Best practices for QSAR model development, validation, and exploitation

A Tropsha - Molecular informatics, 2010 - Wiley Online Library
After nearly five decades “in the making”, QSAR modeling has established itself as one of
the major computational molecular modeling methodologies. As any mature research …

The next era: deep learning in pharmaceutical research

S Ekins - Pharmaceutical research, 2016 - Springer
Over the past decade we have witnessed the increasing sophistication of machine learning
algorithms applied in daily use from internet searches, voice recognition, social network …

Comparison of deep learning with multiple machine learning methods and metrics using diverse drug discovery data sets

A Korotcov, V Tkachenko, DP Russo… - Molecular …, 2017 - ACS Publications
Machine learning methods have been applied to many data sets in pharmaceutical research
for several decades. The relative ease and availability of fingerprint type molecular …

Predictive QSAR modeling workflow, model applicability domains, and virtual screening

A Tropsha, A Golbraikh - Current pharmaceutical design, 2007 - ingentaconnect.com
Quantitative Structure Activity Relationship (QSAR) modeling has been traditionally applied
as an evaluative approach, ie, with the focus on developing retrospective and explanatory …

QSAR modeling of the blood–brain barrier permeability for diverse organic compounds

L Zhang, H Zhu, TI Oprea, A Golbraikh… - Pharmaceutical …, 2008 - Springer
Purpose Development of externally predictive Quantitative Structure–Activity Relationship
(QSAR) models for Blood–Brain Barrier (BBB) permeability. Methods Combinatorial QSAR …

The role of the European Chemicals Bureau in promoting the regulatory use of (Q) SAR methods

AP Worth, A Bassan, J De Bruijn… - SAR and QSAR in …, 2007 - Taylor & Francis
Under the proposed REACH (Registration, Evaluation and Authorisation of CHemicals)
legislation,(Q) SAR models and grouping methods (chemical categories and read across …

Anticancer activity of selected phenolic compounds: QSAR studies using ridge regression and neural networks

S Nandi, M Vracko, MC Bagchi - Chemical biology & drug …, 2007 - Wiley Online Library
Phenol and its congeners are known to induce caspase‐mediated apoptosis activity and
cytotoxicity on various cancer cell lines. Apoptosis, scavenging of radicals, antioxidant, and …

Regression methods for developing QSAR and QSPR models to predict compounds of specific pharmacodynamic, pharmacokinetic and toxicological properties

CW Yap, H Li, ZL Ji, YZ Chen - Mini reviews in medicinal …, 2007 - ingentaconnect.com
Quantitative structure-activity relationship (QSAR) and quantitative structure-property
relationship (QSPR) models have been extensively used for predicting compounds of …

Robust modelling of acute toxicity towards fathead minnow (Pimephales promelas) using counter-propagation artificial neural networks and genetic algorithm

V Drgan, Š Župerl, M Vračko, F Como… - SAR and QSAR in …, 2016 - Taylor & Francis
Large worldwide use of chemicals has caused great concern about their possible adverse
effects on human health, flora and fauna. Increased production of new chemicals has also …

Determining chemical reactivity driving biological activity from SMILES transformations: The bonding mechanism of anti-HIV pyrimidines

MV Putz, NA Dudaş - Molecules, 2013 - mdpi.com
Assessing the molecular mechanism of a chemical-biological interaction and bonding
stands as the ultimate goal of any modern quantitative structure-activity relationship (QSAR) …