For thirty years the study o f Quantitative Structure Activity Relationships (QSAR) has been an active area o f research aimed at developing an understanding o f the interactions be­ tween inhibitors o f photosynthetic electron transport and the herbicide binding site in the Pho­ tosystem II (PS II) reaction centre. Many QSAR studies o f PS II inhibitors with diverse chemi­ cal structures have ...

The Discovery Bus, a multi-agent software system designed for automating aspects of Molecular Design, particularly expert decision making, is described. It extends approaches aimed at automating the processing of drug discovery information but where control remains with the human expert, to automating the " tacit knowledge " of the expert and best practice, which we model as a workflow, and exp...

Quantitative structure activity relationship (QSAR) studies of twenty four 5-cyano, N1, 6disubstituted, 2-thiouracil derivatives were performed for their central nervous system (CNS) depressant (locomotor) activity using VlifeMDS3.5 software. Partial least square (PLS) linear regression analysis coupled with stepwise variable selection method was applied to derive QSAR models which were further...

In this contribution, the advantages and limitations of two computational techniques that can be used for the investigation of nanoparticles activity and toxicity: classic nano-QSAR (Quantitative Structure-Activity Relationships employed for nanomaterials) and 3D nano-QSAR (three-dimensional Quantitative Structure-Activity Relationships, such us Comparative Molecular Field Analysis, CoMFA/Compa...

A series of new 3-amino-6-chloro-7-(azol-2 or 5-yl)-1,1-dioxo-1,4,2-benzodithiazine derivatives 5a-j have been synthesized and evaluated in vitro for their antiproliferative activity at the U.S. National Cancer Institute. The most active compound 5h showed significant cytotoxic effects against ovarian (OVCAR-3) and breast (MDA-MB-468) cancer (10% and 47% cancer cell death, respectively) as well...

This article provides an overview of methods for reliability assessment of quantitative structure-activity relationship (QSAR) models in the context of regulatory acceptance of human health and environmental QSARs. Useful diagnostic tools and data analytical approaches are highlighted and exemplified. Particular emphasis is given to the question of how to define the applicability borders of a Q...

This chapter critically reviews some of the important methods being used for building quantitative structure-activity relationship (QSAR) models using the artificial neural networks (ANNs). It attends predominantly to the use of multilayer ANNs in the regression analysis of structure-activity data. The highlighted topics cover the approximating ability of ANNs, the interpretability of the resul...

Quantitative Structure-Activity Relationships (QSAR) is a method to create models that can predict certain properties of compounds. Because of the importance of QSAR in designing new drugs, ability to accelerate this process becomes crucial. One way to achieve that is to be able to quickly explore the QSAR model space in the search for the best models. The cloud computing paradigm very well fit...

although extensive experimental work has been carried out during the last several years, experimental reaction rate constants are available only for hundreds of compounds. therefore, it is useful to develop a theoretical prediction method, which can be used to obtain estimates of the necessary kinetic parameters. one of the most successful approaches to predict chemical properties starting only...