Summary The dynamic and reversible acetylation of proteins catalyzed by histone acetyltransferases (HATs) and histone deacetylases (HDACs) is a major epigenetic regulatory mechanism of gene transcription 1 associated with multiple diseases. While HDAC inhibitors are approved to treat certain cancers, progress on the development of drug-like HAT inhibitors has lagged 2. The HAT paralogs p300 and CBP (p300/CBP) are key transcriptional co-activators essential for a multitude of cellular processes and also implicated in human pathological conditions, including cancer 3. Current p300/CBP HAT domain inhibitors including natural products, 4 bi-substrate analogs (Lys-CoA) 5 and the widely utilized C646 6, 7 lack potency or selectivity. Here, we describe A-485, a potent, selective and drug-like p300/CBP catalytic inhibitor. We show the first high resolution (1.95Å) co-crystal structure of a small molecule bound to the catalytic active site of p300 and demonstrate that A-485 is acetyl-CoA competitive. A-485 selectively inhibited proliferation across lineage-specific tumor types, including several hematological malignancies and androgen receptor-positive prostate cancer. A-485 inhibited the androgen receptor transcriptional program in both androgen sensitive and castrate resistant prostate cancer and inhibited tumor growth in a castration resistant xenograft model. These results demonstrate the feasibility of selectively targeting the catalytic activity of histone acetyltransferases.

A new method for analyzing a structure-activity relationship is proposed. By use of a simple quantitative index, one can readily identify "structure-activity cliffs": pairs of molecules which are most similar but have the largest change in activity. We show how this provides a graphical representation of the entire SAR, in a way that allows the salient features of the SAR to be quickly grasped. In addition, the approach allows us view the SARs in a data set at different levels of detail. The method is tested on two data sets that highlight its ability to easily extract SAR information. Finally, we demonstrate that this method is robust using a variety of computational control experiments and discuss possible applications of this technique to QSAR model evaluation.

No abstract

This perspectives article has been taken from a talk the author gave at the symposium in honor of Yvonne C. Martin's retirement, held at the American Chemical Society spring meeting in Chicago on March 25, 2007. The talk was intended as a somewhat lighthearted attempt to gaze into the future; inevitably, in print, things will come across more seriously than was intended. As we all know-the past is rarely predictive of the future.

ALADDIN is a computer program for the design or recognition of compounds that meet geometric, steric, and substructural criteria. ALADDIN searches a database of three-dimensional structures, marks atoms that meet substructural criteria, evaluates geometric criteria, and prepares a number of files that are input for molecular modification and coordinate generation as well as for molecular graphics. Properties calculated from the three-dimensional structure are described by either properties calculated from the molecule itself or from the molecule as compared to a reference molecule and associated surfaces. ALADDIN was used to design analogues to probe a bioactive conformation of a small molecule and a peptide, to test alternative superposition rules for receptor mapping of the D2 dopamine receptor, to recognize unexpected D2 dopamine agonist activity of existing compounds, and to design compounds to fit a binding site on a protein of known structure. We have found that series designed by ALADDIN show much more subtle variation in shape than do those designed by traditional methods and that compounds can be designed to be very close matches to the objective.