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In the area of cancer research, the development of new and potent inhibitors of anti-apoptotic proteins is a very active and promising topic. The small molecule MIM1 has been reported earlier as one of the first selective inhibitors of the anti-apoptotic protein Mcl-1. In the present paper, we first revised the structure of this molecule based on extensive physicochemical analyses. Then we designed and synthesized a focused library of analogues for the corrected structure of MIM1. Next, these molecules were subjected to a panel of in cellulo biological studies, allowing the identification of dual Bcl-x L /Mcl-1 inhibitors, as well as selective Mcl-1 inhibitors. These results have been complemented by fluorescence polarization assays with the Mcl-1 protein. Preliminary structure-activity relationships were discussed and extensive molecular modelling studies allowed us to propose a rationale for the biological activity of this series of new inhibitors, in particular for the selectivity of inhibition of Mcl-1 versus Bcl-x L .

Inhibition of Bcl-2 family protein-protein interactions (PPI) is a very promising direction in cancer chemotherapy. Hence over the last decade, many medicinal chemistry studies endeavoured to discover drug candidates, and a wealth of chemical scaffolds with striking chemical diversity was reported as Bcl-xL inhibitors. This raises the question of whether all these molecules could occupy a unique binding site, or rather discrete pockets of the protein surface. To test if small and chemically diverse Bcl-xL inhibitors are likely to bind a single pocket, and to identify which pocket, we used a battery of computational and modeling approaches. We first checked that the large dataset of Bcl-xL inhibitors we built can actually fit to a universal pharmacophore. Then we defined the probable binding hot spots of interaction through comparison of crystal structures, as well as virtual fragment screening. Finally, new analogues of small polyphenol derivatives were synthesized to precisely probe a hydrogen bond suggested by docking experiments. Bcl-xL inhibition potency of these products confirmed the predicted binding mode. This combination of X-ray structure exploration, molecular modeling studies and medicinal chemistry supports that all these small Bcl-xL inhibitors occupy the same hot spot of interaction. The identification of this binding site should help the design and optimization of small PPI Bcl-xL inhibitors., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

We describe the synthesis of a series of new molecules containing phenol and triazoles moieties, compounds which have been evaluated for their ability to inhibit Bax/Bcl-xL interactions in cancer cells, by using BRET assays, and to induce cell death. Several derivatives exhibit a very promising activity, being more potent than the reference compounds acylpyrogallol A and ABT-737. These preliminary results demonstrate that derivatives of this family can be attractive to develop new molecules with potent anticancer activity., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Drug-discovery projects frequently employ structure-based information through protein modeling and ligand docking, and there is a plethora of reports relating successful use of them in virtual screening. Hit/lead optimization, which represents the next step and the longest for the medicinal chemist, is very rarely considered. This is not surprising because lead optimization is a much more complex task. Here, a homology model of the histamine H(3) receptor was built and tested for its ability to discriminate ligands above a defined threshold of affinity. In addition, drug safety is also evaluated during lead optimization, and "antitargets" are studied. So, we have used the same benchmarking procedure with the HERG channel and CYP2D6 enzyme, for which a minimal affinity is strongly desired. For targets and antitargets, we report here an accuracy as high as at least 70%, for ligands being classified above or below the chosen threshold. Such a good result is beyond what could have been predicted, especially, since our test conditions were particularly stringent. First, we measured the accuracy by means of AUC of ROC plots, i. e. considering both false positive and false negatives. Second, we used as datasets extensive chemical libraries (nearly a thousand ligands for H(3)). All molecules considered were true H(3) receptor ligands with moderate to high affinity (from microM to nM range). Third, the database is issued from concrete SAR (Bioprojet H(3) BF2.649 library) and is not simply constituted by few active ligands buried in a chemical catalogue.