No abstract

The canonical WNT pathway plays an important role in cancer pathogenesis. Inhibition of poly­(ADP-ribose) polymerase catalytic activity of the tankyrases (TNKS/TNKS2) has been reported to reduce the Wnt/β-catenin signal by preventing poly ADP-ribosylation-dependent degradation of AXIN, a negative regulator of Wnt/β-catenin signaling. With the goal of investigating the effects of tankyrase and Wnt pathway inhibition on tumor growth, we set out to find small-molecule inhibitors of TNKS/TNKS2 with suitable drug-like properties. Starting from 1a, a high-throughput screening hit, the spiroindoline derivative 40c (RK-287107) was discovered as a potent TNKS/TNKS2 inhibitor with >7000-fold selectivity against the PARP1 enzyme, which inhibits WNT-responsive TCF reporter activity and proliferation of human colorectal cancer cell line COLO-320DM. RK-287107 also demonstrated dose-dependent tumor growth inhibition in a mouse xenograft model. These observations suggest that RK-287107 is a promising lead compound for the development of novel tankyrase inhibitors as anticancer agents.

Significant activity changes due to small structural changes (i.e., activity cliffs) of serine/threonine kinase Pim1 inhibitors were studied theoretically using the fragment molecular orbital method with molecular mechanics Poisson-Boltzmann surface area (FMO+MM-PBSA) approach. This methodology enables quantum-chemical calculations for large biomolecules with solvation. In the course of drug discovery targeting Pim1, six benzofuranone-class inhibitors were found to differ only in the position of the indole-ring nitrogen atom. By comparing the various qualities of complex structures based on X-ray, classical molecular mechanics (MM)-optimized, and quantum/molecular mechanics (QM/MM)-optimized structures, we found that the QM/MM-optimized structures provided the best correlation (R = 0.85) between pIC and the calculated FMO+MM-PBSA binding energy. Combining the classical solvation energy with the QM binding energy was important to increase the correlation. In addition, decomposition of the interaction energy into various physicochemical components by pair interaction energy decomposition analysis suggested that CH-π and electrostatic interactions mainly caused the activity differences.

We developed an automated FMO calculation protocol (Auto-FMO protocol) to calculate huge numbers of protein and ligand complexes, such as drug discovery targets, by an ab initio FMO method. The protocol performs not only FMO calculations but also pre-processing of input structures by homology modeling of missing atoms and subsequent MM-based optimization, as well as post-processing of calculation results. In addition, QM/MM optimization of complex structures, conformational searches of ligand structures in solvent, and MM-PBSA/GBSA calculations can be optionally carried out. In this paper, FMO calculations for 149 X-ray complex structures of estrogen receptor α and p38 MAP kinase were performed at the K computer and in-house PC cluster server by using the Auto-FMO protocol. To demonstrate the usefulness of the Auto-FMO protocol, we compared the ligand binding interaction energies by the Auto-FMO protocol with those of manually prepared data. In most cases, the data calculated by the Auto-FMO protocol showed reasonable agreement with the manually prepared data. Further improvement of the protocol is necessary for the treatment of ionization and tautomerization at the structure preparation stage, because some outlier data were observed due to these issues. The Auto-FMO protocol provides a powerful tool to deal with huge numbers of complexes for drug design, as well as for the construction of the FMO database (http://drugdesign.riken.jp/FMODB/) released in 2019.