockingMachine learningThree-dimensional descriptors

Identifiers

PMID30484023
PMCPMC6682580

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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.