Evidence map›Paper›PMID 38386097›Full record

ArticleJournal of molecular modeling2024

In silico elucidation for the identification of potential phytochemical against ACE-II inhibitors.

Ekambaram Gayathiri, Palanisamy Prakash, Kuppusamy Selvam, Thangaraj Pratheep, Somdatta Y Chaudhari, Subramanian Deepika Priyadharshini

Abstract read
PubMed Publisher
In one paragraph

Article in Journal of molecular modeling, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Ekambaram Gayathiri *Department of Plant Biology and Plant Biotechnology, Guru Nanak College (Autonomous), Chennai, 600042, Tamil Nadu, India. gay3purush@gmail.com.
Palanisamy Prakash *Department of Botany, Periyar University, TamilNadu, Periyar Palkalai Nagar, Salem, 636011, India. drprakas2014@gmail.com.
Kuppusamy SelvamDepartment of Botany, Periyar University, TamilNadu, Periyar Palkalai Nagar, Salem, 636011, India.
Thangaraj PratheepDepartment of Biotechnology, Rathinam College of Arts and Science, Coimbatore, 641021, Tamil Nadu, India.
Somdatta Y ChaudhariDepartment of Pharmaceutical Chemistry, Modern College of Pharmacy, Nigdi, Pune, India.
Subramanian Deepika PriyadharshiniDepartment of Chemistry, Vellalar College for Women, Thindal, Erode-638012, Tamil Nadu, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextThe present study aims to investigate the therapeutic potential of phytocompounds derived from Annona reticulata leaves for the treatment of hypertension, utilizing computational methodologies. Gaining a comprehensive understanding of the molecular interactions between neophytadiene and γ-sitosterol holds significant importance in the advancement of innovative therapeutic approaches. This study aims to examine the inhibitory effects of neophytadiene and γ-sitosterol using molecular docking and dynamics simulations. Additionally, we will evaluate their stability and predict their drug-like properties as well as their ADME/toxicity profiles. Neophytadiene and γ-sitosterol have a substantial binding affinity with 1O8A, as shown by the docking study. The stability of the complexes was confirmed through molecular dynamics simulations, while distinct clusters were identified using PCA. These findings suggest the presence of potential stabilizers. The drug-likeness and ADME/toxicity predictions revealed positive characteristics, such as efficient absorption rates, limited distribution volume and non-hazardous profiles. The neophytadiene and γ-sitosterol exhibit potential as hypertension medication options. Computational investigations reveal that these compounds exhibit high affinity for binding, stability and favourable pharmacokinetic properties. The results of this study lay the groundwork for additional experimental verification and highlight the promising prospects of utilizing natural compounds in the field of pharmaceutical research.

methodsTarget proteins (1O8A) were used to perform molecular docking with representative molecules. Stability, conformational changes and binding energies were assessed through molecular dynamics simulations lasting 100 ns. Principal component analysis (PCA) was utilized to analyze molecular dynamics (MD) simulation data, to identify potential compounds that could stabilize the main protease. The safety and pharmacokinetic profiles of the compounds were evaluated through drug-likeness and ADME/toxicity predictions.

Indexed as

AnnonaCardiovascular AgentsAngiotensin-Converting Enzyme InhibitorsMolecular Docking SimulationPhytochemicalsAngiotensin-Converting Enzyme InhibitorsCardiovascular AgentsPhytochemicalsHypertensionLisinoprilMolecular dynamics simulationsToxicity analysis

Identifiers

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.