Title

Computational insights for target prioritization and pesticide effects on intrauterine growth restriction (IUGR)

Authors

Adarsh Kumar Shukla¹, Anuj Kumar Tyagi^{1, 2,} *& Sandeep Kumar³

Affiliation

¹Department of Multidisciplinary Research Unit, Dr. Bhimrao Ramji Ambedkar Government Medical College, Kannauj, Uttar Pradesh, India, 209732; ²Department of Microbiology, Dr. Bhimrao Ramji Ambedkar Government Medical College, Kannauj, Uttar Pradesh, India, 209732; ³Department of Community Medicine, Autonomous State Medical College, Kaushambi, Uttar Pradesh, India, 212207; *Corresponding author

Email

Adarsh Kumar Shukla - E-mail: adarshshukla349@gmail.com

Anuj Kumar Tyagi -E-mail: tyagi.aiims@gmail.com

Sandeep Kumar - E-mail: sandeepstatc28@gmail.com

Article Type

Research Article

Date

Received June 1, 2026; Revised June 30, 2026; Accepted June 30, 2026, Published June 30, 2026

Abstract

Intrauterine growth restriction (IUGR) is a leading cause of maternal and neonatal morbidity and mortality, particularly in low- and middle-income countries. Placental transcriptomics data were analysed to mapped dysregulated pathways via STRING-based PPI networks, identifying hubs and validating pesticide targets by molecular simulations. Rank-based prioritization identified IL7R, LCK and ZAP70 as top hub proteins driving placental dysfunction with cypermethrin exhibiting the lowest binding affinities across them (docking scores: -7.7, -8.7, -9.3 kcal/mol, respectively). Molecular dynamics simulations confirmed the stability of these docked complexes, while toxicity profiling indicated genotoxic potential for permethrin and high aquatic toxicity for deltamethrin. Thus, we show the critical molecular mediators linking pyrethroid exposure to IUGR, suggesting further experimental validation to support maternal health risk assessment.

Keywords

Comparative toxicogenomics, intrauterine growth restriction (IUGR), molecular simulations, placental transcriptomic data, toxicity profiling

Citation

Shukla et al. Bioinformation 22(6): 3501-3509 (2026)

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.