Exploring the Therapeutic Potential of Phytochemicals as Plasminogen Activator Inhibitor-1 Inhibitors: A Computational Study

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Authors: Dima Joujeh, Mohammad Aabed, Mohammed Alsarakbi, Abdalwhab Alrhmon
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Abstract

The search for new, effective therapeutic agents from natural sources has become a central focus in modern drug discovery. This study aimed to identify potential Plasminogen Activator Inhibitor-1 (PAI-1) inhibitors from natural sources using a purely in silico approach. A total of 26 phytochemicals were screened, alongside three standard inhibitors. Molecular docking analysis was performed using the HDOCK web server. Subsequently, the SwissADME server was used to predict key pharmacokinetic properties, and compliance with Lipinski's Rule of Five, to assess the drug-likeness of the compounds.The docking results revealed that several phytochemicals, including diosmin, verbascoside, and epigallocatechin gallate, exhibited more favorable docking scores than the standard inhibitors. However, a drug-likeness analysis showed that these compounds failed to comply with Lipinski's rules. In contrast, compounds such as chlorogenic acid and quercetin not only achieved docking scores superior to the standards but also fully complied with Lipinski's criteria.Based on a holistic evaluation, chlorogenic acid was identified as the most promising candidate. It demonstrated a superior docking score, a favorable ADME profile, and excellent drug-likeness. The docking analysis also showed that chlorogenic acid interacts with key residues such as THR 93 and ASP 95, which are also targeted by the standard inhibitors TM5441 and tiplaxtinin. This makes it a strong lead compound for further investigation as a PAI-1 inhibitor. Despite its promising attributes, chlorogenic acid's predicted low bioavailability and gastrointestinal absorption present a significant challenge. Future work should focus on optimizing its formulation or exploring non-oral delivery methods to harness its full therapeutic potential.

Fields of Study & Subjects

Computational Drug Discovery Methods Bioactive natural compounds Medicinal Plant Research

Publication details

Journal / source
Journal of Advanced Pharmacy Research
Volume
10
Issue
1
Pages
19–28
Publication date
1 January 2026
Language
EN