PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results

Dixon, Steven L.; Smondyrev, Alexander M.; Knoll, Eric H.; Rao, Shashidhar N.; Shaw, David E.; Friesner, Richard A.

doi:10.1007/s10822-006-9087-6

Cited by 1,059 publications

(837 citation statements)

References 22 publications

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“…The other part (an additional 10 000 compounds) was based on reference compounds collected from the literature ( [19], http://www.wipo.int/pctdb/en/wo.jsp?wo=2005047899), and used as input to computational techniques allowing us to detect compounds with similar properties. In order to do this a pharmacophore was built in Phase [20] and it consisted of a central acceptor/donor pair flanked on one side of an acceptor and a hydrophobic group and on the other side by one aromatic group and one hydrophobic group (see supplementary Fig 1). A Tuplet hypothesis was then constructed using triplets [21], and used in parallel with the Phase pharmacophore to find matching compounds.…”

Section: Methodsmentioning

confidence: 99%

Stable formyl peptide receptor agonists that activate the neutrophil NADPH-oxidase identified through screening of a compound library

Forsman

Kalderén

Nordin

et al. 2011

Biochemical Pharmacology

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The neutrophil formyl peptide receptors (FPR1 and FPR2) are G-protein coupled receptors that can induce pro-inflammatory as well as anti-inflammatory activities when activated. Accordingly, these receptors may become therapeutic targets for the development of novel drugs to be used for reducing the inflammation induced injuries in asthma, rheumatoid arthritis, Alzheimer's disease, cardiovascular diseases and traumatic shock. We screened a library of more then 50 K small compounds for an ability of the compounds to induce a transient rise in intracellular Ca 2+ in cells transfected to express FPR2 (earlier called FPRL1 or the lipoxin A 4 receptor). Ten agonists hits were selected for further analysis representing different chemical series and five new together with five earlier described molecules were further profiled.. Compounds 1 -10 gave rise to a calcium response in the FPR2 transfectants with EC 50 values ranging from 4 x 10 -9 M to 2 x 10 -7 M. All 10 compounds activated human neutrophils to release superoxide , and based on the potency of their activity, the three most potent activators of the neutrophil NADPH-oxidase were further characterized. These three agonists were largely resistant to inactivation by neutrophil produced reactive oxygen species and shown to trigger the same functional repertoire in neutrophils as earlier described peptide agonists. Accordingly they induced chemotaxis, granule mobilization and secretion of superoxide. Interestingly, the oxidase activity was largely inhibited by cyclosporine H, an FPR1 selective antagonist, but not by PBP10, an FPR2 selective inhibitor, suggesting that FPR1 is the preferred receptor in neutrophils for all three agonists.

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Section: Methodsmentioning

confidence: 99%

Stable formyl peptide receptor agonists that activate the neutrophil NADPH-oxidase identified through screening of a compound library

Forsman

Kalderén

Nordin

et al. 2011

Biochemical Pharmacology

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“…3D-QSAR models were built using PHASE [34,35] . Reliable Each new code consists of two parts separated by an underscore.…”

Section: D-qsar Model Buildingmentioning

confidence: 99%

Structure-based ensemble-QSAR model: a novel approach to the study of the EGFR tyrosine kinase and its inhibitors

Sun

Chen

et al. 2013

Acta Pharmacol Sin

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Aim: To develop a novel 3D-QSAR approach for study of the epidermal growth factor receptor tyrosine kinase (EGFR TK) and its inhibitors. Methods: One hundred thirty nine EGFR TK inhibitors were classified into 3 clusters. Ensemble docking of these inhibitors with 19 EGFR TK crystal structures was performed. Three protein structures that showed the best recognition of each cluster were selected based on the docking results. Then, a novel QSAR (ensemble-QSAR) building method was developed based on the ligand conformations determined by the corresponding protein structures. Results: Compared with the 3D-QSAR model, in which the ligand conformations were determined by a single protein structure, ensemble-QSAR exhibited higher R2 (0.87) and Q2 (0.78) values and thus appeared to be a more reliable and better predictive model. Ensemble-QSAR was also able to more accurately describe the interactions between the target and the ligands. Conclusion: The novel ensemble-QSAR model built in this study outperforms the traditional 3D-QSAR model in rationality, and provides a good example of selecting suitable protein structures for docking prediction and for building structure-based QSAR using available protein structures.

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“…The 3D-QSAR study was performed using the Phase software package [22]. Phase utilizes fine-grained conformational sampling and a range of scoring techniques to identify common pharmacophore hypotheses.…”

Section: D-qsar Pharmacophore Modelingmentioning

confidence: 99%

“…The choice of model depends largely on whether or not the training-set molecules are sufficiently rigid and congeneric. If the structures contain a small number of rotatable bonds and have some of their structural framework in common, then an atom-based model may work quite well [22]. The selected dataset did not have many rotatable bonds, so the atom-based QSAR model was used.…”

Section: D-qsar Pharmacophore Modelingmentioning

confidence: 99%

Receptor-guided 3D-QSAR approach for the discovery of c-kit tyrosine kinase inhibitors

2011

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Studies of the the three-dimensional quantitative structure-activity relationships for ninety-five c-kit tyrosine kinase inhibitors were performed. Based on a cocrystallized compound (1 T46), known inhibitors were aligned with c-kit by induced-fit docking, and multiple training/test set splitting was performed to validate the selected pharmacophore model. The best pharmacophore model consisted of five features: one hydrogen-bond donor and four aromatic rings. Reliable statistics were obtained (R 2 =0.95, R pred 2 =0.75), and the model was validated by using it to select c-kit inhibitors from a database; 82.1% of the hits it retrieved were active. Accordingly, our model can be reliably used to identify new c-kit inhibitors, and can provide useful information when designing new inhibitors.

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PHASE: a new engine for pharmacophore perception, 3D QSAR model development, and 3D database screening: 1. Methodology and preliminary results

Cited by 1,059 publications

References 22 publications

Stable formyl peptide receptor agonists that activate the neutrophil NADPH-oxidase identified through screening of a compound library

Stable formyl peptide receptor agonists that activate the neutrophil NADPH-oxidase identified through screening of a compound library

Structure-based ensemble-QSAR model: a novel approach to the study of the EGFR tyrosine kinase and its inhibitors

Receptor-guided 3D-QSAR approach for the discovery of c-kit tyrosine kinase inhibitors

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