ArticleCurrent computer-aided drug design2025
Article in Current computer-aided drug design, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- Benchmark Investigation of SARS-CoV-2 Mutants' Immune Escape with 2B04 Murine Antibody: A Step Towards Unraveling a Larger Picture.Current issues in molecular biology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundSARS-CoV-2's remarkable capacity for genetic mutation enables it to swiftly adapt to environmental changes, influencing critical attributes, such as antigenicity and transmissibility. Thus, multi-target inhibitors capable of effectively combating various viral mutants concurrently are of great interest. This study aimed to investigate natural compounds that could unitedly inhibit spike glycoproteins of various Omicron mutants. Implementation of various in silico approaches allows us to scan a library of compounds against a variety of mutants in order to find the ones that would inhibit the viral entry disregard of occurred mutations.
methodsAn extensive analysis of relevant literature was conducted to compile a library of chemical compounds sourced from citrus essential oils. Ten homology models representing mutants of the Omicron variant were generated, including the latest 23F clade (EG.5.1), and the compound library was screened against them. Subsequently, employing comprehensive molecular docking and molecular dynamics simulations, we successfully identified promising compounds that exhibited sufficient binding efficacy towards the receptor binding domains (RBDs) of the mutant viral strains. The scoring of ligands was based on their average potency against all models generated herein, in addition to a reference Omicron RBD structure. Furthermore, the toxicity profile of the highest-scoring compounds was predicted.
resultsOut of ten built homology models, seven were successfully validated and showed to be reliable for
conclusionThe outcomes of this investigation hold significant potential for the utilization of a homology modeling approach for the prediction of RBD's secondary structure based on its sequence when the 3D structure of a mutated protein is not available. This opens the opportunities for further advancing the drug discovery process, offering novel avenues for the development of multifunctional, non-toxic natural medications.
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What Socratic holds
Registered trials
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 Socratic graph.