The process for drug discovery and development is challenging, time consuming and
expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut …

In the absence of three-dimensional (3D) structures of potential drug targets, ligand-based
drug design is one of the popular approaches for drug discovery and lead optimization. 3D …

There are no formal guidelines for the development of quantitative structure–activity
relationships (QSARs). However, there are a number of practices that should be avoided …

Quantitative structure–activity relationship (QSAR) models are useful in understanding how
chemical structure relates to the biological activity of natural and synthetic chemicals and for …

The theory of artificial neural networks is briefly reviewed focusing on supervised and
unsupervised techniques which have great impact on current chemical applications. An …

Drug discovery is the process used to discover new candidate medications. In the past, most
drugs were discovered by identification of active-ingredients or by serendipity. Modern drug …

A quantitative structure− activity relationship (QSAR) model is presented in which both the
independent and dependent (response) variables are derived from density functional theory …

Background: There are many ways to represent a molecule's properties, including atomic-
connectivity drawings. NMR spectra, and molecular orbital models. Prior methods for …

The scientists, and the researchers around the globe generate tremendous amount of
information everyday; for instance, so far more than 74 million molecules are registered in …

A method, system and computer program product for scaling, or dimensionally reducing,
multi-dimensional data sets, that scales well for large data sets. The invention scales multi …