Evidence map›Paper›PMID 37497547›Full record

ArticleFrontiers in microbiology2023

Development of a new drug candidate for the inhibition of Lassa virus glycoprotein and nucleoprotein by modification of evodiamine as promising therapeutic agents.

Shopnil Akash, Javiera Baeza, Sajjat Mahmood, Nobendu Mukerjee, Vetriselvan Subramaniyan, Md Rezaul Islam, Gaurav Gupta, Vinibha Rajakumari, Suresh V Chinni, Gobinath Ramachawolran and 4 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

9 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. 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

14 authors at 12 institutions in 6 countries.

Shopnil AkashDepartment of Pharmacy, Faculty of Allied Health Sciences, Daffodil International, University, Dhaka, Bangladesh.
Javiera BaezaCenter for Bioinformatics and Molecular Simulation, Universidad de Talca, Talca, Chile.
Sajjat MahmoodDepartment of Microbiology, Jagannath University, Dhaka, Bangladesh.
Nobendu Mukerjee *Department of Microbiology, West Bengal State University, West Bengal, Kolkata, India.
Vetriselvan Subramaniyan *Pharmacology Unit, Jeffrey Cheah School of Medicine and Health Sciences, MONASH University, Jalan Lagoon Selatan, Bandar Sunway, Selangor, Malaysia.
Md Rezaul IslamDepartment of Pharmacy, Faculty of Allied Health Sciences, Daffodil International, University, Dhaka, Bangladesh.
Gaurav GuptaSchool of Pharmacy, Suresh Gyan Vihar University, Jagatpura, Jaipur, India.
Vinibha RajakumariFaculty of Foundation, MAHSA University, Selangor, Malaysia.
Suresh V ChinniDepartment of Biochemistry, Faculty of Medicine, Bioscience, and Nursing, MAHSA University, Selangor, Malaysia.
Gobinath RamachawolranDepartment of Foundation, RCSI & UCD Malaysia Campus, Pulau Pinang, Malaysia.
Fayez M SalehDepartment of Medical Microbiology, Faculty of Medicine, University of Tabuk, Tabuk, Saudi Arabia.
Ghadeer M AlbadraniDepartment of Biology, College of Science, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Amany A SayedDepartment of Zoology, Faculty of Science, Cairo University, Giza, Egypt.
Mohamed M Abdel-DaimDepartment of Pharmaceutical Sciences, Pharmacy Program, Batterjee Medical College, Jeddah, Saudi Arabia.
Daffodil International University · BDMahsa University · MYCairo University · EGJagannath University · BDMonash University Malaysia · MYPrincess Nourah bint Abdulrahman University · SARCSI & UCD Malaysia Campus · MYSuez Canal University · EGUniversity of Chile · CLUniversity of Tabuk · SAUttaranchal University · INWest Bengal State University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Lassa virus (LASV), an RNA virus prevalent in West and Central Africa, causes severe hemorrhagic fever with a high fatality rate. However, no FDA-approved treatments or vaccines exist. Two crucial proteins, LASV glycoprotein and nucleoprotein, play vital roles in pathogenesis and are potential therapeutic targets. As effective treatments for many emerging infections remain elusive, cutting-edge drug development approaches are essential, such as identifying molecular targets, screening lead molecules, and repurposing existing drugs. Bioinformatics and computational biology expedite drug discovery pipelines, using data science to identify targets, predict structures, and model interactions. These techniques also facilitate screening leads with optimal drug-like properties, reducing time, cost, and complexities associated with traditional drug development. Researchers have employed advanced computational drug design methods such as molecular docking, pharmacokinetics, drug-likeness, and molecular dynamics simulation to investigate evodiamine derivatives as potential LASV inhibitors. The results revealed remarkable binding affinities, with many outperforming standard compounds. Additionally, molecular active simulation data suggest stability when bound to target receptors. These promising findings indicate that evodiamine derivatives may offer superior pharmacokinetics and drug-likeness properties, serving as a valuable resource for professionals developing synthetic drugs to combat the Lassa virus.

Indexed as

ADMETdrug discoveryemerging viral infectionsevodiamineLassa fever virusmolecular dockingmolecular dynamics simulation

Identifiers

PMID37497547
PMCPMC10366616
OpenAlexW4383911989

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.