Literature DB >> 33917986

Deeper Insights on Cnesmone javanica Blume Leaves Extract: Chemical Profiles, Biological Attributes, Network Pharmacology and Molecular Docking.

Ahmad J Obaidullah1, Mohammed M Alanazi1, Nawaf A Alsaif1, Wael A Mahdi2, Omer I Fantoukh3, Abu Montakim Tareq4, Saad Ahmed Sami5, Ali M Alqahtani6, Talha Bin Emran7.   

Abstract

This study assessed the anxiolytic and antidepressant activities of a methanol leaves extract of Cnesmone javanica (CV) in Swiss albino mice. The study found a significant increase in the percentage of time spent in the open arms of an elevated plus maze and in the incidence of head dipping in hole-board tests following the administration of 400 mg/kg of CV or 1 mg/kg diazepam. Moreover, a significant (p < 0.001) dose-dependent reduction was observed in the immobility time following CV (200 and 400 mg/kg) and fluoxetine (20 mg/kg) administration for forced swimming and tail suspension tests. Gas chromatography-mass spectroscopy (GC-MS) analysis identified 62 compounds in CV, consisting primarily of phenols, terpenoids, esters, and other organic compounds. A molecular docking study was performed to assess the anxiolytic and antidepressant effects of 45 selected compounds against human serotonin transporter and potassium channels receptors. Network pharmacology was performed to predict the pathways involved in these neuropharmacological effects. Overall, CV demonstrated significant and dose-dependent anxiolytic and antidepressant effects due to the presence of several bioactive phytoconstituents, which should be further explored using more advanced and in-depth mechanistic research.

Entities:  

Keywords:  Cnesmone javanica; GC–MS; antidepressant; anxiolytic; molecular docking; network pharmacology

Year:  2021        PMID: 33917986     DOI: 10.3390/plants10040728

Source DB:  PubMed          Journal:  Plants (Basel)        ISSN: 2223-7747


  3 in total

1.  Network Pharmacology- and Molecular Docking-Based Identification of Potential Phytocompounds from Argyreia capitiformis in the Treatment of Inflammation.

Authors:  Ahmad J Obaidullah; Mohammed M Alanazi; Nawaf A Alsaif; Ashwag S Alanazi; Hussam Albassam; Alanazi Az; Osama I Alwassil; Ali M Alqahtani; Abu Montakim Tareq
Journal:  Evid Based Complement Alternat Med       Date:  2022-01-31       Impact factor: 2.629

2.  Computational screening and biochemical analysis of Pistacia integerrima and Pandanus odorifer plants to find effective inhibitors against Receptor-Binding domain (RBD) of the spike protein of SARS-Cov-2.

Authors:  Gobindo Kumar Paul; Shafi Mahmud; Afaf A Aldahish; Mirola Afroze; Suvro Biswas; Swagota Briti Ray Gupta; Mahmudul Hasan Razu; Shahriar Zaman; Md Salah Uddin; Mohammed H Nahari; Mohammed Merae Alshahrani; Mohammed Abdul Rahman Alshahrani; Mala Khan; Md Abu Saleh
Journal:  Arab J Chem       Date:  2021-12-01       Impact factor: 5.165

3.  Antistroke Network Pharmacological Prediction of Xiaoshuan Tongluo Recipe Based on Drug-Target Interaction Based on Deep Learning.

Authors:  Yongfu Zhou
Journal:  Comput Math Methods Med       Date:  2022-08-02       Impact factor: 2.809

  3 in total

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