Search

Class B G-protein-coupled receptors (GPCRs) remain an underexploited target for drug development. The calcitonin receptor (CTR) family is particularly challenging, as its receptors are heteromers comprising two distinct components: the calcitonin receptor-like receptor (CLR) or calcitonin receptor (CTR) together with one of three accessory proteins known as receptor activity-modifying proteins (RAMPs). CLR/RAMP1 forms a CGRP receptor, CLR/RAMP2 forms an adrenomedullin-1 (AM1) receptor, and CLR/RAMP3 forms an adrenomedullin-2 (AM2) receptor. The CTR/RAMP complexes form three distinct amylin receptors. While the selective blockade of AM2 receptors would be therapeutically valuable, inhibition of AM1 receptors would cause clinically unacceptable increased blood pressure. We report here a systematic study of structure–activity relationships that has led to the development of first-in-class AM2 receptor antagonists. These compounds exhibit therapeutically valuable properties with 1000-fold selectivity over the AM1 receptor. These results highlight the therapeutic potential of AM2 antagonists.

[Image: see text] The hormone adrenomedullin has both physiological and pathological roles in biology. As a potent vasodilator, adrenomedullin is critically important in the regulation of blood pressure, but it also has several roles in disease, of which its actions in cancer are becoming recognized to have clinical importance. Reduced circulating adrenomedullin causes increased blood pressure but also reduces tumor progression, so drugs blocking all effects of adrenomedullin would be unacceptable clinically. However, there are two distinct receptors for adrenomedullin, each comprising the same G protein-coupled receptor (GPCR), the calcitonin receptor-like receptor (CLR), together with a different accessory protein known as a receptor activity-modifying protein (RAMP). The CLR with RAMP2 forms an adrenomedullin-1 receptor, and the CLR with RAMP3 forms an adrenomedullin-2 receptor. Recent research suggests that a selective blockade of adrenomedullin-2 receptors would be therapeutically valuable. Here we describe the design, synthesis, and characterization of potent small-molecule adrenomedullin-2 receptor antagonists with 1000-fold selectivity over the adrenomedullin-1 receptor, although retaining activity against the CGRP receptor. These molecules have clear effects on markers of pancreatic cancer progression in vitro, drug-like pharmacokinetic properties, and inhibit xenograft tumor growth and extend life in a mouse model of pancreatic cancer. Taken together, our data support the promise of a new class of anticancer therapeutics as well as improved understanding of the pharmacology of the adrenomedullin receptors and other GPCR/RAMP heteromers.

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.

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.

Herein, we describe the discovery and optimisation of a series of potent and selective TRPV4 antagonists. The application of a variety of computational techniques (including Bayesian modelling) at the HTS triage stage enabled the early deprioritisation of likely frequent hitters. The use of methods to positively prioritise compounds for follow-up screening allowed the rapid identification of a number of interesting TRPV4 antagonist series. The hit-to-lead efforts in one such series, the hydroxypiperidines, will be described.

High-throughput screening (HTS) is an effective method for lead and probe discovery that is widely used in industry and academia to identify novel chemical matter and to initiate the drug discovery process. However, HTS can be time consuming and costly and the use of subsets as an efficient alternative to screening entire compound collections has been investigated. Subsets may be selected on the basis of chemical diversity, molecular properties, biological activity diversity or biological target focus. Previously, we described a novel form of subset screening: plate-based diversity subset (PBDS) screening, in which the screening subset is constructed by plate selection (rather than individual compound cherry-picking), using algorithms that select for compound quality and chemical diversity on a plate basis. In this paper, we describe a second-generation approach to the construction of an updated subset: PBDS2, using both plate and individual compound selection, that has an improved coverage of the chemical space of the screening file, whilst only selecting the same number of plates for screening. We describe the validation of PBDS2 and its successful use in hit and lead discovery. PBDS2 screening became the default mode of singleton (one compound per well) HTS for lead discovery in Pfizer. Electronic supplementary material The online version of this article (doi:10.1007/s11030-016-9692-9) contains supplementary material, which is available to authorized users.

