ArticleMolecules (Basel, Switzerland)2020
Computer-Driven Development of an in Silico Tool for Finding Selective Histone Deacetylase 1 Inhibitors.
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 9 papers.
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Who cites it
9 citing papers in PubMed, 28 citations in OpenAlex.
- Development of novel benzamide class I selective lysine deacetylase inhibitors as potent anticancer agents.Journal of enzyme inhibition and medicinal chemistry · 2025Article
- Novel Antischistosomal Drug Targets: Identification of Alkaloid Inhibitors of SmTGR via Integrated In Silico Methods.Pathogens (Basel, Switzerland) · 2025Article
- Discovery and biological evaluation of novel CARM1/HDAC2 dual-targeting inhibitors with anti-prostate cancer agents.Journal of enzyme inhibition and medicinal chemistry · 2023Article
- Discovery of newer pyrazole derivatives with potential anti-tubercular activity via 3D-QSAR based pharmacophore modelling, virtual screening, molecular docking and molecular dynamics simulation studies.Molecular diversity · 2023Article
- Identification of novel and potent dual-targeting HDAC1/SPOP inhibitors using structure-based virtual screening, molecular dynamics simulation and evaluation ofFrontiers in pharmacology · 2023Article
- Identification of novel leads as potent inhibitors of HDAC3 using ligand-based pharmacophore modeling and MD simulation.Scientific reports · 2022Article
- Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics.Molecules (Basel, Switzerland) · 2021Article
- Recent progress on cheminformatics approaches to epigenetic drug discovery.Drug discovery today · 2020Review
- Development of In Vitro Corneal Models: Opportunity for Pharmacological Testing.Methods and protocols · 2020Review
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Histone deacetylases (HDACs) are a class of epigenetic modulators overexpressed in numerous types of cancers. Consequently, HDAC inhibitors (HDACIs) have emerged as promising antineoplastic agents. Unfortunately, the most developed HDACIs suffer from poor selectivity towards a specific isoform, limiting their clinical applicability. Among the isoforms, HDAC1 represents a crucial target for designing selective HDACIs, being aberrantly expressed in several malignancies. Accordingly, the development of a predictive in silico tool employing a large set of HDACIs (aminophenylbenzamide derivatives) is herein presented for the first time. Software Phase was used to derive a 3D-QSAR model, employing as alignment rule a common-features pharmacophore built on 20 highly active/selective HDAC1 inhibitors. The 3D-QSAR model was generated using 370 benzamide-based HDACIs, which yielded an excellent correlation coefficient value (R
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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.