Three- and four-dimensional quantitative structure activity relationship (3D/4D-QSAR) pharmacophore models of competitive inhibitors of CYP2D6 were constructed using data from our laboratory or the literature. The 3D-QSAR pharmacophore models of the common structural features of CYP2D6 inhibitors were built using the program Catalyst (Molecular Simulations, San Diego, CA, USA). These 3D-QSAR mo...

QSAR models of 22 benzamidine derivatives reported as inhibitors of thrombin have been developed using the descriptors heat of formation, valence connectivity index, shape index, solvent accessibility surface area, molar refractivity, log P and molecular weight. QSAR models, in which either heat of formation or shape index or molar refractivity is present, have good predictive powers as correla...

the urgent need of neuraminidase inhibitors (ni) has provided an impetus for understanding the structure requisite at molecular level. our search for selective inhibitors of neuraminidase has led to the identification of pharmacophoric requirements at various positions around acyl thiourea pharmacophore. the main objective of present study is to develop selective ni, with least toxicity and dru...

Membrane-interaction quantitative structure-activity relationship (MI-QSAR) models for two skin penetration enhancer data sets of 61 and 42 compounds were constructed and compared to QSAR models constructed for the same two data sets using only classic intramolecular QSAR descriptors. These two data sets involve skin penetration enhancement of hydrocortisone and hydrocortisone acetate, and the ...

A novel scheme for modeling 3D QSAR has been developed. A method involving multiple self-organizing neural network adjusted to be analyzed by the PLS (partial least squares) analysis was used to model 3D QSAR of the selected colchicinoids. The model obtained allows the identification of some structural determinants of the biological activity of compounds.

A ligand-based 3D-QSAR study for the identification of MMP3 inhibitors was developed by applying an innovative alignment method capable of taking into account information obtained from available X-ray MMP3 structures. Comparison of the obtained model with data recently published using a docking-based alignment method indicated that the ligand-based 3D-QSAR model provided better predictive abili...

Based on descriptors of n-octanol/water partition coefficients (logKow), molecular connectivity indices, and quantum chemical parameters, several QSAR models were built to estimate the soil sorption coefficients (logKoc) of substituted anilines and phenols. Results showed that descriptor logKow plus molecular quantum chemical parameters gave poor regression models. Further study was performed t...

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...

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...