Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models

Building attention and edge message passing neural networks for bioactivity and physical–chemical property prediction

(2020) M. Withnall et al.   Journal of Cheminformatics

A self-attention based message passing neural network for predicting molecular lipophilicity and aqueous solubility

(2020) Bowen Tang et al.   Journal of Cheminformatics

ADMET evaluation in drug discovery. 20. Prediction of breast cancer resistance protein inhibition through machine learning

(2020) Dejun Jiang et al.   Journal of Cheminformatics

Learning Molecular Representations for Medicinal Chemistry

(2020) Kangway V. Chuang et al.   JOURNAL OF MEDICINAL CHEMISTRY

Predictive Multitask Deep Neural Network Models for ADME-Tox Properties: Learning from Large Datasets

(2019) Jan Wenzel et al.   Journal of Chemical Information and Modeling

Opportunities and challenges using artificial intelligence in ADME/Tox

(2019) Barun Bhhatarai et al.   NATURE MATERIALS

Analyzing Learned Molecular Representations for Property Prediction

(2019) Kevin Yang et al.   Journal of Chemical Information and Modeling

Structural Analysis and Identification of Colloidal Aggregators in Drug Discovery

(2019) Zi-Yi Yang et al.   Journal of Chemical Information and Modeling

Interpretation of Compound Activity Predictions from Complex Machine Learning Models Using Local Approximations and Shapley Values

(2019) Raquel Rodríguez-Pérez et al.   JOURNAL OF MEDICINAL CHEMISTRY

Artificial Intelligence for Drug Toxicity and Safety

(2019) Anna O. Basile et al.   TRENDS IN PHARMACOLOGICAL SCIENCES

LightGBM: An Effective and Scalable Algorithm for Prediction of Chemical Toxicity–Application to the Tox21 and Mutagenicity Data Sets

(2019) Jin Zhang et al.   Journal of Chemical Information and Modeling

ADMET Evaluation in Drug Discovery. 19. Reliable Prediction of Human Cytochrome P450 Inhibition Using Artificial Intelligence Approaches

(2019) Zhenxing Wu et al.   Journal of Chemical Information and Modeling

Graph Convolutional Neural Networks as “General-Purpose” Property Predictors: The Universality and Limits of Applicability

(2019) Vadim Korolev et al.   Journal of Chemical Information and Modeling

The rise of deep learning in drug discovery

(2018) Hongming Chen et al.   DRUG DISCOVERY TODAY

Prediction of Human Cytochrome P450 Inhibition Using a Multitask Deep Autoencoder Neural Network

(2018) Xiang Li et al.   MOLECULAR PHARMACEUTICS

Geometric Deep Learning Autonomously Learns Chemical Features That Outperform Those Engineered by Domain Experts

(2018) Patrick Hop et al.   MOLECULAR PHARMACEUTICS

Large-scale comparison of machine learning methods for drug target prediction on ChEMBL

(2018) Andreas Mayr et al.   Chemical Science

MoleculeNet: a benchmark for molecular machine learning

(2018) Zhenqin Wu et al.   Chemical Science

A Comparative Study of Multitask Toxicity Modeling on a Broad Chemical Space

(2018) Sergey Sosnin et al.   Journal of Chemical Information and Modeling

The impact of interior dielectric constant and entropic change on HIV-1 complex binding free energy prediction

(2018) Yuchen Li et al.   Structural Dynamics

Interpretation of Quantitative Structure–Activity Relationship Models: Past, Present, and Future

(2017) Pavel Polishchuk   Journal of Chemical Information and Modeling

ADMET Evaluation in Drug Discovery. 18. Reliable Prediction of Chemical-Induced Urinary Tract Toxicity by Boosting Machine Learning Approaches

(2017) Tailong Lei et al.   MOLECULAR PHARMACEUTICS

DeepTox: Toxicity prediction using deep learning

(2017) Günter Klambauer et al.   TOXICOLOGY LETTERS

Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to shallow methods for modeling bioactivity data

(2017) Alexios Koutsoukas et al.   Journal of Cheminformatics

Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set

(2017) Eelke B. Lenselink et al.   Journal of Cheminformatics

Extreme Gradient Boosting as a Method for Quantitative Structure–Activity Relationships

(2016) Robert P. Sheridan et al.   Journal of Chemical Information and Modeling

Understanding the Roles of the “Two QSARs”

(2016) Toshio Fujita et al.   Journal of Chemical Information and Modeling

Molecular graph convolutions: moving beyond fingerprints

(2016) Steven Kearnes et al.   JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN

Predicting the aquatic toxicity mode of action using logistic regression and linear discriminant analysis

(2016) Y. Y. Ren et al.   SAR AND QSAR IN ENVIRONMENTAL RESEARCH

Large-scale ligand-based predictive modelling using support vector machines

(2016) Jonathan Alvarsson et al.   Journal of Cheminformatics

Deep Learning for Drug-Induced Liver Injury

(2015) Youjun Xu et al.   Journal of Chemical Information and Modeling

Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships

(2015) Junshui Ma et al.   Journal of Chemical Information and Modeling

Deep Learning in Drug Discovery

(2015) Erik Gawehn et al.   Molecular Informatics

ADMET Evaluation in Drug Discovery. 13. Development of in Silico Prediction Models for P-Glycoprotein Substrates

(2014) Dan Li et al.   MOLECULAR PHARMACEUTICS

In silico Prediction of Chemical Ames Mutagenicity

(2012) Congying Xu et al.   Journal of Chemical Information and Modeling

Drug-likeness Analysis of Traditional Chinese Medicines: Prediction of Drug-likeness Using Machine Learning Approaches

(2012) Sheng Tian et al.   MOLECULAR PHARMACEUTICS

Trade-off between accuracy and interpretability for predictivein silicomodeling

(2011) Ulf Johansson et al.   Future Medicinal Chemistry

ADME Evaluation in Drug Discovery. 10. Predictions of P-Glycoprotein Inhibitors Using Recursive Partitioning and Naive Bayesian Classification Techniques

(2011) Lei Chen et al.   MOLECULAR PHARMACEUTICS

PaDEL-descriptor: An open source software to calculate molecular descriptors and fingerprints

(2010) Chun Wei Yap   JOURNAL OF COMPUTATIONAL CHEMISTRY

Recent Developments of In Silico Predictions of Intestinal Absorption and Oral Bioavailability

(2009) Tingjun Hou et al.   COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING