# Targeting Integrin β3: novel antiplatelet lignans 6’-Hydroxyjusticidin B and Neojusticin A from Justicia procumbens unveiled via multi-omics and biophysical validation

## TL;DR

This study identifies two natural compounds from Justicia procumbens that target integrin β3, offering safer and more effective antiplatelet therapy options for thrombotic disorders.

## Contribution

The study introduces a target-driven strategy to identify novel antiplatelet lignans with validated molecular targets and binding affinities.

## Key findings

- Integrin β3 (ITGB3) was identified as the direct molecular target of 6'-Hydroxyjusticidin B and Neojusticin A.
- High-affinity binding was confirmed with Kd values of 0.0642 ± 0.005 μM for 6'-HJB and 0.0097 ± 0.001 μM for Neo-A.
- Structural features like C-6 hydroxylation and a fused furan ring enhance target specificity and COX-1 interaction.

## Abstract

Thrombotic disorders remain a global health burden, necessitating novel antiplatelet agents with improved safety and efficacy. This study investigates the molecular mechanisms of two lignans, 6'-Hydroxyjusticidin B (6'-HJB) and Neojusticin A (Neo-A), isolated from Justicia procumbens L., through an innovative target-driven strategy integrating LC/MS, proteomics, network pharmacology, and biophysical validation. For the first time, integrin β3 (ITGB3) was identified as their direct molecular target, with microscale thermophoresis (MST) confirming high-affinity binding, the dissociation constant (Kd) = 0.0642 ± 0.005 μM for 6'-HJB; 0.0097 ± 0.001 μM for Neo-A. This study not only elucidates the structural basis of their activity-C-6 hydroxylation in 6'-HJB enhances ITGB3 specificity, whereas Neo-A’s fused furan ring optimizes COX-1 interaction, but also establishes a paradigm shift from phenotypic screening to target-validated natural product research. The findings position 6'-HJB and Neo-A as promising candidates for the development of safer, ITGB3-mediated antithrombotic therapies, with future efforts directed toward structural optimization and preclinical validation.