Drug repurposing by in silico prediction of cyclizine derivatives as antihyperlipemic agents
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…
How strong is the evidence?
Evidence Hub reads this as a preprint, done in computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
Read the paper
Related studies
- Artificial Intelligence in Medicine: Cross-Sectional Study Among Medical Students on Application, Education, and Ethical Aspects
- Information quality of videos related to esophageal cancer on tiktok, kwai, and bilibili: a cross-sectional study
- The quality and reliability of short videos about hypertension on TikTok: a cross-sectional study
- Quality and reliability evaluation of pancreatic cancer-related video content on social short video platforms: a cross-sectional study
- Quality and reliability of pediatric pneumonia related short videos on mainstream platforms: cross-sectional study
- Association between metabolic score for insulin resistance (METS-IR) and hypertension: a cross-sectional study based on NHANES 2007–2018
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.