Given the large amounts of screening data now available, empirical methods derived from matched-molecular pairs are being used as a means for suggesting bioisosteric replacements to the medicinal chemist. The pairwise analysis of compounds has been extended to the pairwise analysis of series to bring further context to these suggestions. A validation dataset derived from recent literature has been used to demonstrate that, given a series of active compounds, this approach would be expected to predict a more potent compound, if it exists, in around 46% of cases. The approach has been successfully applied to a series of TRPA1 antagonists.

The V1a receptor has emerged as an attractive target for a range of indications including Raynaud's disease and dysmenorrhoea. As part of an effort to discover a new class of orally active V1a antagonist, we optimised a highly lipophilic, metabolically unstable lead into a range of potent, selective and metabolically stable V1a antagonists. In this communication, we demonstrate the series-dependent effect of limiting the number of rotatable bonds in order to decrease Cytochrome P450-mediated metabolism. This effort culminated in the discovery of PF-184563, a novel, selective V1a antagonist with excellent in vitro and in vivo properties.

This review highlights the medicinal and synthetic chemistry relevance of replacing an aromatic chloride motif with an aromatic nitrile. We explore the desirable features that this transformation can bring in a drug design sense and the recent synthetic chemistry advances that effect this replacement in a single step.

The postprocessing of high-throughput screening (HTS) results is complicated by the occurrence of false positives (inactive compounds misidentified as active by the primary screen) and false negatives (active compounds misidentified as inactive by the primary screen). An activity cutoff is frequently used to select "active" compounds from HTS data; however, this approach is insensitive to both false positives and false negatives. An alternative method that can minimize the occurrence of these artifacts will increase the efficiency of hit selection and therefore lead discovery. In this work, rather than merely using the activity of a given compound, we look at the presence and absence of activity among all compounds in its "chemical space neighborhood" to give a degree of confidence in its activity. We demonstrate that this local hit rate (LHR) analysis method outperforms hit selection based on ranking by primary screen activity values across ten diverse high throughput screens, spanning both cell-based and biochemical assay formats of varying biology and robustness. On average, the local hit rate analysis method was approximately 2.3-fold and approximately 1.3-fold more effective in identifying active compounds and active chemical series, respectively, than selection based on primary activity alone. Moreover, when applied to finding false negatives, this method was 2.3-fold better than ranking by primary activity alone. In most cases, novel hit series were identified that would have otherwise been missed. Additional uses of and observations regarding this HTS analysis approach are also discussed.

Succinyl hydroxamates 1 and 2 are disclosed as novel series of potent and selective inhibitors of procollagen C-proteinase (PCP) which may have potential as anti-fibrotic agents. Carboxamide 7 demonstrated good PCP inhibition and had excellent selectivity over MMPs involved in wound healing. In addition, 7 was effective in a cell-based model of collagen deposition (fibroplasia model) and was very effective at penetrating human skin in vitro. Compound 7 (UK-383,367) was selected as a candidate for evaluation in clinical studies as a topically applied, dermal anti-scarring agent.

The structure-activity relationship and the synthesis of novel N-benzyl-N-(pyrrolidin-3-yl)carboxamides as dual serotonin (5-HT) and noradrenaline (NA) monoamine reuptake inhibitors are described. Compounds such as 18 exhibited dual 5-HT and NA reuptake inhibition, good selectivity over dopamine (DA) reuptake inhibition and drug-like physicochemical properties consistent with CNS target space. Compound 18 was selected for further preclinical evaluation.

Visceral leishmaniasis is a severe parasitic disease that is one of the most neglected tropical diseases. Treatment options are limited and there is an urgent need for new therapeutic agents. Following an HTS campaign and hit optimization, a novel series of amino-pyrazole ureas has been identified with potent in vitro antileishmanial activity. Furthermore, compound 26 shows high levels of in vivo efficacy (>90%) against Leishmania infantum, thus demonstrating proof of concept for this series

Modern methods in genomics and high-throughput crystallography have ensured that we have access to a large and rapidly increasing, number of X-ray structures of protein-ligand complexes. A structure-based approach to drug design aims to exploit this information, but current methods are not suited to the examination of the large numbers of complexes available. We present computational tools that analyse and display multiple protein-ligand interactions and their properties in a simplified way. We illustrate how a novel binding-mode similarity metric is able to cluster 20 ligands complexed to HIV-1 reverse transcriptase into distinct groups. The properties of each cluster are then projected onto a group surface as a series of color gradients. Analysis of these surfaces reveals fundamental similarities and differences in the binding modes of these diverse compounds. In addition, the simplicity of the surface representations facilitates the transfer of information between the crystallographer, computational chemist and the chemist. We also show how two- and three-dimensional (2- and 3-D) similarities can be combined to provide enhanced understanding of 33 factor Xa inhibitor complexes. This methodology has enabled us to identify pharmaceutically relevant relationships between ligands and their binding modes that had previously been hidden in a wealth of data.

