Dataset Information

Search for the pharmacophore of histone deacetylase inhibitors using pharmacophore query and docking study.

ABSTRACT: Histone deacetylase inhibitors have gained a great deal of attention recently for the treatment of cancers and inflammatory diseases. So design of new inhibitors is of great importance in pharmaceutical industries and labs. Creating pharmacophor models in order to design new molecules or search a library for finding lead compounds is of great interest. This approach reduces the overall cost associated with the discovery and development of a new drug. Here we elaborated an exact pharmacophore model for histone deacetylase inhibitors by using pharmacophore query and docking study. The data set used for the modelling exercise comprised of 383 molecules collated from the original literature. These molecules were used to crating the model and docking study was held with Zolinza, the recently FDA approved drug as potent histone deacetylase inhibitor. Our model consists of 5 features: Hydrogen bond donors, Hydrogen bond acceptors, H-bond donor/acceptors, Aromatic ring centers, and hydrophobic centers. With the aid of this pharmacophore model and docking result, 3D searches in large databases can be performed, leading to a significant enrichment of active analogs.

SUBMITTER: Haji Agha Bozorgi A

PROVIDER: S-EPMC4232781 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Search for the pharmacophore of histone deacetylase inhibitors using pharmacophore query and docking study.

Haji Agha Bozorgi Atefeh A Zarghi Afshin A

Iranian journal of pharmaceutical research : IJPR 20140101 4

Histone deacetylase inhibitors have gained a great deal of attention recently for the treatment of cancers and inflammatory diseases. So design of new inhibitors is of great importance in pharmaceutical industries and labs. Creating pharmacophor models in order to design new molecules or search a library for finding lead compounds is of great interest. This approach reduces the overall cost associated with the discovery and development of a new drug. Here we elaborated an exact pharmacophore mod ...[more]

PMID: 25587304

Similar Datasets

Project description:BackgroundThe use of internet search data has been demonstrated to be effective at predicting influenza incidence. This approach may be more successful for dengue which has large variation in annual incidence and a more distinctive clinical presentation and mode of transmission.MethodsWe gathered freely-available dengue incidence data from Singapore (weekly incidence, 2004-2011) and Bangkok (monthly incidence, 2004-2011). Internet search data for the same period were downloaded from Google Insights for Search. Search terms were chosen to reflect three categories of dengue-related search: nomenclature, signs/symptoms, and treatment. We compared three models to predict incidence: a step-down linear regression, generalized boosted regression, and negative binomial regression. Logistic regression and Support Vector Machine (SVM) models were used to predict a binary outcome defined by whether dengue incidence exceeded a chosen threshold. Incidence prediction models were assessed using r² and Pearson correlation between predicted and observed dengue incidence. Logistic and SVM model performance were assessed by the area under the receiver operating characteristic curve. Models were validated using multiple cross-validation techniques.ResultsThe linear model selected by AIC step-down was found to be superior to other models considered. In Bangkok, the model has an r² = 0.943, and a correlation of 0.869 between fitted and observed. In Singapore, the model has an r² = 0.948, and a correlation of 0.931. In both Singapore and Bangkok, SVM models outperformed logistic regression in predicting periods of high incidence. The AUC for the SVM models using the 75th percentile cutoff is 0.906 in Singapore and 0.960 in Bangkok.ConclusionsInternet search terms predict incidence and periods of large incidence of dengue with high accuracy and may prove useful in areas with underdeveloped surveillance systems. The methods presented here use freely available data and analysis tools and can be readily adapted to other settings.

Project description:BackgroundDabbing is an emerging method of marijuana ingestion. However, little is known about dabbing owing to limited surveillance data on dabbing.ObjectiveThe aim of the study was to analyze Google search data to assess the scope and breadth of information seeking on dabbing.MethodsGoogle Trends data about dabbing and related topics (eg, electronic nicotine delivery system [ENDS], also known as e-cigarettes) in the United States between January 2004 and December 2015 were collected by using relevant search terms such as "dab rig." The correlation between dabbing (including topics: dab and hash oil) and ENDS (including topics: vaping and e-cigarette) searches, the regional distribution of dabbing searches, and the impact of cannabis legalization policies on geographical location in 2015 were analyzed.ResultsSearches regarding dabbing increased in the United States over time, with 1,526,280 estimated searches during 2015. Searches for dab and vaping have very similar temporal patterns, where the Pearson correlation coefficient (PCC) is .992 (P<.001). Similar phenomena were also obtained in searches for hash oil and e-cigarette, in which the corresponding PCC is .931 (P<.001). Dabbing information was searched more in some western states than other regions. The average dabbing searches were significantly higher in the states with medical and recreational marijuana legalization than in the states with only medical marijuana legalization (P=.02) or the states without medical and recreational marijuana legalization (P=.01).ConclusionsPublic interest in dabbing is increasing in the United States. There are close associations between dabbing and ENDS searches. The findings suggest greater popularity of dabs in the states that legalized medical and recreational marijuana use. This study proposes a novel and timely way of cannabis surveillance, and these findings can help enhance the understanding of the popularity of dabbing and provide insights for future research and informed policy making on dabbing.

Dataset Information

Search for the pharmacophore of histone deacetylase inhibitors using pharmacophore query and docking study.

Publications

Search for the pharmacophore of histone deacetylase inhibitors using pharmacophore query and docking study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets