Discovery of novel CDK1 inhibitors by combining pharmacophore modeling, QSAR analysis and in silico screening followed by in vitro bioassay

Al-Sha’er, Mahmoud A.; Taha, Mutasem O.

doi:10.1016/j.ejmech.2010.06.034

Cited by 39 publications

(32 citation statements)

References 61 publications

(76 reference statements)

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“…6 suggests they represent two complementary binding modes accessible to ligands within the binding pocket of ROCK II, i.e., one of the pharmacophores explains the bioactivities of some training inhibitors while the other explains the remaining inhibitors. Similar conclusions were reached about the binding pockets of other targets based on QSAR analysis [21][22][23][24][25][26][27][28][29][30][31]. Figures 2c and 3c show Hypo6/35 and Hypo4/15 and how they map 107 (IC 50 = 0.009 lM) and 98 (IC 50 = 0.02 lM), respectively.…”

Section: Qsar Modelingsupporting

confidence: 66%

“…However, since pharmacophore models fail in explaining electronic and steric bioactivity-modulating effects, the GFA-QSAR process should be allowed to select other 2D physicochemical descriptors to complement the selected pharmacophore(s). We have applied this approach in several previous publications [21][22][23][24][25][26][27][28][29][30][31].…”

Section: Exploration Of Rockii Pharmacophoric Spacementioning

confidence: 99%

“…Despite that pharmacophoric hypotheses provide excellent insights into ligand-macromolecule recognition and can be used to mine for new biologically interesting scaffolds, their predictive value as 3D-QSAR models is limited by steric shielding and bioactivity-enhancing or reducing auxiliary groups [21][22][23][24][25][26][27][28][29][30][31]. This point combined with the fact that pharmacophore modeling of ROCKII inhibitors furnished several binding hypotheses of comparable success criteria prompted us to employ classical QSAR analysis to search for the best combination of pharmacophore(s) and other 2D descriptors capable of explaining bioactivity variation across the collected inhibitors (tables A1 and A2 under Supplementary Materials).…”

Section: Qsar Modelingmentioning

confidence: 99%

“…This approach avoids the pitfalls of structure-based techniques; furthermore, the pharmacophore model(s) can be used as 3D search queries to discover new ROCKII inhibitory scaffolds. We previously reported the use of this approach towards the discovery of new inhibitory leads against glycogen synthase kinase-3b, [21] bacterial MurF [22], protein tyrosine phosphatase [23], DPP IV, [24] hormone sensitive lipase [25], b-secretase [26], influenza neuraminidase [27], cholesteryl ester transfer protein [28], CDK1 [29], Hsp90 [30], estrogen receptor b, [31] b-D-Glucosidase, [32] b-D-Galactosidase [33] and glycogen phosphorylase [34].…”

Section: Introductionmentioning

confidence: 99%

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Elaborate ligand-based modeling reveal new submicromolar Rho kinase inhibitors

Shahin

Alqtaishat

Taha

2011

J Comput Aided Mol Des

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Rho Kinase (ROCKII) has been recently implicated in several cardiovascular diseases prompting several attempts to discover and optimize new ROCKII inhibitors. Towards this end we explored the pharmacophoric space of 138 ROCKII inhibitors to identify high quality pharmacophores. The pharmacophoric models were subsequently allowed to compete within quantitative structure-activity relationship (QSAR) context. Genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of accessing self-consistent QSAR of optimal predictive potential (r (77) = 0.84, F = 18.18, r (LOO) (2) = 0.639, r (PRESS) (2) against 19 external test inhibitors = 0.494). Two orthogonal pharmacophores emerged in the QSAR equation suggesting the existence of at least two binding modes accessible to ligands within ROCKII binding pocket. Receiver operating characteristic (ROC) curve analyses established the validity of QSAR-selected pharmacophores. Moreover, the successful pharmacophores models were found to be comparable with crystallographically resolved ROCKII binding pocket. We employed the pharmacophoric models and associated QSAR equation to screen the national cancer institute (NCI) list of compounds Eight submicromolar ROCKII inhibitors were identified. The most potent gave IC(50) values of 0.7 and 1.0 μM.

