ArticleIn silico pharmacology2023
Drug repurposing by in silico prediction of cyclizine derivatives as antihyperlipemic agents.
Article in In silico pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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.
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Who cites it
4 citing papers in PubMed, 12 citations in OpenAlex.
- Predictive models and WTAP targeting for idiopathic pulmonary fibrosis (IPF).Scientific reports · 2025Article
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- Targeting MERTK tyrosine kinase: Virtual screening and molecular dynamics insights for anti-cancer drug development.PloS one · 2025Article
- Identification of DprE1 inhibitors for tuberculosis through integrated in-silico approaches.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiovascular diseases are the primary factor for increased mortality rates around the world. Atherosclerosis brought on by high serum cholesterol can result in coronary heart disease (CHD). The risk of CHD is markedly reduced by lowering serum cholesterol levels. Scientists across the world are inventing new treatment regimens for lowering blood lipid levels. In this work, we repurposed the already established drugs, i.e., cyclizine derivatives as antihyperlipidemic agents. The repurposing was done based on the similarity of the selected cyclizine derivatives with the already established antihyperlipidemic drug, fenofibrate. Computational studies were performed and the 16 cyclizine derivatives docked against PPAR. alpha scored higher than fenofibrate. Lifarizine and medibazine outperform fenofibrate inmmgbsa. Fenofibrate, etodroxizine, meclizine, and cinnarizine had similar mmgbsa scores. The ADME properties of these compounds were performed and from that etodroxizine and levocetirizine were found to have better properties. The computational studies were performed using the Schrodinger software, maestro 12.8. The "Protein Preparation Wizard" module in the Maestro panel was used to create the protein structure and OPLS4 force field was used for energy minimization. The maestro builder panel's "Ligprep", "Receptor Grid Generation" and "Ligand Docking" modules were then used to prepare ligands, receptor grids and to perform docking respectively. MMGBSA was performed on the "prime MMGBSA" segment. Using the "Qikprop" setting in the maestro panel, a number of ADMET properties were predicted, and the program was run in default mode using vsgb as the solvation model.
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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 OpenQuestion graph.