ArticleMolecular diversity2018
Computational design of new protein kinase D 1 (PKD1) inhibitors: homology-based active site prediction, energy-optimized pharmacophore, docking and database screening.
Article in Molecular diversity, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 4 citations in OpenAlex.
- Structure similarity based screening coupled to integrated structural biochemistry approach for exploring the high affinity inhibitors against histone deacetylase (HDAC)-6.In silico pharmacology · 2025Article
- Small Molecule Inhibitors of Protein Kinase D: Early Development, Current Approaches, and Future Directions.Journal of medicinal chemistry · 2023Review
- Docking-Based Virtual Screening Enables Prioritizing Protein Kinase Inhibitors WithFrontiers in cellular and infection microbiology · 2022Article
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Authors and funding
6 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Protein kinase D 1 (PKD1) overexpression has a well-validated role in cancer progression and its inhibitors have defined a protective role-play of PKD1 for various cancers such as prostate, pancreatic and noninvasive breast cancers, and more. Therefore, the current research was aimed at designing new PKD1 inhibitors combining different ligand- and structure-based computational drug designing methodologies. Initially, the three-dimensional structure of PKD1's active site was computationally modeled, corrected using molecular dynamic simulations and validated for docking experiments. The highest active PKD1 inhibitor was used to develop a structure-based energetic pharmacophore (e-pharmacophore) model, and a final model was selected with five structural features (Pmodel_AADHR). Pmodel_AADHR was validated and used for database screening to obtain new hits against PKD1. These newly retrieved hits were docked against our PKD1 protein model, and those displaying essential interactions are reported herein as new hits, which could serve as new leads for cancer research, especially pancreatic cancer.
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