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A structure-based virtual screening approach to identify novel anaplastic lymphoma kinase inhibitors
Kajal Sandhu1, Sibasis Sahoo2, S Chockalingam3
1Cell Signaling Research Laboratory, Department of Biotechnology, National Institute of Technology, Warangal, Telangana State, India.
Context:
Anaplastic lymphoma kinase (ALK) is a receptor tyrosine kinase that plays a crucial role in cellular signaling and is implicated in several cancers, including anaplastic large cell lymphoma (ALCL), non-small cell lung cancer (NSCLC), and neuroblastoma. ALK's catalytic activity is driven by its intracellular kinase domain, which activates key signaling pathways, making it an important target for small-molecule inhibitors. Although FDA (Food and Drug Administration) approved inhibitors such as crizotinib, ceritinib, alectinib, brigatinib, and lorlatinib have improved clinical outcomes, their efficacy is often challenged by resistance mechanisms, including secondary kinase domain mutations and activation of bypass pathways. As a step towards overcoming the challenges associated with the existing inhibitors, we conducted virtual screening of the ZINC database to discover novel and alternative compounds with potential ALK inhibitory activity. The top hits obtained following a three-tiered virtual screening process namely high throughput virtual screening, standard precision, and extra precision, were further analyzed using molecular dynamics simulations to evaluate the stability of ALK-small molecule complexes under physiological conditions. Free energy calculations and binding affinity prediction were conducted to estimate the binding affinities along with per-residue energy decomposition of the most stable complexes. Principal component analysis further revealed dominant motions in apo and ligand-bound ALK, underscoring the role of key residues in conformational changes and complex stabilization. This integrative computational approach identified ZINC97743494, ZINC55325417, and ZINC83408527 as promising ALK inhibitors with potential to improve therapeutic strategies for ALK-positive cancers.
Method:
The ZINC12 library was processed using LigPrep to generate optimized 3D structures, followed by multi-tiered virtual screening against the ALK kinase domain (PDB: 2XP2), prepared using the Schrödinger Suite. MMGBSA (Molecular Mechanics/Generalized Born Surface Area) binding free energy calculations and ADME-based pharmacokinetic analyses were performed for the top hits. MD simulations were conducted using Desmond to evaluate complex stability. Binding free energies and per-residue contributions were computed using MMGBSA. Boltz-2 machine learning platform to predict KD values and the top three hits were validated using PCA and free energy landscape.
Insights
This study identifies novel anaplastic lymphoma kinase (ALK) inhibitors using virtual screening and molecular dynamics. Three compounds, ZINC97743494, ZINC55325417, and ZINC83408527, show promise for treating ALK-positive cancers.
Area of Science:
- Computational chemistry and drug discovery.
- Oncology and molecular biology.
Background:
- Anaplastic lymphoma kinase (ALK) is a key target in cancers like NSCLC and ALCL.
- Existing ALK inhibitors face resistance due to mutations and bypass pathways.
- Novel inhibitors are needed to overcome therapeutic challenges.
Purpose of the Study:
- To discover novel small-molecule inhibitors of ALK.
- To identify alternative compounds overcoming resistance mechanisms.
- To evaluate potential ALK inhibitors using computational methods.
Main Methods:
- Multi-tiered virtual screening of the ZINC database against the ALK kinase domain.
- Molecular dynamics simulations to assess complex stability and binding free energies (MMGBSA).
- Principal component analysis (PCA) and free energy landscape to validate top hits.
Main Results:
- Identified ZINC97743494, ZINC55325417, and ZINC83408527 as promising ALK inhibitors.
- Evaluated binding affinities and per-residue contributions for stable ALK-small molecule complexes.
- Confirmed dominant motions and key residue roles in ALK conformational changes.
Conclusions:
- The identified compounds represent potential novel therapeutic agents for ALK-positive cancers.
- This computational approach provides a foundation for developing improved ALK inhibitors.
- Further research may lead to overcoming resistance and enhancing cancer treatment strategies.
