Evidence map›Paper›PMID 37110655›Full record

ArticleMolecules (Basel, Switzerland)2023

Virtual Screening Strategy to Identify Retinoic Acid-Related Orphan Receptor γt Modulators.

Elmeri M Jokinen, Miika Niemeläinen, Sami T Kurkinen, Jukka V Lehtonen, Sakari Lätti, Pekka A Postila, Olli T Pentikäinen, Sanna P Niinivehmas

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

8 authors.

Elmeri M JokinenMedChem.fi, Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, FI-20014 Turku, Finland.ORCID 0000-0003-2352-6550
Miika NiemeläinenMedChem.fi, Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, FI-20014 Turku, Finland.
Sami T KurkinenMedChem.fi, Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, FI-20014 Turku, Finland.ORCID 0000-0003-2515-7429
Jukka V LehtonenStructural Bioinformatics Laboratory, Biochemistry, Faculty of Science and Engineering, Åbo Akademi University, FI-20500 Turku, Finland.ORCID 0000-0003-0385-0636
Sakari LättiMedChem.fi, Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, FI-20014 Turku, Finland.ORCID 0000-0002-4132-8745
Pekka A PostilaMedChem.fi, Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, FI-20014 Turku, Finland.ORCID 0000-0002-2947-7991
Olli T PentikäinenMedChem.fi, Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, FI-20014 Turku, Finland.ORCID 0000-0001-7188-4016
Sanna P NiinivehmasMedChem.fi, Institute of Biomedicine, Integrative Physiology and Pharmacology, University of Turku, FI-20014 Turku, Finland.

Funding

Academy of Finland 315492Academy of Finland 337530Novo Nordisk Foundation 0068926Novo Nordisk Foundation 0075825
6 · The paper itself

Abstract

Molecular docking is a key method used in virtual screening (VS) campaigns to identify small-molecule ligands for drug discovery targets. While docking provides a tangible way to understand and predict the protein-ligand complex formation, the docking algorithms are often unable to separate active ligands from inactive molecules in practical VS usage. Here, a novel docking and shape-focused pharmacophore VS protocol is demonstrated for facilitating effective hit discovery using retinoic acid receptor-related orphan receptor gamma t (RORγt) as a case study. RORγt is a prospective target for treating inflammatory diseases such as psoriasis and multiple sclerosis. First, a commercial molecular database was flexibly docked. Second, the alternative docking poses were rescored against the shape/electrostatic potential of negative image-based (NIB) models that mirror the target's binding cavity. The compositions of the NIB models were optimized via iterative trimming and benchmarking using a greedy search-driven algorithm or brute force NIB optimization. Third, a pharmacophore point-based filtering was performed to focus the hit identification on the known RORγt activity hotspots. Fourth, free energy binding affinity evaluation was performed on the remaining molecules. Finally, twenty-eight compounds were selected for in vitro testing and eight compounds were determined to be low μM range RORγt inhibitors, thereby showing that the introduced VS protocol generated an effective hit rate of ~29%.

Indexed as

Drug DiscoveryNuclear Receptor Subfamily 1, Group F, Member 3LigandsMolecular Docking SimulationReceptors, Retinoic AcidTranscription FactorsTretinoinLigandsNuclear Receptor Subfamily 1, Group F, Member 3Receptors, Retinoic AcidTranscription FactorsTretinoinbrute force negative image-based optimization (BR-NiB)docking rescoringinflammationmolecular dockingnegative image-based rescoring (R-NiB)pharmacophore (PHA) filteringretinoic acid receptor-related orphan receptor gamma t (RORγt)virtual screening (VS)

Identifiers

PMID37110655
PMCPMC10145393

What Socratic 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 Socratic graph.