Since the advent of the Hammett equation (1935) and the applicants' incorporation of it into a generalized basis for quantitative structure-activity relationships (1962) in all areas of biology (DNA, enzymes, organelles, cells, membranes, whole animals) this paradigm has been extended to all facets of chemistry and biology. A database based on the QSAR paradigm has now been established and is growing at the rate of about 1000 QSAR/yr. It contains 11,000 equations plus attendant data; four thousand three hundred of these equations pertain to biological systems. At the first level of understanding, each equation encapsulates a mechanistically based and statistically sound predictor for understanding how congeneric molecules can be expected to react. A second level of insight is possible in biological reactions that involve bond making, breaking or change transfer interactions. Often, these QSAR can be related to similar organic reactions via electronic terms most often delineated by Hammett constants or molecular orbital indices. Moreover, more complex understanding is attained when biological QSAR can be related to each other in groups; lateral validation is an effective means of bringing cohesion to a body of work on a particular subject. The applicants' highly efficient and interactive electronic system provides an avenue of opportunity for such comparative analyses.
Their aim i s to utilize this system to enhance our understanding of the beneficial and toxic attributes of free radicals with particular emphasis on phenols, anilines and benzylic type compounds entities with active hydrogens. The relationship between cellular toxicity and estrogenic activity will also be evaluated with phenols. The preponderance of drugs, pesticides, herbicides and environmental chemicals that contain the phenolic moiety makes it an insidious and potent threat to our overall well being. Its mechanism of action at the molecular and cellular level needs to be clearly elucidated. Studies in various cell lines as well as binding assays versus particular enzymatic targets will be used to examine the hazard/benefit ratio. Thus, our long term objective is to enhance the development of a molecular science based on physical organic chemistry tenets of QSAR that constitute the basis of predictive toxicology.
| Hadjipavlou-Litina, D; Garg, Rajni; Hansch, Corwin (2004) Comparative quantitative structure-activity relationship studies (QSAR) on non-benzodiazepine compounds binding to benzodiazepine receptor (BzR). Chem Rev 104:3751-94 |
| Hansch, Corwin; Bonavida, Benjamin; Jazirehi, Ali R et al. (2003) Quantitative structure-activity relationships of phenolic compounds causing apoptosis. Bioorg Med Chem 11:617-20 |
| Kurup, Alka; Mekapati, Suresh B; Garg, Rajni et al. (2003) HIV-1 protease inhibitors: a comparative QSAR analysis. Curr Med Chem 10:1679-88 |
| Garg, Rajni; Kurup, Alka; Mekapati, Suresh Babu et al. (2003) Cyclooxygenase (COX) inhibitors: a comparative QSAR study. Chem Rev 103:703-32 |
| Garg, Rajni; Kurup, Alka; Mekapati, Suresh B et al. (2003) Searching for allosteric effects via QSAR. Part II. Bioorg Med Chem 11:621-8 |
| Hansch, Corwin; Garg, Rajni; Kurup, Alka et al. (2003) Allosteric interactions and QSAR: on the role of ligand hydrophobicity. Bioorg Med Chem 11:2075-84 |
| Verma, Rajeshwar P; Kapur, Sanjay; Barberena, Omar et al. (2003) Synthesis, cytotoxicity, and QSAR analysis of X-thiophenols in rapidly dividing cells. Chem Res Toxicol 16:276-84 |
| Hansch, Corwin; Steinmetz, Wayne E; Leo, Albert J et al. (2003) On the role of polarizability in chemical-biological interactions. J Chem Inf Comput Sci 43:120-5 |
| Hansch, Corwin; Jazirehi, Ali; Mekapati, Suresh Babu et al. (2003) QSAR of apoptosis induction in various cancer cells. Bioorg Med Chem 11:3015-9 |
| Selassie, Cynthia D; Garg, Rajni; Kapur, Sanjay et al. (2002) Comparative QSAR and the radical toxicity of various functional groups. Chem Rev 102:2585-605 |
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