| Beyond Acaricides: AI-Generated GRP78 Inhibitors as a Novel Strategy Against Tick-Borne CCHF Virus Transmission |
| Paper ID : 1121-IPCA5 (R2) |
| Authors |
|
Elina Khanehzar1, Fatemeh Shams1, Zakkyeh Telmadarraiy2, Faezeh Faghihi3, Amirsajad Jafari *4 11. Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran 2. Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz, Iran 21. Department of Medical Entomology and Vector Control, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran 2. Rahyan Novin Danesh (RND) University, Sari, Mazandaran, Iran 31. Cellular and Molecular Research Center, Iran University of Medical Sciences, Tehran, Iran 2. Immunogenetics Research Center, Mazandaran University of Medical Sciences, Sari, Iran 41. Department of Basic Sciences, School of Veterinary Medicine, Shiraz University, Shiraz, Iran
2. Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, Shiraz, Iran |
| Abstract |
| Crimean-Congo haemorrhagic fever (CCHF) remains a major public health threat in Iran, where multiple tick species transmit the CCHF virus (CCHFV). The primary vector, Hyalomma marginatum, coexists with other ixodid ticks, including Rhipicephalus sanguineus, H. anatolicum, H. asiaticum, and H. dromedarii, alongside less common species like H. schulzi, Dermacentor marginatus, and Haemaphysalis sulcata, all confirmed CCHFV carriers. Soft ticks (Ornithodoros lahorensis, Argas reflexus) further complicate transmission dynamics. Iran reports over 1,200 annual CCHF cases, with a 15–30% mortality rate, particularly in Sistan-va-Baluchestan, Isfahan, and Fars. Climate change and agricultural expansion have expanded tick habitats, increasing human exposure. Seroprevalence studies show 4–8% CCHFV exposure among high-risk groups like livestock workers. Targeting glucose-regulated protein 78 (GRP78), a host chaperone critical for viral replication and tick-host interactions, offers a novel intervention strategy. Here, we employ large language models (LLMs) to design de novo GRP78 inhibitors, disrupting both viral replication and vector-mediated transmission. Using DeepSeek and Grok, we generated 100 drug-like molecules mimicking bioactive natural scaffolds. The top 10 candidates underwent pharmacokinetic screening (SwissADME, Lipinski’s rule compliance) and molecular docking (AutoDock Vina) against GRP78 (PDB ID: 6ASY), with acetylsalicylic acid as a control. Two lead compounds exhibited superior binding affinities (−8.5 and −8.4 kcal/mol vs. −7.1 kcal/mol for control), adhering to drug-likeness criteria and demonstrating low toxicity in ADMET predictions. These AI-designed inhibitors merge natural product-inspired chemistry with computational precision, offering dual antiviral and vector-targeting potential. This study highlights LLMs as transformative tools for CCHF drug discovery. Future work should validate these compounds against Iranian CCHFV strains and Hyalomma saliva-enhanced models to assess their dual therapeutic and transmission-blocking efficacy. This approach addresses the urgent need for CCHF interventions in endemic regions by bridging traditional knowledge and AI-driven innovation. |
| Keywords |
| AI drug discovery, CCHF, de novo design, GRP78 inhibitors, Large Language Models, Natural products |
| Status: Abstract Accepted |
