ArticleCurrent pharmaceutical design2025
Targeting Anaplastic Lymphoma Kinase in Oncology: Identification and Computational Validation of Novel Inhibitors for Anaplastic Large Cell Lymphoma, Non-small Cell Lung Cancer, and Neuroblastoma.
Article in Current pharmaceutical design, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
backgroundAnaplastic Lymphoma Kinase (ALK) is implicated in several cancers, including anaplastic large cell lymphoma, non-small cell lung cancer, and neuroblastoma. Targeted inhibition of ALK represents a promising therapeutic strategy.
aimsThis study aimed to identify and evaluate potential ALK inhibitors using virtual screening and computational analyses to determine their binding stability, affinity, and dynamic behavior, ultimately assessing their potential as therapeutic agents for ALK-driven cancers.
objectiveThe objective of this study was to identify potential ALK inhibitors using virtual screening techniques and to evaluate their binding affinities and stability through computational analyses.
methodsThis study utilized virtual screening to identify potential ALK inhibitors from the MTiOpen Screen Diverse library and selected three compounds (24331480, 26536128, and 24353407) based on their binding affinities. These compounds underwent optimization using Density Functional Theory (DFT) and were redocked to confirm binding stability. Molecular dynamics simulations, hydrogen bond analysis, MM/PBSA calculations, and PCA-based free energy landscape analysis were also carried out.
resultsThe re-docking experiments confirmed the stable and strong binding affinities of the selected compounds to the ALK active site. Molecular dynamics simulations revealed stable interactions throughout the 200 ns simulation period. Hydrogen bond analysis demonstrated consistent hydrogen bonds between key residues and the inhibitors. MM/PBSA calculations indicated favorable binding free energies, suggesting strong binding affinities. Finally, PCA-based free energy landscape analysis highlighted energetically favorable binding modes.
conclusionThe identified compounds (24331480, 26536128, and 24353407) exhibited promising inhibitory potential against ALK. These findings warrant further experimental validation to confirm their potential as therapeutic agents for ALK-driven cancers.
Indexed as
Identifiers
40070330What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.