Evidence map›Paper›PMID 37676596›Full record

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

Applications of Molecular Dynamics Simulations in Drug Discovery.

Sara AlRawashdeh, Khaled H Barakat

Abstract readReview
PubMed Publisher
In one paragraph

Review 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 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing 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

32 citing papers in PubMed.

  1. Artificial intelligence-assisted lead optimization in drug discovery: bridging computational advances and translational challenges.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2026
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  11. Discovery of Polyphenolic Compounds fromCurrent computer-aided drug design · 2026
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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

2 authors.

Sara AlRawashdehFaculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada.
Khaled H BarakatFaculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada. kbarakat@ualberta.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the current drug development process, molecular dynamics (MD) simulations have proven to be very useful. This chapter provides an overview of the current applications of MD simulations in drug discovery, from detecting protein druggable sites and validating drug docking outcomes to exploring protein conformations and investigating the influence of mutations on its structure and functions. In addition, this chapter emphasizes various strategies to improve the conformational sampling efficiency in molecular dynamics simulations. With a growing computer power and developments in the production of force fields and MD techniques, the importance of MD simulations in helping the drug development process is projected to rise significantly in the future.

Indexed as

Drug DiscoveryMolecular Dynamics SimulationMutationProtein ConformationDrug discoveryEnhanced samplingMolecular dynamics simulationsProtein druggability

Identifiers

PMID37676596

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.