Journal ArticleDOI
Conformal prediction of HDAC inhibitors.
Ulf Norinder,Ulf Norinder,J. Jesús Naveja,J. Jesús Naveja,Edgar López-López,Daniel Mucs,José L. Medina-Franco +6 more
TLDR
This work introduces a novel approach for epigenetic quantitative structure–activity relationship (QSAR) modelling using conformal prediction and discusses the development of models for 11 sets of inhibitors of histone deacetylases, which are one of the major epigenetic target families that have been screened.Abstract:
The growing interest in epigenetic probes and drug discovery, as revealed by several epigenetic drugs in clinical use or in the lineup of the drug development pipeline, is boosting the generation of screening data. In order to maximize the use of structure-activity relationships there is a clear need to develop robust and accurate models to understand the underlying structure-activity relationship. Similarly, accurate models should be able to guide the rational screening of compound libraries. Herein we introduce a novel approach for epigenetic quantitative structure-activity relationship (QSAR) modelling using conformal prediction. As a case study, we discuss the development of models for 11 sets of inhibitors of histone deacetylases (HDACs), which are one of the major epigenetic target families that have been screened. It was found that all derived models, for every HDAC endpoint and all three significance levels, are valid with respect to predictions for the external test sets as well as the internal validation of the corresponding training sets. Furthermore, the efficiencies for the predictions are above 80% for most data sets and above 90% for four data sets at different significant levels. The findings of this work encourage prospective applications of conformal prediction for other epigenetic target data sets.read more
Citations
More filters
Journal ArticleDOI
Recent progress on cheminformatics approaches to epigenetic drug discovery.
Zoe L Sessions,Norberto Sánchez-Cruz,Fernando D. Prieto-Martínez,Vinicius M. Alves,Hudson P. Santos,Eugene N. Muratov,Alexander Tropsha,José L. Medina-Franco +7 more
TL;DR: The advances in computational approaches to drug discovery of small molecules with epigenetic modulation profiles are reviewed, the current chemogenomics data available for epigenetics targets are summarized, and a perspective on the greater utility of biomedical knowledge mining as a means to advance the epigenetic drug discovery is provided.
Journal ArticleDOI
Epigenetic Target Fishing with Accurate Machine Learning Models.
TL;DR: In this article, a large-scale study of 26 318 compounds with a quantitative measure of biological activity for 55 protein targets with epigenetic activity was conducted. And the results indicated that the models reported herein have considerable potential to identify small molecules with epigenetics activity.
Journal ArticleDOI
Towards the understanding of the activity of G9a inhibitors: an activity landscape and molecular modeling approach
TL;DR: This work analyzes the structure–activity relationships (SAR) of epigenetic inhibitors (lysine mimetics) against lysine methyltransferase (G9a or EHMT2) using a combined activity landscape, molecular docking and molecular dynamics approach.
Book ChapterDOI
In silico tools to study molecular targets of neglected diseases: inhibition of TcSir2rp3, an epigenetic enzyme of Trypanosoma cruzi
Edgar López-López,Carolina Barrientos-Salcedo,Fernando D. Prieto-Martínez,José L. Medina-Franco +3 more
TL;DR: This chapter identifies amentoflavone as a potential inhibitor of TcSir2rp3 (sirtuine) from Trypanosoma cruzi with a workflow that integrates chemoinformatic approaches, molecular modeling, and theoretical affinity calculations, as well as in vitro assays.
Journal ArticleDOI
Applying comparative molecular modelling techniques on diverse hydroxamate-based HDAC2 inhibitors: an attempt to identify promising structural features for potent HDAC2 inhibition
TL;DR: The implementation of a combined comparative 2D and 3D molecular modelling techniques was done on a group of 92 diverse hydroxamate derivatives having a wide range of HDAC2 inhibitory potency, upholding the importance of groups like triazole and benzyl moieties along with the molecular fields that are crucial for regulatingHDAC2 inhibition.
References
More filters
Journal ArticleDOI
Random Forests
TL;DR: Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the forest, and are also applicable to regression.
Posted Content
Scikit-learn: Machine Learning in Python
Fabian Pedregosa,Gaël Varoquaux,Alexandre Gramfort,Vincent Michel,Bertrand Thirion,Olivier Grisel,Mathieu Blondel,Andreas Müller,Joel Nothman,Gilles Louppe,Peter Prettenhofer,Ron Weiss,Vincent Dubourg,Jake Vanderplas,Alexandre Passos,David Cournapeau,Matthieu Brucher,Matthieu Perrot,Edouard Duchesnay +18 more
TL;DR: Scikit-learn as mentioned in this paper is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems.
Journal ArticleDOI
DrugBank: a comprehensive resource for in silico drug discovery and exploration
David S. Wishart,Craig Knox,An Chi Guo,Savita Shrivastava,Murtaza Hassanali,Paul Stothard,Zhan Chang,Jennifer Woolsey +7 more
TL;DR: DrugBank is a unique bioinformatics/cheminformatics resource that combines detailed drug data with comprehensive drug target information and is fully searchable supporting extensive text, sequence, chemical structure and relational query searches.
Journal ArticleDOI
BindingDB in 2015: A public database for medicinal chemistry, computational chemistry and systems pharmacology.
TL;DR: The first update of BindingDB since 2007 is provided, focusing on new and unique features and highlighting directions of importance to the field as a whole.
Journal Article
A Tutorial on Conformal Prediction
Glenn Shafer,Vladimir Vovk +1 more
TL;DR: This tutorial presents a self-contained account of the theory of conformal prediction and works through several numerical examples of how the model under which successive examples are sampled independently from the same distribution can be applied to any method for producing ŷ.