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An extensive crystal survey of the Cambridge Structural Database has been carried out to provide hydrogen-bond data for use in drug-design strategies. Previous crystal surveys have generated 1D frequency distributions of hydrogen-bond distances and angles, which are not sufficient to model the hydrogen bond as a ligand-receptor interaction. For each hydrogen-bonding group of interest to the drug designer, geometric hydrogen-bond criteria have been derived. The 3D distribution of complementary atoms about each hydrogen-bonding group has been ascertained by dividing the space about each group into bins of equal volume and counting the number of observed hydrogen-bonding contacts in each bin. Finally, the propensity of each group to form a hydrogen bond has been calculated. Together, these data can be used to predict the potential site points with which a ligand could interact and therefore could be used in molecular-similarity studies, pharmacophore query searching of databases, or de novo design algorithms.

Drug discovery faces economic and scientific imperatives to deliver lead molecules rapidly and efficiently. Using traditional paradigms the molecular design, synthesis, and screening loops enforce a significant time delay leading to inefficient use of data in the iterative molecular design process. Here, we report the application of a flow technology platform integrating the key elements of structure-activity relationship (SAR) generation to the discovery of novel Abl kinase inhibitors. The platform utilizes flow chemistry for rapid in-line synthesis, automated purification, and analysis coupled with bioassay. The combination of activity prediction using Random-Forest regression with chemical space sampling algorithms allows the construction of an activity model that refines itself after every iteration of synthesis and biological result. Within just 21 compounds, the automated process identified a novel template and hinge binding motif with pIC50 > 8 against Abl kinase--both wild type and clinically relevant mutants. Integrated microfluidic synthesis and screening coupled with machine learning design have the potential to greatly reduce the time and cost of drug discovery within the hit-to-lead and lead optimization phases.

Inhibition of N-myristoyltransferase has been validated pre-clinically as a target for the treatment of fungal and trypanosome infections, using species-specific inhibitors. In order to identify inhibitors of protozoan NMTs, we chose to screen a diverse subset of the Pfizer corporate collection against Plasmodium falciparum and Leishmania donovani NMTs. Primary screening hits against either enzyme were tested for selectivity over both human NMT isoforms (Hs1 and Hs2) and for broad-spectrum anti-protozoan activity against the NMT from Trypanosoma brucei. Analysis of the screening results has shown that structure-activity relationships (SAR) for Leishmania NMT are divergent from all other NMTs tested, a finding not predicted by sequence similarity calculations, resulting in the identification of four novel series of Leishmania-selective NMT inhibitors. We found a strong overlap between the SARs for Plasmodium NMT and both human NMTs, suggesting that achieving an appropriate selectivity profile will be more challenging. However, we did discover two novel series with selectivity for Plasmodium NMT over the other NMT orthologues in this study, and an additional two structurally distinct series with selectivity over Leishmania NMT. We believe that release of results from this study into the public domain will accelerate the discovery of NMT inhibitors to treat malaria and leishmaniasis. Our screening initiative is another example of how a tripartite partnership involving pharmaceutical industries, academic institutions and governmental/non-governmental organisations such as Medical Research Council and Wellcome Trust can stimulate research for neglected diseases.

SMYD3 has been implicated in a range of cancers; however, until now no potent selective small molecule inhibitors have been available for target validation studies. A novel oxindole series of SMYD3 inhibitors was identified through screening of the Epizyme proprietary histone methyltransferase-biased library. Potency optimization afforded two tool compounds, sulfonamide EPZ031686 and sulfamide EPZ030456, with cellular potency at a level sufficient to probe the in vitro biology of SMYD3 inhibition. EPZ031686 shows good bioavailability following oral dosing in mice making it a suitable tool for potential in vivo target validation studies. KEYWORDS: SMYD3, oxindole, methyltransferase, KMT, oncology, tool compound S et and Mynd Domain containing 3 (SMYD3) is a lysine methyltransferase (KMT) expressed at high levels in a number of different cancer histologies and is associated with a poor clinical prognosis. 1−10 While no single mechanism has emerged to explain this correlation, a number of studies have implicated SMYD3 in the regulation of gene transcription and signal transduction pathways critical for cell survival in breast, liver, prostate, pancreatic, and lung cancer models. 4,7−9 In addition, considerable evidence has been reported in the literature showing that genetic knockdown of SMYD3 leads to a decrease in proliferation of a variety of cancer cell lines. 4,[7][8][9]11 Two studies, employing RNAi-based technologies, have shown that ablation of SMYD3 in hepatocellular carcinoma cell lines greatly reduces cell viability and that its pro-oncogenic role is dependent on its catalytic activity. 7,9 Moreover, SMYD3 has also been shown to be a critical mediator of transformation induced by a KRAS gain-of-function mutation in both pancreatic and lung adenocarcinoma mouse models; these models were likewise dependent on the catalytic activity of SMYD3. 11 The biological function of SMYD3 is still poorly understood. Early studies of SMYD3 suggested that its primary function is to methylate histones. Indeed, several reports have indicated that SMYD3 modifies histone H3 on lysine 4, 9,12 but have also identified a novel modification of histone H4 on lysine 5. 7 The results of these studies have not yet yielded a clear picture of how SMYD3 might be regulating chromatin, but a recent study has strongly implicated SMYD3 as a direct regulator of MAPK pathways in the cytoplasm and not as a regulator of transcription. MAP3K2 (MEKK2) was shown to be trimethylated at lysine 260 by SMYD3. Modification of this residue leads to enhanced downstream MAPK activation and appears to be critical for mutant KRAS driven oncogenesis. 11 SMYD3's role in cancer cell line proliferation, its effect on known oncogenic signal transduction pathways, and the association of SMYD3 mRNA expression with aggressive transformed phenotypes make SMYD3 an attractive target for therapeutic intervention. We report here the first potent and selective small molecule inhibitors suitable for target validation studies.Compound 1 was identified as a mi...

A key challenge in the development of precision medicine is defining the phenotypic consequences of pharmacological modulation of specific target macromolecules. To address this issue, a variety of genetic, molecular and chemical tools can be used. All of these approaches can produce misleading results if the specificity of the tools is not well understood and the proper controls are not performed. In this paper we illustrate these general themes by providing detailed studies of small molecule inhibitors of the enzymatic activity of two members of the SMYD branch of the protein lysine methyltransferases, SMYD2 and SMYD3. We show that tool compounds as well as CRISPR/Cas9 fail to reproduce many of the cell proliferation findings associated with SMYD2 and SMYD3 inhibition previously obtained with RNAi based approaches and with early stage chemical probes.

A new computational algorithm for protein binding sites characterization and comparison has been developed, which uses a common reference framework of the projected ligand-space four-point pharmacophore fingerprints, includes cavity shape, and can be used with diverse proteins as no structural alignment is required. Protein binding sites are first described using GRID molecular interaction fields (GRID-MIFs), and the FLAP (fingerprints for ligands and proteins) method is then used to encode and compare this information. The discriminating power of the algorithm and its applicability for large-scale protein analysis was validated by analyzing various scenarios: clustering of kinase protein families in a relevant manner, predicting ligand activity across related targets, and protein-protein virtual screening. In all cases the results showed the effectiveness of the GRID-FLAP method and its potential use in applications such as identifying selectivity targets and tools/hits for new targets via the identification of other proteins with pharmacophorically similar binding sites.

This review highlights the medicinal and synthetic chemistry relevance of replacing an aromatic chloride motif with an aromatic nitrile.