ArticleMolecules (Basel, Switzerland)2020
Structure-Based Discovery and Bioactivity Evaluation of Novel Aurora-A Kinase Inhibitors as Anticancer Agents via Docking-Based Comparative Intermolecular Contacts Analysis (dbCICA).
Article in Molecules (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 16 citations in OpenAlex.
- Computational identification of potential VEGFR2 inhibitors using integrated pharmacophore modeling, QSAR analysis, molecular docking, dynamics simulation, and virtual screening followed by in vitro bioassays.Journal of computer-aided molecular design · 2026Article
- Hybrid amine-derived compounds as cytotoxic anticancer leads: design, synthesis, and biological evaluation.RSC advances · 2026Article
- Computer-aided discovery of CDK16 inhibitors: a docking-augmented machine learning regression modelling approach.Journal of computer-aided molecular design · 2026Article
- Research progress on the relationship between AURKA and tumorigenesis: the neglected nuclear function of AURKA.Annals of medicine · 2024Review
- Design, synthesis, and biochemical and computational screening of novel oxindole derivatives as inhibitors of Aurora A kinase and SARS-CoV-2 spike/host ACE2 interaction.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2024Article
- Pharmacophore Mapping Combined with dbCICA Reveal New Structural Features for the Development of Novel Ligands Targeting α4β2 and α7 Nicotinic Acetylcholine Receptors.Molecules (Basel, Switzerland) · 2022Article
- Exploiting activity cliffs for building pharmacophore models and comparison with other pharmacophore generation methods: sphingosine kinase 1 as case study.Journal of computer-aided molecular design · 2022Article
- Aurora Kinase B Inhibition: A Potential Therapeutic Strategy for Cancer.Molecules (Basel, Switzerland) · 2021Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aurora-A kinase plays a central role in mitosis, where aberrant activation contributes to cancer by promoting cell cycle progression, genomic instability, epithelial-mesenchymal transition, and cancer stemness. Aurora-A kinase inhibitors have shown encouraging results in clinical trials but have not gained Food and Drug Administration (FDA) approval. An innovative computational workflow named Docking-based Comparative Intermolecular Contacts Analysis (dbCICA) was applied-aiming to identify novel Aurora-A kinase inhibitors-using seventy-nine reported Aurora-A kinase inhibitors to specify the best possible docking settings needed to fit into the active-site binding pocket of Aurora-A kinase crystal structure, in a process that only potent ligands contact critical binding-site spots, distinct from those occupied by less-active ligands. Optimal dbCICA models were transformed into two corresponding pharmacophores. The optimal one, in capturing active hits and discarding inactive ones, validated by receiver operating characteristic analysis, was used as a virtual in-silico search query for screening new molecules from the National Cancer Institute database. A fluorescence resonance energy transfer (FRET)-based assay was used to assess the activity of captured molecules and five promising Aurora-A kinase inhibitors were identified. The activity was next validated using a cell culture anti-proliferative assay (MTT) and revealed a most potent lead
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