Molecular insights into the role of Estrogen Receptor Beta in Ecdysterone Mediated Anabolic Activity

Ecdysterone, often dubbed a "natural steroid," has garnered significant attention among athletes for its reputed growth-promoting and anabolic properties. Unlike synthetic anabolic steroids, which are classified as controlled substances, ecdysteroids remain largely unregulated in many countries and are widely marketed as dietary supplements. Notably, ecdysterone has been included in the World Anti-Doping Agency (WADA) monitoring program, highlighting its potential impact on athletic performance and raising questions about its regulation. Emerging evidence indicates that, unlike traditional anabolic steroids that act primarily via the Androgen Receptor (AR), ecdysterone's anabolic effects may be mediated through Estrogen Receptors (ERs), particularly Estrogen Receptor beta (ERβ). Despite these insights, the precise molecular mechanisms underlying ecdysterone's biological activity remain poorly characterized, particularly from an in-silico perspective. This paper aims to address these gaps by exploring ecdysterone's mechanism of action through computational and molecular modeling approaches. This study employs an advanced computational framework to unravel the binding dynamics and interaction mechanisms of ecdysterone with Androgen Receptor (AR), Estrogen Receptor alpha (ERα), and Estrogen Receptor beta (ERβ). Using chemical descriptor analysis, inter-molecular interaction mapping, and all-atom molecular dynamics simulations spanning 250 ns for each system, the study reveals that ecdysterone preferentially binds to ERβ, forming stable and compact complexes characterized by minimal per-residue fluctuations as evident in the average RMSD, RMSF, and Rg values observed for ERβ - Ecdysterone as 1.98 ± 0.31 Å, 1.07 ± 0.52 Å, and 18.44 ± 0.08 Å respectively which are significantly comparable with the ERβ - native complex, while high hydrogen bond occupancy was also observed for ERβ - Ecdysterone complex. Although binding free energy calculations suggest stronger interactions with ERα, the associated high fluctuations diminish its binding efficacy. In contrast, interactions with ERβ remain consistent and robust. Machine learning-based principal component analysis highlights coordinated motion patterns, while free energy profiles demonstrate stable energy basins with minimal variation. These findings underscore the pivotal role of ERβ in mediating ecdysterone's anabolic effects, distinguishing it from traditional androgenic steroids, and provide critical insights into its unique mechanism of action. This work lays the foundation for further exploration of ecdysterone as a potential anabolic agent.