New molecular modeling tools were developed to construct a qualitative pharmacophore model for histamine H3 receptor antagonists. The program SLATE superposes ligands assuming optimum hydrogen bond geometry. One or two ligands are allowed to flex in the procedure, thereby enabling the determination of the bioactive conformation of flexible H3 antagonists. In the derived model, four hydrogen-bonding site points and two hydrophobic pockets available for binding antagonists are revealed. The model results in a better understanding of the structure-activity relationships of H3 antagonists. To validate the model, a series of new antagonists was synthesized. The compounds were designed to interact with all four hydrogen-bonding site points and the two hydrophobic pockets simultaneously. These ligands have high H3 receptor affinity, thereby illustrating how the model can be used in the design of new classes of H3 antagonists.

A novel program for the superposition of flexible molecules, slate, is presented. It uses simulated annealing to minimise the difference between the distance matrices calculated from the hydrogen-bonding and aromatic-ring properties of two ligands. A method for generating a molecular stack using multiple pairwise matches is illustrated. These stacks are used by the program doh to predict the relative positions of receptor atoms that could form hydrogen bonds to two or more ligands in the dataset. The methodology has been applied to ligands binding to dihydrofolate reductase, thermolysin, H3 histamine receptors, α2 adrenoceptors and 5-HT1D receptors. When there are sufficient numbers and diversity of molecules in the dataset, the prediction of receptor-atom positions is applicable to compound design.

Hydrogen bonds are the most specific, and therefore predictable of the intermolecular interactions involved in ligand-protein binding. Given the structure of a molecule, it is possible to estimate the positions at which complementary hydrogen-bonding atoms could be found. Crystal-survey data are used in the design of a program, HBMAP, that generates a hydrogen-bond map for any given ligand, which contains all the feasible positions at which a complementary atom could be found. On superposition of ligands, the overlapping regions of their maps represent positions of receptor atoms to which each molecule can bind. The certainty of these positions is increased by the incorporation of a larger number and diversity of molecules. In this work, superposition is achieved using the program HBMATCH, which uses simulated annealing to generate the correspondence between points from the hydrogen-bonding maps of the two molecules. Equivalent matches are distinguished on the basis of their steric similarity. The strategy is tested on a number of ligands for which ligand-protein complexes have been solved crystallographically, which allows validation of the techniques. The receptor atom positions of thermolysin are successfully predicted when the correct superposition is obtained.

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 there-fore 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.

The screening files of many large companies, including Pfizer, have grown considerably due to internal chemistry efforts, company mergers and acquisitions, external contracted synthesis, or compound purchase schemes. In order to screen the targets of interest in a cost-effective fashion, we devised an easy-to-assemble, plate-based diversity subset (PBDS) that represents almost the entire computed chemical space of the screening file whilst comprising only a fraction of the plates in the collection. In order to create this file, we developed new design principles for the quality assessment of screening plates: the Rule of 40 (Ro40) and a plate selection process that insured excellent coverage of both library chemistry and legacy chemistry space. This paper describes the rationale, design, construction, and performance of the PBDS, that has evolved into the standard paradigm for singleton (one compound per well) high-throughput screening in Pfizer since its introduction in 2006.

Steric complementarity is a prerequisite for ligand-receptor recognition; this implies that drugs with a common receptor binding site should possess sterically similar binding surfaces. This principle is used as the basis for an automatic and unbiased method that superposes molecules. One molecule is rotated and translated to maximize the overlap between the two molecular surface volumes. A fast grid-based method is used to determine the extent of this overlap, and this is optimized using simulated annealing. Matches with high steric similarity scores are then sorted on the basis of both hydrogen-bond and electrostatic similarity between the matched molecules. Flexible molecules are treated as a set of rigid representative conformers. The algorithm has correctly predicted superpositions between a number of paris of molecules, according to crystallographic data from ligands that have been co-crystallized at common enzyme binding sites.

