Evidence map›Paper›PMID 38028536›Full record

ArticleFrontiers in molecular biosciences2023

Thermal titration molecular dynamics (TTMD): shedding light on the stability of RNA-small molecule complexes.

Andrea Dodaro, Matteo Pavan, Silvia Menin, Veronica Salmaso, Mattia Sturlese, Stefano Moro

Open access · goldAbstract read
In one paragraph

Article in Frontiers in molecular biosciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

  1. P2YACS pharmacology & translational science · 2025
    Article
  2. Article
  3. Thermal Titration Molecular Dynamics: The Revenge of the Fragments.Journal of chemical information and modeling · 2025
    Article
  4. Article
  5. Potent and Selective Human 5-HTJournal of medicinal chemistry · 2024
    Article
  6. Lipid Trolling to Optimize AJournal of medicinal chemistry · 2024
    Article
  7. 2-Substituted (N)-Methanocarba AACS pharmacology & translational science · 2024
    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

6 authors at 1 institution in 1 country.

Andrea DodaroMolecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.
Matteo PavanMolecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.
Silvia MeninMolecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.
Veronica SalmasoMolecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.
Mattia SturleseMolecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.
Stefano MoroMolecular Modeling Section (MMS), Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Padova, Italy.
University of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ribonucleic acids are gradually becoming relevant players among putative drug targets, thanks to the increasing amount of structural data exploitable for the rational design of selective and potent binders that can modulate their activity. Mainly, this information allows employing different computational techniques for predicting how well would a ribonucleic-targeting agent fit within the active site of its target macromolecule. Due to some intrinsic peculiarities of complexes involving nucleic acids, such as structural plasticity, surface charge distribution, and solvent-mediated interactions, the application of routinely adopted methodologies like molecular docking is challenged by scoring inaccuracies, while more physically rigorous methods such as molecular dynamics require long simulation times which hamper their conformational sampling capabilities. In the present work, we present the first application of Thermal Titration Molecular Dynamics (TTMD), a recently developed method for the qualitative estimation of unbinding kinetics, to characterize RNA-ligand complexes. In this article, we explored its applicability as a post-docking refinement tool on RNA in complex with small molecules, highlighting the capability of this method to identify the native binding mode among a set of decoys across various pharmaceutically relevant test cases.

Indexed as

interaction fingerprintsligand-RNA complexmolecular dockingmolecular dynamicsthermal titration molecular dynamicsTTMD

Identifiers

PMID38028536
PMCPMC10679717
OpenAlexW4388646598

What OpenQuestion 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 OpenQuestion graph.