Evidence map›Paper›PMID 36169867›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Computational Chemistry and Molecular Modeling of Reversible MAO Inhibitors.

Kemal Yelekçi, Safiye Sağ Erdem

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
4.0field-weighted citation impact, top 5% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. 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

2 authors at 2 institutions in 1 country.

Kemal YelekçiDepartment of Bioinformatics and Genetics, Faculty of Engineering and Natural Sciences, Kadir Has University, Istanbul, Turkey. yelekci@khas.edu.tr.
Safiye Sağ ErdemDepartment of Chemistry, Faculty of Arts and Sciences, Marmara University, Istanbul, Turkey.
Kadir Has University · TRMarmara University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proper elucidation of drug-target interaction is one of the most significant steps at the early stages of the drug development research. Computer-aided drug design tools have substantial contribution to this stage. In this chapter, we specifically concentrate on the computational methods widely used to develop reversible inhibitors for monoamine oxidase (MAO) isozymes. In this context, current computational techniques in identifying the best drug candidates showing high potency are discussed. The protocols of structure-based drug design methodologies, namely, molecular docking, in silico screening, and molecular dynamics simulations, are presented. Employing case studies of safinamide binding to MAO B, we demonstrate how to use AutoDock 4.2.6 and NAMD software packages.

Indexed as

Computational ChemistryMonoamine Oxidase InhibitorsIsoenzymesMolecular Docking SimulationMonoamine OxidaseStructure-Activity RelationshipIsoenzymesMonoamine OxidaseMonoamine Oxidase InhibitorsDockingMolecular dynamicsMonoamine oxidaseVirtual screening

Identifiers

PMID36169867
OpenAlexW4297458027

What OpenQuestion holds

Textmetadata
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.