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., Author Summary 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 (HsNMT1 and HsNMT2) and for broad-spectrum anti-protozoan activity against the NMT from Trypanosoma brucei. We have identified eight series of protozoan NMT inhibitors, six having good selectivity for either Plasmodium or Leishmania NMTs over the other orthologues in this study. We believe that all of these series could form the basis of medicinal chemistry programs to deliver drug candidates against either malaria or leishmaniasis. Our screening initiative is another example of how a tripartite partnership involving pharmaceutical industries, academic institutions and governmental/non-governmental organisations such as the UK Medical Research Council and Wellcome Trust can stimulate research for neglected diseases.

This review highlights the medicinal and synthetic chemistry relevance of replacing an aromatic chloride motif with an aromatic nitrile. We explore the desirable features that this transformation can bring in a drug design sense and the recent synthetic chemistry advances that effect this replacement in a single step.

Background Trypanosoma brucei, the causative agent of Human African Trypanosomiasis (HAT), expresses two proteins with homology to human glycogen synthase kinase 3β (HsGSK-3) designated TbruGSK-3 short and TbruGSK-3 long. TbruGSK-3 short has previously been validated as a potential drug target and since this enzyme has also been pursued as a human drug target, a large number of inhibitors are available for screening against the parasite enzyme. A collaborative industrial/academic partnership facilitated by the World Health Organisation Tropical Diseases Research division (WHO TDR) was initiated to stimulate research aimed at identifying new drugs for treating HAT. Methodology/Principal Findings A subset of over 16,000 inhibitors of HsGSK-3 β from the Pfizer compound collection was screened against the shorter of two orthologues of TbruGSK-3. The resulting active compounds were tested for selectivity versus HsGSK-3β and a panel of human kinases, as well as in vitro anti-trypanosomal activity. Structural analysis of the human and trypanosomal enzymes was also performed. Conclusions/Significance We identified potent and selective compounds representing potential attractive starting points for a drug discovery program. Structural analysis of the human and trypanosomal enzymes also revealed hypotheses for further improving selectivity of the compounds., Author Summary Over 60 million people in sub-Saharan Africa are at risk of infection with the parasite Trypanosoma brucei which causes Human African Trypanosomiasis (HAT), also known as sleeping sickness. The disease results in systemic and neurological disability to its victims. At present, only four drugs are available for treatment of HAT. However, these drugs are expensive, limited in efficacy and are severely toxic, hence the need to develop new therapies. Previously, the short TbruGSK-3 short has been validated as a potential target for developing new drugs against HAT. Because this enzyme has also been pursued as a drug target for other diseases, several inhibitors are available for screening against the parasite enzyme. Here we present the results of screening over 16,000 inhibitors of human GSK-3β (HsGSK-3) from the Pfizer compound collection against TbruGSK-3 short. The resulting active compounds were tested for selectivity versus HsGSK-3β and a panel of human kinases, as well as their ability to inhibit proliferation of the parasite in vitro. We have identified attractive compounds that now form potential starting points for drug discovery against HAT. This is an example of how a tripartite partnership involving pharmaceutical industries, academic institutions and non-government organisations such as WHO TDR, can stimulate research for neglected diseases.

Fragment Based Drug Discovery (FBDD) continues to advance as an efficient and alternative screening paradigm for the identification and optimization of novel chemical matter. To enable FBDD across a wide range of pharmaceutical targets, a fragment screening library is required to be chemically diverse and synthetically expandable to enable critical decision making for chemical follow-up and assessing new target druggability. In this manuscript, the Pfizer fragment library design strategy which utilized multiple and orthogonal metrics to incorporate structure, pharmacophore and pharmacological space diversity is described. Appropriate measures of molecular complexity were also employed to maximize the probability of detection of fragment hits using a variety of biophysical and biochemical screening methods. In addition, structural integrity, purity, solubility, fragment and analog availability as well as cost were important considerations in the selection process. Preliminary analysis of primary screening results for 13 targets using NMR Saturation Transfer Difference (STD) indicates the identification of uM–mM hits and the uniqueness of hits at weak binding affinities for these targets.

