Evidence map›Paper›PMID 37676597›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

Molecular Dynamics Simulation-Based Prediction of Glycosaminoglycan Interactions with Drug Molecules.

Martyna Maszota-Zieleniak, Sergey A Samsonov

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.4field-weighted citation impact, top 15% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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 1 institution in 1 country.

Martyna Maszota-ZieleniakFaculty of Chemistry, University of Gdańsk, Gdańsk, Poland.
Sergey A SamsonovFaculty of Chemistry, University of Gdańsk, Gdańsk, Poland. sergey.samsonov@ug.edu.pl.
University of Gdańsk · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glycosaminoglycans (GAGs) are a class of long linear anionic periodic polysaccharides. Their biological activities are very broad including tissue remodeling, regulation of cell proliferation, cell migration, cell differentiation, participation in bacterial/viral infections, and immune response. They can interact with many important biomolecular partners in the extracellular matrix of the cell including small drug molecules. Recently, several GAG-bioactive small molecule complexes have been experimentally and theoretically studied. Some of these compounds in complexes with GAGs may potentially interfere with protein-GAG or peptide-GAG multimolecular systems affecting the processes of cellular differentiation or have anti-inflammatory, antiviral as well as antithrombotic effects. Although many studies have been conducted on GAG-drug complexes, the molecular mechanisms of the formation of such complexes are still poorly understood. At the same time, the complexity of their physicochemical properties renders the use of both experimental and computational methods to study these molecular systems challenging. Here, we present the molecular dynamics-based protocols successfully employed to in silico analyze GAG-small molecule interactions.

Indexed as

BacteriophagesGlycosaminoglycansAntiviral AgentsCell DifferentiationMolecular Dynamics SimulationAntiviral AgentsGlycosaminoglycansDrug moleculesFree energy calculationsGlycosaminoglycanMM-GBSAMolecular dockingMolecular dynamicsOligomeric stacksSulfation pattern

Identifiers

PMID37676597
OpenAlexW4386500790

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.