Pamicogrel

Stem cell transplantation and genetic therapies offer potential cures for patients with sickle cell disease (SCD), but these options require advanced medical facilities and are expensive. Consequently, these treatments will not be available for many years to the majority of patients suffering from this disease. What is urgently needed now is an inexpensive oral drug in addition to hydroxyurea, the only drug approved by the FDA that inhibits sickle-hemoglobin polymerization. Here, we report the results of the first phase of our phenotypic screen of the 12,657 compounds of the Scripps ReFRAME drug repurposing library using a recently developed high-throughput assay to measure sickling times following deoxygenation to 0% oxygen of red cells from sickle trait individuals. The ReFRAME library is a very important collection because the compounds are either FDA-approved drugs or have been tested in clinical trials. From dose-response measurements, 106 of the 12,657 compounds exhibit statistically significant antisickling at concentrations ranging from 31 nM to 10 μM. Compounds that inhibit sickling of trait cells are also effective with SCD cells. As many as 20 of the 106 antisickling compounds emerge as potential drugs. This estimate is based on a comparison of inhibitory concentrations with free concentrations of oral drugs in human serum. Moreover, the expected therapeutic potential for each level of inhibition can be predicted from measurements of sickling times for cells from individuals with sickle syndromes of varying severity. Our results should motivate others to develop one or more of these 106 compounds into drugs for treating SCD.

A compound's synthetic accessibility (SA) is an important aspect of drug design, since in some cases computer-designed compounds cannot be synthesized. There have been several reports on SA prediction, most of which have focused on the difficulties of synthetic reactions based on retro-synthesis analyses, reaction databases and the availability of starting materials. We developed a new method of predicting SA using commercially available compound databases and molecular descriptors. SA was estimated from the probability of existence of substructures consisting of the compound in question, the number of symmetry atoms, the graph complexity, and the number of chiral centers of the compound. The probabilities of the existence of given substructures were estimated based on a compound library. The predicted SA results reproduced the expert manual assessments with a Pearson correlation coefficient of 0.56. Since our method required a compound database and not a reaction database, it should be easy to customize the prediction for compound vendors. The correlation between the sales price of approved drugs and the SA values was also examined and found to be weak. The price most likely depends on the total cost of development and other factors.