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Identification of PI3K alpha inhibitors through large-scale virtual screening and integrated molecular modeling,
Yahya Khan1, Attiqa Naz2, Asad Ullah3
1Department of Pharmacy, Abasyn University, Peshawar, 25000, KP, Pakistan.
Abstract:
Lung cancer remains one of the leading causes of cancer-associated mortality globally, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of all cases. The PI3K p110α catalytic subunit (PIK3CA) signaling pathway is often dysregulated in non-small cell lung cancer (NSCLC) and plays a vital role in promoting tumor cell proliferation, survival, and resistance to apoptosis, making it a clinically validated therapeutic target. Despite the approval of several PI3K p110α inhibitors, challenges including off-target toxicity, drug resistance, and suboptimal pharmacokinetic profiles require the continued discovery of novel, drug-like candidates. In this study, virtual screening of 650,000 compounds targeting the PI3K p110α pathway identified five lead candidates based on the lowest docking binding energy. MD simulations over 100 ns, MM-GBSA/MM-PBSA binding free energy calculations were performed using 1000 frames extracted at 100 ps intervals from the 100 ns molecular dynamics simulation trajectory. The results showed negative binding free energy values for all complexes, computationally indicating favorable binding interactions and potential stability of the compounds with the target protein. DFT analysis and SwissADME ADMET profiling were performed. All five complexes showed stable RMSD profiles and consistently negative binding free energies. DFT confirmed acceptable HOMO-LUMO energy gaps. ADMET profiling demonstrated satisfactory drug-likeness for all candidates. Five promising PI3K p110α inhibitor candidates with potential anti-lung cancer activity were identified; experimental validation is required to confirm these computational results.
Insights
Researchers identified five novel drug candidates targeting the PI3K p110α pathway for non-small cell lung cancer (NSCLC). These compounds show promise for inhibiting tumor growth and overcoming drug resistance, pending experimental validation.
Area of Science:
- Oncology
- Computational Chemistry
- Drug Discovery
Background:
- Non-small cell lung cancer (NSCLC) is a leading cause of cancer mortality worldwide.
- The PI3K p110α (PIK3CA) pathway is frequently dysregulated in NSCLC, driving tumor proliferation and survival.
- Existing PI3K p110α inhibitors face challenges like toxicity and resistance, necessitating new therapeutic strategies.
Purpose of the Study:
- To identify novel drug-like candidates targeting the PI3K p110α pathway for potential NSCLC treatment.
- To computationally evaluate the binding affinity and drug-likeness of identified compounds.
Main Methods:
- Virtual screening of 650,000 compounds against the PI3K p110α target.
- Molecular dynamics (MD) simulations, MM-GBSA/MM-PBSA binding free energy calculations.
- Density Functional Theory (DFT) analysis and SwissADME ADMET profiling.
Main Results:
- Five lead compounds with favorable docking binding energies were identified.
- MD simulations and binding energy calculations indicated stable and favorable interactions.
- DFT and ADMET profiling confirmed acceptable drug-likeness and electronic properties for all candidates.
Conclusions:
- Five promising PI3K p110α inhibitor candidates with potential anti-lung cancer activity were computationally identified.
- These candidates represent potential novel therapeutics for NSCLC.
- Experimental validation is crucial to confirm the efficacy and safety of these compounds.
