Evidence map›Paper›PMID 39584017›Full record

ArticleCommunications in information and systems2024

Docking strategies for predicting protein-ligand interactions and their application to structure-based drug design.

Zhiwei Ma, Abeeb Ajibade, Xiaoqin Zou

Abstract read
In one paragraph

Article in Communications in information and systems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
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  4. Review
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  9. Review
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  11. Article
  12. Frontiers in bioinformatics · 2026
    Review
  13. 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

3 authors.

Zhiwei MaDalton Cardiovascular Research Center, University of Missouri-Columbia USA.
Abeeb AjibadeDalton Cardiovascular Research Center, University of Missouri-Columbia.
Xiaoqin ZouDalton Cardiovascular Research Center, University of Missouri-Columbia.

Funding

MANIPULATING IKS AS A THERAPEUTIC APPROACH TO CARDIAC ARRHYTHMIASR01HL126774 · NHLBI · WASHINGTON UNIVERSITY · PI CUI, JIANMIN · 2015 to 2018
$3.1M
Structure prediction and in silico screening of protein-peptide interactionsR35GM136409 · NIGMS · UNIVERSITY OF MISSOURI-COLUMBIA · PI XIAOQIN ZOU · 2020 to 2026
$2.9M
A full spectrum rational approach to identify antiarrhythmic agents targeting IKs ChannelsR01HL166628 · NHLBI · STATE UNIVERSITY NEW YORK STONY BROOK · PI Jianmin Cui, RICHARD Z LIN · 2023 to 2026
$2.8M
NHLBI NIH HHS R01 HL126774NHLBI NIH HHS R01 HL166628NIGMS NIH HHS R35 GM136409
6 · The paper itself

Abstract

Molecular docking stands as a pivotal element in the realm of computer-aided drug design (CADD), consistently contributing to advancements in pharmaceutical research. In essence, it employs computer algorithms to identify the "best" match between two molecules, akin to solving intricate three-dimensional jigsaw puzzles. At a more stringent level, the molecular docking challenge entails predicting the accurate bound association state based on the atomic coordinates of two molecules. This process assumes particular significance in unraveling the mechanistic intricacies of physicochemical interactions at the atomic scale. Notably, the application of docking, especially in the context of protein-small molecule interactions, holds wide-ranging implications for structure-based drug design, given the prevalent use of small compounds as drug candidates. This study provides an overview of docking methodologies, delves into recent key developments, elucidates the physicochemical underpinnings of molecular recognition in protein-ligand interactions, and concludes by addressing the applications of docking in virtual screening, alongside current challenges within existing docking methods.

Indexed as

Free energy of bindingMolecular dockingProtein-ligand interactionsStructure-based drug designVirtual screening

Identifiers

PMID39584017
PMCPMC11583305

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Registered trials

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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.