In 1982, Kuntz et al. published an article with the title “A Geometric Approach to Macromolecule-Ligand Interactions”, where they described a method “to explore geometrically feasible alignment of ligands and receptors of known structure”. Since then, small molecule docking has been employed as a fast way to estimate the binding pose of a given compound within a specific target protein and also to predict binding affinity. Remarkably, the first docking method suggested by Kuntz and colleagues aimed to predict binding poses but very little was specified about binding affinity. This raises the question as to whether docking is the right tool to estimate binding affinity. The short answer is no, and this has been concluded in several comprehensive analyses. However, in this opinion paper we discuss several critical aspects that need to be reconsidered before a reliable binding affinity prediction through docking is realistic. These are not the only issues that need to be considered, but they are perhaps the most critical ones. We also consider that in spite of the huge efforts to enhance scoring functions, the accuracy of binding affinity predictions is perhaps only as good as it was 10–20 years ago. There are several underlying reasons for this poor performance and these are analyzed. In particular, we focus on the role of the solvent (water), the poor description of H-bonding and the lack of the systems’ true dynamics. We hope to provide readers with potential insights and tools to overcome the challenging issues related to binding affinity prediction via docking.
We have previously reported that the endocannabinoid, 2-arachidonoyl-glycerol (2-AG), is hydrolyzed in rat cerebellar membranes by monoglyceride lipase (MGL)-like enzymatic activity. The present study shows that, like MGL, 2-AG-degrading enzymatic activity is sensitive to inhibition by sulfhydryl-specific reagents. Inhibition studies of this enzymatic activity by N-ethylmaleimide analogs revealed that analogs with bulky hydrophobic N-substitution were more potent inhibitors than hydrophilic or less bulky agents. Interestingly, the substrate analog N-arachidonylmaleimide was found to be the most potent inhibitor. A comparison model of MGL was constructed to get a view on the cysteine residues located near the binding site. These findings support our previous conclusion that the 2-AG-degrading enzymatic activity in rat cerebellar membranes corresponds to MGL or MGL-like enzyme and should facilitate further efforts to develop potent and more selective MGL inhibitors.
MYC oncoproteins are involved in the genesis and maintenance of the majority of human tumors but are considered undruggable. By using a direct in vivo shRNA screen, we show that liver cancer cells that have mutations in the gene encoding the tumor suppressor protein p53 (Trp53 in mice and TP53 in humans) and that are driven by the oncoprotein NRAS become addicted to MYC stabilization via a mechanism mediated by aurora kinase A (AURKA). This MYC stabilization enables the tumor cells to overcome a latent G2/M cell cycle arrest that is mediated by AURKA and the tumor suppressor protein p19(ARF). MYC directly binds to AURKA, and inhibition of this protein-protein interaction by conformation-changing AURKA inhibitors results in subsequent MYC degradation and cell death. These conformation-changing AURKA inhibitors, with one of them currently being tested in early clinical trials, suppressed tumor growth and prolonged survival in mice bearing Trp53-deficient, NRAS-driven MYC-expressing hepatocellular carcinomas (HCCs). TP53-mutated human HCCs revealed increased AURKA expression and a positive correlation between AURKA and MYC expression. In xenograft models, mice bearing TP53-mutated or TP53-deleted human HCCs were hypersensitive to treatment with conformation-changing AURKA inhibitors, thus suggesting a therapeutic strategy for this subgroup of human HCCs.
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