Global structure-activity relationship model for nonmutagenic carcinogens using virtual ligand-protein interactions as model descriptors.

Structure-activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe the use of a traditional fragment-based SAR approach along with a new virtual ligand-protein interaction-based approach for modeling of nonmutagenic carcinogens. The ligand-based SAR models used descriptors derived from computationally calculated ligand-binding affinities for learning set agents to 5495 proteins.

Anticancer SAR models for MCF-7 and MDA-MB-231 breast cell lines.

The National Cancer Institute's Developmental Therapeutics Program (DTP) maintains the screening results obtained in 60 standardized cancer cell lines for ~43,000 compounds. Here the application of the categorical structure-activity relationship (cat-SAR) program for the identification of the structural attributes of identified compounds that display differential cytostatic or cytotoxic activity to one breast cancer cell line and not another is reported. The goal of this approach is to separate features associated with antiproliferative activity towards many cell lines from those that affect only a specific cell type.

Structure-activity relationship analysis of rat mammary carcinogens.

Structure-activity relationship (SAR) models are powerful tools to investigate the mechanisms of action of chemical carcinogens and to predict the potential carcinogenicity of untested compounds. We describe here the application of the cat-SAR (categorical-SAR) program to two learning sets of rat mammary carcinogens. One set of developed models was based on a comparison of rat mammary carcinogens to rat noncarcinogens (MC-NC), and the second set compared rat mammary carcinogens to rat nonmammary carcinogens (MC-NMC).

The challenge of testing chemicals for potential carcinogenicity using multiple short-term assays: an analysis of a proposed test battery for hair dyes.

Recent reports of the association of hair dyes usage with increased bladder cancer risk in women with the slow NAT-2 acetylator phenotype have resulted both in attempts to identify the putative carcinogen as well as in devising batteries of tests that could be used to screen for such putative carcinogens in hair dye formulations, their intermediates and final products. Analytical studies have reported the presence of traces ( approximately 0.5 ppm) of the carcinogen 4-aminobiphenyl in some hair dye preparations.

CoMFA, HQSAR and molecular docking studies of butitaxel analogues with beta-tubulin.

Results from biochemical analyses for a series of 20 butitaxel analogues, paclitaxel and docetaxel were used to build two- and three-dimensional quantitative structure-activity relationship (QSAR) models in order to investigate the properties associated with microtubule assembly and stabilization. A comparative molecular field analysis (CoMFA) model was built using steric and electrostatic fields. The CoMFA model yielded an r2 of 0.

Identification of structural components associated with cytostatic activity in MCF-7 but not in MDA-MB-231 cells.

The National Cancer Institute's Developmental Therapeutics Program maintains the screening results obtained in 60 standardized cancer cell lines and contained 37,836 compounds for this study. This dataset has shown to be an outstanding resource for the development of structure-activity relationship (SAR) models describing anticancer activity. We report here a novel SAR modeling approach based on a subtractive protocol to develop models that describe cell type-specific molecular descriptors of cytotoxicity.