Evidence map›Paper›PMID 39427127›Full record

ArticleBMC infectious diseases2024

Unraveling Cordia myxa's anti-malarial potential: integrative insights from network pharmacology, molecular modeling, and machine learning.

Yufei Miao, Wenkang Liu, Sarah Mohammed Saeed Alsallameh, Norah A Albekairi, Ziyad Tariq Muhseen, Christopher J Butch

Abstract read
In one paragraph

Article in BMC infectious diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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.

Yufei MiaoDepartment of Biomedical Engineering, College of Engineering and Applied Sciences, Nanjing University, Nanjing, 210093, China.
Wenkang LiuDepartment of Biomedical Engineering, College of Engineering and Applied Sciences, Nanjing University, Nanjing, 210093, China.
Sarah Mohammed Saeed AlsallamehDepartment of Medical Laboratories Techniques, College of Health and Medical Techniques, Gilgamesh Ahliya University Gau, Baghdad, Iraq.
Norah A AlbekairiCollege of Pharmacy, King Saud University, Post Box 2455, Riyadh, 11451, Saudi Arabia.
Ziyad Tariq MuhseenDepartment of Biomedical Engineering, College of Engineering and Applied Sciences, Nanjing University, Nanjing, 210093, China. Ziyad.tariq82@gmail.com.
Christopher J ButchDepartment of Biomedical Engineering, College of Engineering and Applied Sciences, Nanjing University, Nanjing, 210093, China. chrisbutch@gmail.com.

Funding

Fundamental Research Funds for the Central Universities 0213-14380238King Saud University RSPD2024R1035
6 · The paper itself

Abstract

Malaria is a potentially fatal infective illness caused due to parasites that belong to the Plasmodium genus, which are transferred to humans with the help of the stings of affected female Anopheles mosquitoes, and it persists as a serious public wellness problem worldwide. Cordia myxa is a medicinal plant that possesses various medicinal characteristics like antimicrobial, anti-inflammation, antioxidant, and antidiabetic activities, which makes it an important natural resource for the therapy of different maladies in traditional medicine. In this investigation, a certain network pharmacology method has been utilized to identify the potent active components, possible targets as well as signaling pathways present in C. myxa in relation to malaria therapy. The active compounds were submitted to molecular docking approaches to validate their successful activity against the potential targets. The study concluded that three constituents named cosmosiin, stigmastanol, robinetin, and quercetin were highly active and could regulate the expression of Interleukin 6 (IL6) and Cysteine-aspartic acid protease 3 (CASP3), which may act as a potential therapeutic target for malaria treatment. These analyses are validated by molecular dynamics simulation which reflects on the overall structural stability of the intermolecular conformation and interactions. These results can also be witnessed in simulation-based trajectories binding free energies, which concluded the significant role of electrostatic and van der Waals energies in total intermolecular interactions. Finally, we utilized machine learning to predict the anti-malarial activity of C. myxa compounds, comparing them with approved drugs. Using the Chemprop model and MAIP predictions, we assessed ten compounds, revealing their potential as lead anti-malarial agents. This study establishes a groundwork for comprehending the function of the anti-malaria action of C. myxa.

Indexed as

AntimalarialsMachine LearningMolecular Docking SimulationNetwork PharmacologyAnimalsHumansMalariaMolecular Dynamics SimulationPlant ExtractsAntimalarialsPlant ExtractsBioinformaticsCordia myxaMachine learningMalariaMolecular DockingNetwork pharmacologyProtein-protein Interaction

Identifiers

PMID39427127
PMCPMC11490058

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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.