Computer-Aided Discovery of Novel Breast Cancer Therapeutics
|Institution:||Molecular Research Institute|
Marcia Dawson , Ph.D. -
Danni Harris , Ph.D. -
|Award Cycle:||2000 (Cycle VI)||Grant #: 6XB-0018||Award: $112,041|
|Award Type:||SPRC Exploratory|
|Innovative Treatments>New drug design: creative science|
Initial Award Abstract (2000)
Our CBCRP-funded project represents a collaborative effort to explore a computational approach to discovery of new compounds to treat breast cancer. The focus is to use a set of compounds already known to have the desired activity to generate a 3-dimensional pharmacophore that contains the requirements for this activity. Searching of 3-D databases using this pharmacophore as a query will result in the discovery of novel candidate therapeutics. These compounds will be tested in simple assays using breast cancer cell lines. Our interest evolves from previous work on vitamin A compounds, called retinoids. These compounds regulate cell differentiation and proliferation. Unfortunately, retinoids must be administered in doses that cause toxic side effects that limit patient compliance. Thus, a primary goal of our effort will be to discover novel retinoids that could both be useful as anti-breast cancer chemotherapeutic agents and show reduced toxicity. Our two laboratories represent complimentary disciplines. First, Gilda Loew and colleagues have experience in development of computer software that generates 3-dimensional pharmacophores leading to the identification of novel drug compounds. Second, Marcia Dawson has the combined experience in breast cancer and retinoid biology. Prior work established evidence for compounds having cancer cell growth inhibiting and apoptosis (programmed cell death) inducing activities that do not involve interactions with retinoid receptors. Further, these new compounds are effective against more malignant breast cancer cells that resist therapy with anti-estrogens. Using CBCRP support we will expand on these observations; (i) by using this data in the computational group together with an in-house program called MOLMOD to develop a 3-D pharmacophore to identify molecular requirements for inducing cancer cell apoptosis; and (ii) to search data bases to identify new compounds that satisfy these requirements. The expertise of the cancer biology group will ensure that the compounds selected and acquired from these leads are rapidly assessed for cancer cell growth inhibition and analysis of apoptosis induction. Both the active and inactive compounds identified will be used to refine and to validate the 3-D pharmacophore, which will then be used to select second-generation compounds for testing. Thus, two useful outcomes are anticipated from the one-year collaborative effort: (i) to identify a small set of highly promising novel compounds that inhibit human breast cancer cell growth by inducing apoptosis independently of the traditional retinoid receptors; and (ii) find a larger set of second generation leads for future study. We are hopeful that our approach will greatly enhance the efficiency and likelihood of identifying promising novel leads for use in breast cancer therapy.
Final Report (2002)
Notes: The project was extended an additional year to complete the aims and funding.
Dr. Danni Harris at the Molecular Research Institute replaced Gilda Loew as a co-PI in March, 2001. In April, 2001 Dr. Marcia Dawson relocated to The Burnham Institute, La Jolla. The goals of this exploratory project were to develop a novel three-dimensional (3D) pharmacophore, which is a molecular framework that carries the essential structural and electronic features responsible for a drug's biological activity, in order to identify new drug candidates that would cause the death of breast cancer cells, while sparing normal cells. In addition to causing the death of cancer cells by the process of apoptosis, the original compounds in this series behaved like vitamin A derivatives. Therefore, they regulated gene activities controlled by retinoids by interacting with the nuclear retinoid receptor proteins. These interactions caused toxic effects to normal cells. This research effort melded the scientific disciplines of cell biology and computational chemistry. We hypothesized that by investigating a group of these compounds using computational methods we could identify the properties necessary for selective anticancer activity, then identify other compounds these had these properties by searching through databases of compounds whose structural and electronic properties could be calculated using our software. Thus, the software was used to represent each compound in mathematical terms, then compare these terms for similarity to the mathematical representation of the pharmacophore. The software ranked the compounds on the basis of similarity. This method allowed rapid screening of compound databases without the expense of conducting actual laboratory studies using cancer cells. In our pilot study, we identified 200 such compounds. Of these, 11 were obtained from the National Cancer Institute compound library and evaluated for their activity against human breast cancer cells that were not growth-inhibited by standard retinoids. Of these compounds, one was highly active and found to have been selected for clinical studies against cancer. These results indicated that our strategy would work. However, inspection of the general structural properties of all the identified compounds revealed that the majority lacked drug-like properties because of their size or lack of solubility. This result indicated the necessity for improving the features of the pharmacophore. The improved second-generation pharmacophore, which was based on 55 compounds in this novel class, had seven elements, compared to the original five, that were necessary for inducing breast cancer cell death. At present, we are adapting several compound databases that contain more drug-like molecules for use in searching to find comparisons with our improved pharmacophore. Note: The CBCRP funded Dr. Dawson for a new grant in 2002 to continue studies on the novel retinoids and molecular modeling to refine structure vs. biological effects.