3D-QSAR of histone deacetylase inhibitors: hydroxamate analogues

Abstract

The histone deacetylase enzyme has increasingly become an attractive target for developing novel anticancer drugs. Hydroxamates are a new class of anticancer agents reported to act by selective inhibition of the histone deacetylase (HDAC) enzyme. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were employed to study three-dimensional quantitative structure-activity relationships (3D-QSARs). QSAR models were derived from a training set of 40 molecules. An external test set consisting of 17 molecules was used to validate the CoMFA and CoMSIA models. All molecules were superimposed on the template structure by atom-based, multifit and the SYBYL QSAR rigid body field fit alignments. The statistical quality of the QSAR models was assessed using the parameters r(2)(conv), r(2)(cv) and r(2)(pred). In addition to steric and electronic fields, ClogP was also taken as descriptor to account for lipophilicity. The resulting models exhibited a good conventional r(2)(conv) and cross-validated r(2)(cv) values up to 0.910 and 0.502 for CoMFA and 0.987 and 0.534 for CoMSIA. Robust cross-validation by 2 groups was performed 25 times to eliminate chance correlation. The CoMFA models exhibited good external predictivity as compared to that of CoMSIA models. These 3D-QSAR models are very useful for design of novel HDAC inhibitors.

N-(6-(hydroxyamino)-6-oxohexyl) decanamide collector: Flotation performance and adsorption mechanism to diaspore

“…The CONH and CONHOH groups of NHOD have different metal chelating properties and possess hydrogen bond sites [48]; their acid-base dissociation equilibriums were listed in Scheme 2. The species distribution of NHOD depends on the dissociation constants and aqueous pH values.…”

Identifying Novel Type ZBGs and Nonhydroxamate HDAC Inhibitors Through a SVM Based Virtual Screening Approach

“…All HDACi are distributed in 702 compound families (method for deriving compound families described in our earlier publication [40,41] and their structural diversity index is 0.506, which is comparable to that of the structurally diverse estrogen receptor agonist dataset. [46] Therefore, our collected HDACi are fairly diverse in structures and physicochemical properties, and they are significantly higher in numbers than the 40-200 compounds used in developing ligand-based HDACi prediction tools reported in the literatures (QSAR, [9][10][11][12][13] 3D-QSAR, [14][15][16][17][18][19] and pharmacophore [20] ). Among the 1488 HDACi and 84 weak HDACi, there are 1268 HDACi, 70 weak HDACi published before 2008, and 220 HDACi, 14 weak HDACi published since 2008.…”

“…[1,2] Efforts have been directed at expanded search of the chemical space, rational modification of linker and cap groups, and the introduction of pro-drugs. [1,2] Some of these efforts have been facilitated by the use of such virtual screening (VS) tools as ligand-based QSAR, [9][10][11][12][13] 3D-QSAR, [14][15][16][17][18][19] and pharmacophore, [20] and structure-based molecular docking. [21][22][23][24][25][26] The applicability domains of these ligand-based methods in some cases are restricted [27,28] by limited diversity (< 200 compounds in most cases) [29][30][31] or structural types (e.g.…”

A novel surfactant N-(6-(hydroxyamino)-6-oxohexyl)octanamide: Synthesis and flotation mechanisms to wolframite

“…Amide ligands contain AC(@O)NHA groups which can provide potential metal coordination sites and hydrogen bond sites [18][19][20][21]. The affinity of amide moieties for binding of metal ions strongly depends on deprotonation ability of amidic nitrogen, which is the coordination center for chelating metal ions.…”