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Section: Qsar Modelingsupporting

confidence: 66%

Section: Exploration Of Rockii Pharmacophoric Spacementioning

confidence: 99%

Section: Qsar Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Elaborate ligand-based modeling reveal new submicromolar Rho kinase inhibitors

Shahin

Alqtaishat

Taha

2011

J Comput Aided Mol Des

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“…The clustering identified three compound clusters: the naphthoquinone cluster, the 8-hydroxyquinoline cluster, and the 2-pyrimidinyl-aminopiperidine-propane-2-ol cluster, which we named after the most active representative of the individual cluster. Naphthoquinones, 8-hydroxyquinolines as well as 2-pyrimidinyl-aminopiperidine-propane-2-ols (Table 3) have already been described in the literature as inhibitors of different kinases (Aziz et al , 2008, Al-Sha’er & Taha, 2010; Kim et al , 2011). …”

Section: Resultsmentioning

confidence: 99%

High-throughput screening with the Eimeria tenella CDC2-related kinase2/cyclin complex EtCRK2/EtCYC3a

Fernández

Engels²,

Bender³

et al. 2012

Microbiology

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The poultry disease coccidiosis, caused by infection with Eimeria spp. apicomplexan parasites, is responsible for enormous economic losses to the global poultry industry. The rapid increase of resistance to therapeutic agents, as well as the expense of vaccination with live attenuated vaccines, requires the development of new effective treatments for coccidiosis. Because of their key regulatory function in the eukaryotic cell cycle, cyclin-dependent kinases (CDKs) are prominent drug targets. The Eimeria tenella CDC2-related kinase 2 (EtCRK2) is a validated drug target that can be activated in vitro by the CDK activator XlRINGO (Xenopus laevis rapid inducer of G2/M progression in oocytes). Bioinformatics analyses revealed four putative E. tenella cyclins (EtCYCs) that are closely related to cyclins found in the human apicomplexan parasite Plasmodium falciparum. EtCYC3a was cloned, expressed in Escherichia coli and purified in a complex with EtCRK2. Using the non-radioactive time-resolved fluorescence energy transfer (TR-FRET) assay, we demonstrated the ability of EtCYC3a to activate EtCRK2 as shown previously for XlRINGO. The EtCRK2/EtCYC3a complex was used for a combined in vitro and in silico high-throughput screening approach, which resulted in three lead structures, a naphthoquinone, an 8-hydroxyquinoline and a 2-pyrimidinyl-aminopiperidine-propane-2-ol. This constitutes a promising starting point for the subsequent lead optimization phase and the development of novel anticoccidial drugs.

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Discovery of novel potent nuclear factor kappa‐B inhibitors (IKK‐β) via extensive ligand‐based modeling and virtual screening

Al-Sha’er

Almazari

Taha

2016

J of Molecular Recognition

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Inhibitor kappa-B kinase-beta (IKK-β) controls the activation of nuclear transcription factor kappa-B and has been linked to inflammation and cancer. Therefore, inhibitors of this kinase should have potent anti-inflammatory and anticancer properties. Accordingly, we explored the pharmacophoric space of 218 IKK-β inhibitors to identify high-quality binding models. Subsequently, genetic algorithm-based quantitative structure activity relationship (QSAR) analysis was employed to select the best possible combination of pharmacophoric models and physicochemical descriptors that explain bioactivity variation among training compounds. Three successful pharmacophores emerged in 2 optimal QSAR equations (r = 0.733, r = 0.52, F1 = 65.62, r against 43 test inhibitors = 0.63 and r = 0.683, r = 0.52, F2 = 72.66, r against 43 test inhibitors = 0.65). Two pharmacophores were merged in a single binding model. Receiver operating characteristic curve validation proved the excellent qualities of this model. The merged pharmacophore and the associated QSAR equations were applied to screen the National Cancer Institute list of compounds. Ten hits were found to exhibit potent anti-IKK-β bioactivity, out of which, one illustrates IC50 of 11.0nM.

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Discovery of novel CDK1 inhibitors by combining pharmacophore modeling, QSAR analysis and in silico screening followed by in vitro bioassay

Cited by 39 publications

References 61 publications

Elaborate ligand-based modeling reveal new submicromolar Rho kinase inhibitors

Elaborate ligand-based modeling reveal new submicromolar Rho kinase inhibitors

High-throughput screening with the Eimeria tenella CDC2-related kinase2/cyclin complex EtCRK2/EtCYC3a

Discovery of novel potent nuclear factor kappa‐B inhibitors (IKK‐β) via extensive ligand‐based modeling and virtual screening

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