Integrated computational-experimental pipeline for CHK1 inhibitor discovery: structure-based identification of novel
Dhanushya Gopal1, Manasa Pacharla1, Nehal Arvind Kumar1
1Department of Pharmacology, Sri Ramachandra Faculty of Pharmacy, Sri Ramachandra Institute of Higher Education and Research (Deemed to be University), Chennai, India.
Abstract:
Checkpoint kinase 1 (CHK1) plays a critical role in DNA damage response and cell cycle regulation, making it an attractive target for cancer therapy. However, clinical translation of CHK1 inhibitors has been limited by selectivity issues, dose-limiting toxicities, and drug resistance mechanisms, necessitating the development of novel inhibitors with improved therapeutic profiles. We developed an integrated computational-experimental pipeline for CHK1 inhibitor discovery. Starting with 492,534 compounds from the Specs database, we applied PAINS filtering, molecular fingerprinting (ECFP4), and dimensionality reduction (UMAP with K-means clustering). Structure-based virtual screening included e-pharmacophore modeling, molecular docking (Schrödinger's Glide), and 200-ns molecular dynamics simulations with MM-GBSA calculations. Lead compounds were evaluated for ADME properties and synthetic accessibility. The top candidate was validated in triple-negative breast cancer cell lines MDA-MB-231 and MDA-MB-468 using MTT assays. The pipeline identified 544 diverse compounds for analysis. Five compounds showed favorable CHK1 binding profiles. AO-022/43514723 emerged as the lead with a docking score of -9.205 kcal/mol, forming stable interactions with hinge region residues GLU85 and CYS87. Molecular dynamics confirmed complex stability. Scaffold analysis revealed novel chemotype diversity distinct from existing clinical inhibitors. ADME profiling showed drug-like properties with acceptable synthetic accessibility (SA score = 2.93). In vitro validation demonstrated dose-dependent cytotoxicity with IC₅₀ values of 51.53 μM (MDA-MB-231) and 64.02 μM (MDA-MB-468), representing micromolar potency typical of early-stage computational hits requiring further optimization. This integrated approach successfully identified AO-022/43514723 as a structurally novel preliminary hit with favorable computational binding profiles and preliminary cellular activity. While direct CHK1 target engagement remains to be confirmed and potency optimization is required, this compound serves as a promising starting point for lead development. The workflow provides a generalizable framework for oncology drug discovery where conventional approaches face clinical challenges.
Insights
Researchers developed a computational pipeline to discover novel checkpoint kinase 1 (CHK1) inhibitors for cancer therapy. The approach identified a promising lead compound, AO-022/43514723, with favorable binding and preliminary activity, offering a new framework for drug discovery.
Area of Science:
- Oncology
- Medicinal Chemistry
- Computational Biology
Background:
- Checkpoint kinase 1 (CHK1) is crucial for DNA damage response and cell cycle regulation, making it a key target in cancer therapy.
- Existing CHK1 inhibitors face challenges including selectivity, toxicity, and drug resistance, necessitating new therapeutic strategies.
Purpose of the Study:
- To develop and apply an integrated computational-experimental pipeline for the discovery of novel CHK1 inhibitors.
- To identify and validate a structurally novel CHK1 inhibitor with improved therapeutic potential.
Main Methods:
- Utilized a large compound database (Specs, 492,534 compounds) with PAINS filtering, ECFP4 fingerprinting, and UMAP/K-means clustering.
- Employed structure-based virtual screening including e-pharmacophore modeling, molecular docking (Glide), and molecular dynamics simulations (MM-GBSA).
- Validated lead candidates via ADME profiling, synthetic accessibility assessment, and in vitro cytotoxicity assays in triple-negative breast cancer cell lines.
Main Results:
- The pipeline identified 544 diverse compounds, with five showing favorable CHK1 binding.
- AO-022/43514723 emerged as the lead compound, exhibiting a docking score of -9.205 kcal/mol and stable interactions with CHK1 hinge residues.
- In vitro assays showed dose-dependent cytotoxicity with IC50 values of 51.53 μM (MDA-MB-231) and 64.02 μM (MDA-MB-468), indicating micromolar potency.
Conclusions:
- The integrated pipeline successfully identified AO-022/43514723, a novel preliminary CHK1 inhibitor hit with promising computational and cellular activity.
- This compound represents a potential starting point for further lead optimization in oncology drug discovery.
- The developed workflow offers a generalizable framework for discovering oncology drugs when traditional methods encounter clinical hurdles.
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