In Silico Discovery of ABZI Nitrogen Heterocycle STING Agonists via 3D-QSAR, Molecular Dynamics, and AI-Based Synthesis Prediction
(2026) In Pharmaceuticals 19(3).- Abstract
Background/Objectives: The stimulator of interferon genes (STING) pathway plays a central role in innate immune signaling and represents an attractive therapeutic target for cancer immunotherapy. Amidobenzimidazole (ABZI) derivatives have emerged as promising non-nucleotide STING agonists with improved drug-like properties compared to cyclic dinucleotides. However, current ABZI compounds still exhibit limited oral bioavailability and cross-species potency discrepancies. In addition, potential systemic toxicity remains a concern, indicating the need for further structural optimization. Methods: In this study, a comprehensive computer-aided drug design strategy was employed to systematically investigate ABZI derivatives and identify novel... (More)
Background/Objectives: The stimulator of interferon genes (STING) pathway plays a central role in innate immune signaling and represents an attractive therapeutic target for cancer immunotherapy. Amidobenzimidazole (ABZI) derivatives have emerged as promising non-nucleotide STING agonists with improved drug-like properties compared to cyclic dinucleotides. However, current ABZI compounds still exhibit limited oral bioavailability and cross-species potency discrepancies. In addition, potential systemic toxicity remains a concern, indicating the need for further structural optimization. Methods: In this study, a comprehensive computer-aided drug design strategy was employed to systematically investigate ABZI derivatives and identify novel STING agonists with enhanced activity and favorable pharmacokinetic profiles. A 3D quantitative structure–activity relationship (3D-QSAR) model was constructed using the Topomer CoMFA approach based on a dataset of 109 reported ABZI compounds. Guided by the contour map analysis, new chemical groups were introduced through a fragment growth method, generating a large virtual library. The library was subsequently filtered via molecular docking, molecular dynamics simulations, and MM-PBSA binding free energy calculations. Results: Among the newly designed ABZI compounds, five compounds displayed lower binding free energies than D59, with M13 and M44 showing reductions exceeding 6.7 kcal/mol. This work demonstrates the effectiveness of an integrated in silico design strategy for the discovery of novel STING agonists. Conclusions: The identified compounds represent promising candidates for subsequent experimental validation and may support the development of nitrogen heterocycle-based STING agonists for antitumor applications.
(Less)
- author
- Ren, Houcheng ; Jin, Yuhong ; Zhao, Baipu ; Peng, Xiangbing ; Zhao, Shan and Wang, Meiting LU
- organization
- publishing date
- 2026-03
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- 3D-QSAR, ABZI, AI synthesis prediction, free energy, molecular dynamics, STING agonists
- in
- Pharmaceuticals
- volume
- 19
- issue
- 3
- article number
- 387
- publisher
- MDPI AG
- external identifiers
-
- scopus:105035081910
- pmid:41901234
- ISSN
- 1424-8247
- DOI
- 10.3390/ph19030387
- language
- English
- LU publication?
- yes
- id
- c156b0fb-9652-4588-9ecf-c72b48e8ccf5
- date added to LUP
- 2026-07-06 15:13:18
- date last changed
- 2026-08-31 20:03:28
@article{c156b0fb-9652-4588-9ecf-c72b48e8ccf5,
abstract = {{<p>Background/Objectives: The stimulator of interferon genes (STING) pathway plays a central role in innate immune signaling and represents an attractive therapeutic target for cancer immunotherapy. Amidobenzimidazole (ABZI) derivatives have emerged as promising non-nucleotide STING agonists with improved drug-like properties compared to cyclic dinucleotides. However, current ABZI compounds still exhibit limited oral bioavailability and cross-species potency discrepancies. In addition, potential systemic toxicity remains a concern, indicating the need for further structural optimization. Methods: In this study, a comprehensive computer-aided drug design strategy was employed to systematically investigate ABZI derivatives and identify novel STING agonists with enhanced activity and favorable pharmacokinetic profiles. A 3D quantitative structure–activity relationship (3D-QSAR) model was constructed using the Topomer CoMFA approach based on a dataset of 109 reported ABZI compounds. Guided by the contour map analysis, new chemical groups were introduced through a fragment growth method, generating a large virtual library. The library was subsequently filtered via molecular docking, molecular dynamics simulations, and MM-PBSA binding free energy calculations. Results: Among the newly designed ABZI compounds, five compounds displayed lower binding free energies than D59, with M13 and M44 showing reductions exceeding 6.7 kcal/mol. This work demonstrates the effectiveness of an integrated in silico design strategy for the discovery of novel STING agonists. Conclusions: The identified compounds represent promising candidates for subsequent experimental validation and may support the development of nitrogen heterocycle-based STING agonists for antitumor applications.</p>}},
author = {{Ren, Houcheng and Jin, Yuhong and Zhao, Baipu and Peng, Xiangbing and Zhao, Shan and Wang, Meiting}},
issn = {{1424-8247}},
keywords = {{3D-QSAR; ABZI; AI synthesis prediction; free energy; molecular dynamics; STING agonists}},
language = {{eng}},
number = {{3}},
publisher = {{MDPI AG}},
series = {{Pharmaceuticals}},
title = {{In Silico Discovery of ABZI Nitrogen Heterocycle STING Agonists via 3D-QSAR, Molecular Dynamics, and AI-Based Synthesis Prediction}},
url = {{http://dx.doi.org/10.3390/ph19030387}},
doi = {{10.3390/ph19030387}},
volume = {{19}},
year = {{2026}},
}