Design and campaign synthesis of pyridine-based histone deacetylase inhibitors

Andrews, David M.; Gibson, Keith M.; Graham, M. A.; Matusiak, Zbigniew S.; Roberts, Craig; Stokes, Elaine S.E.; Brady, Madeleine C.; Chresta, Christine

doi:10.1016/j.bmcl.2008.03.058

Cited by 11 publications

(10 citation statements)

References 12 publications

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“…formalized by defining a core and simply plotting the substituent at a given position against the property of interest. 32 The analysis is then completed with the connection of points in which the remainder of the molecule is the same. The magnitude and consistency of property differences between one substituent and another are revealed.…”

Section: Perspectivementioning

confidence: 99%

Matched Molecular Pairs as a Medicinal Chemistry Tool

et al. 2011

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Section: Perspectivementioning

confidence: 99%

Matched Molecular Pairs as a Medicinal Chemistry Tool

et al. 2011

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“…34) as a lead benzamide and its corresponding des‐cyano analog were identified as potent low MW, but moderately soluble leads, capable of being elaborated into drug‐like compounds 195. For Andrews et al194 N ‐(2‐aminophenyl)‐4‐(3‐cyanopyridin‐2‐yl)benzamide became their focus of their optimization efforts. Their synthetic strategy led to a series of compounds which were tested for HDAC inhibition and anti‐proliferative activity in HCT‐116 cells.…”

Section: Results and Discussion Of The New Derived Qsarsmentioning

confidence: 99%

“…The laboratory tests utilized in identifying HDACIs are: HDAC from human leukemia K562 cells, purified recombinant human histone deacetylase (HDAC‐1), human colon cancer HCT 116 cells, human T‐24 cancer cells, HT1080 proliferation, partially purified human HDAC‐1, maize histone deacetylase (maize‐HD‐2), HDAC fluorescence activity/assay/drug discovery kit (AK‐500, Biomol Research Laboratories, Plymouth Meeting, PA) Friend leukemic cells, predominantly HDAC 1 and HDAC 2, human HT1080 fibrosarcoma cell line, mixture of HDAC‐1 and HDAC‐2 prepared from nuclear extraction of K562 erythroleukemia cells, HCT116 human colon, HD1‐A (homolog of mammalian class IIa HDACs), HD1‐B (homolog of mammalian class I HDAC), human lung cancer (A549) and breast cancer (SK‐BR‐3), H4‐Ac, HT1080 fibrosarcoma cells, purified HDAC 1, HDAC class II (HD1‐A), maize HDAC class I (HD1‐B), HeLa cell nuclear extract, H661 cell lines and HDAC 6. All the activity data have been collected from the literature 55, 102, 124–128, 130–132, 134–138, 146–149, 151, 156, 159, 160, 168, 169, 173, 174, 180, 181, 188–194, 196–199. The activity is expressed in molar concentration.…”

Section: Evaluation Of New Qsar Models—materials and Methodsmentioning

confidence: 99%

Histone deacetylase inhibitors (HDACIs). Structure—activity relationships: history and new QSAR perspectives

Pontiki

Hadjipavlou‐Litina

2011

Medicinal Research Reviews

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Histone deacetylase (HDAC) inhibition is a recent, clinically validated therapeutic strategy for cancer treatment. HDAC inhibitors (HDACIs) block angiogenesis, arrest cell growth, and lead to differentiation and apoptosis in tumor cells. In this article, a survey of published quantitative structure-activity relationships (QSARs) studies are presented and discussed in the hope of identifying the structural determinants for anticancer activity. Secondly a two-dimensional QSAR study was carried out on biological results derived from various types of HDACIs and from different assays using the C-QSAR program of Biobyte. The QSAR analysis presented here is an attempt to organize the knowledge on the HDACIs with the purpose of designing new chemical entities with enhanced inhibitory potencies and to study the mechanism of action of the compounds. This study revealed that lipophilicity is one of the most important determinants of activity. Additionally, steric factors such as the overall molar refractivity (CMR), molar volume (MgVol), the substituent's molar refractivity (MR) (linear or parabola), or the sterimol parameters B(1) and L are important. Electronic parameters indicated as σ(p), are found to be present only in one case.

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“…A comprehensive set of HDAC1 inhibitors characterized by the 2-aminophenylbenzamide scaffold with known IC 50 values that vary over a wide range was collected from the literature [66,67,[79][80][81][82][83][84][85][86][87][88][89][90][91][92] and the bindingDB database [93]. The selection criterion for the compounds to be included in the set was that their HDAC1 inhibition was evaluated using the same fluorescent assay based on the fluorogenic substrate Fluor-de-Lys.…”

Section: Ligands and Data Set Preparationmentioning

confidence: 99%

Computer-Driven Development of an in Silico Tool for Finding Selective Histone Deacetylase 1 Inhibitors

et al. 2020

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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 2 = 0.958) and a satisfactory predictive power (Q 2 = 0.822; Q 2 F3 = 0.894). The model was validated (r 2 ext_ts = 0.794) using an external test set (113 compounds not used for generating the model), and by employing a decoys set and the receiver-operating characteristic (ROC) curve analysis, evaluating the Güner-Henry score (GH) and the enrichment factor (EF). The results confirmed a satisfactory predictive power of the 3D-QSAR model. This latter represents a useful filtering tool for screening large chemical databases, finding novel derivatives with improved HDAC1 inhibitory activity.Molecules 2020, 25, 1952 2 of 20 chromatin structure which concomitantly restricts the accessibility of related transcriptional factors to their target genes, thereby suppressing gene expression including tumor suppressor genes [6][7][8]. The abnormal regulation of this process culminates with the high expression level of HDACs. This event has been observed in the development of several human cancers. Consequently, effective inhibition of HDACs has recently gained importance as a valid therapeutic strategy to reverse aberrant epigenetic changes associated with cancer [9][10][11]. HDAC inhibitors (HDACIs) induce histone hyperacetylation and subsequent transcriptional re-activation of suppressed genes which are correlated with a variety of effects on tumor cells including apoptosis, differentiation, cell cycle arrest, inhibition of proliferation and cytostasis [12,13].The HDAC family comprises 18 isoforms in mammalian cells which are categorized into four main classes (class I-IV) based on their structural and functional characteristics. HDACs belonging to class I (HDAC1-3 and 8), II (HDACs 4-7, 9 and 10) and IV (HDAC11) are all zinc-dependent metalloenzymes, while class III HDACs, also known as the sirtuins (SIRT1-7), requires NAD + as a cofactor for their catalytic function [6,14].Extensive efforts over recent decades have led to the identification of four chemically diverse classes of HDACIs as potent antineoplastic agents including, hydroxamates, benzamides, cyclic peptides, and short-chain fatty acids [3]. The main...

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Design and campaign synthesis of pyridine-based histone deacetylase inhibitors

Cited by 11 publications

References 12 publications

Matched Molecular Pairs as a Medicinal Chemistry Tool

Matched Molecular Pairs as a Medicinal Chemistry Tool

Histone deacetylase inhibitors (HDACIs). Structure—activity relationships: history and new QSAR perspectives

Computer-Driven Development of an in Silico Tool for Finding Selective Histone Deacetylase 1 Inhibitors

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