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.

Our efforts to reduce overall lipophilicity and increase ligand-lipophilicity efficiency (LLE) by modification of the 3- and 5-substituents of pyrazole 1, a novel non-nucleoside HIV reverse transcriptase inhibitor (NNRTI) prototype were unsuccessful. In contrast replacement of the substituted benzyl group with corresponding phenylthio or phenoxy groups resulted in marked improvements in potency, ligand efficiency (LE) and LLE.

Succinyl hydroxamates 1 and 2 are disclosed as novel series of potent and selective inhibitors of procollagen C-proteinase (PCP) which may have potential as anti-fibrotic agents. Carboxamide 7 demonstrated good PCP inhibition and had excellent selectivity over MMPs involved in wound healing. In addition, 7 was effective in a cell-based model of collagen deposition (fibroplasia model) and was very effective at penetrating human skin in vitro. Compound 7 (UK-383,367) was selected as a candidate for evaluation in clinical studies as a topically applied, dermal anti-scarring agent.

The G protein–coupled chemokine (C‐C motif) receptor, CCR5, was originally characterized as a protein responding functionally to a number of CC chemokines. As with chemokine receptors in general, studies indicate that CCR5 plays a role in inflammatory responses to infection, although its exact role in normal immune function is not completely defined. The vast majority of research into CCR5 has been focused on its role as an essential and predominant coreceptor for HIV‐1 entry into host immune cells. Discovery of this role was prompted by the elucidation that individuals homozygous for a 32 bp deletion in the CCR5 gene do not express the receptor at the cell surface, and as a consequence, are remarkably resistant to HIV‐1 infection, and apparently possess no other clear phenotype. Multiple studies followed with the ultimate aim of identifying drugs that functionally and physically blocked CCR5 to prevent HIV‐1 entry, and thus provide a completely new approach to treating infection and AIDS, the world's biggest infectious disease killer. To this end, functional antagonists with potent anti–HIV‐1 activity have been discovered, as best exemplified by maraviroc, the first new oral drug for the treatment of HIV‐1 infection in 10 years. In this chapter, the specific methods used to characterize CCR5 primary pharmacology and apply the data generated to enable drug discovery, notably maraviroc, for the treatment of HIV infection and potentially inflammatory‐based indications, are described.

SMYD3 (Set and Mynd Domain containing 3) is a lysine methyltransferase overexpressed in several cancer types including breast, prostrate, pancreatic, and lung, and this overexpression is associated with poor clinical prognosis. Genetic knockdown of SMYD3 by shRNA has been shown to decrease proliferation in a range of cancer cell lines suggesting that inhibition of SMYD3 may have therapeutic utility. In this presentation we describe the discovery and optimization of a novel series of oxindole sulfonamides and sulfamides with SMYD3 inhibitory activity. One of these compounds, EPZ030456, has a SMYD3 biochemical IC50 of 4 nM and is active in cells with an IC50 of 48 nM in a trimethyl MAP3K2 (MEKK2) in-cell western (ICW) assay. The crystal structure of this compound was solved with SMYD3 and the nucleotide substrate, S-adenosylmethionine and shows the oxindole portion of the molecule extends into the SMYD3 lysine binding channel. EPZ030456 shows < 30% inhibition at a 10 uM screening concentration against 17 histone methyltransferase targets tested, including SMYD2. Further optimization within the series resulted in EPZ031686 which has similar potency to EPZ030456 with a biochemical IC50 of 3 nM and an ICW IC50 of 36 nM and in addition exhibits good bioavailability following oral dosing in mice. Hence, EPZ031686 is a suitable tool to study the role of SMYD3 in cancer and other therapeutic areas, using both in vitro and in vivo models. Citation Format: Lorna H. Mitchell, Paula A. Boriack-Sjodin, Sherri Smith, Michael Thomenius, Nathalie Rioux, Michael Munchhof, James E. Mills, Christine Klaus, Jennifer Totman, Thomas V. Riera, Alejandra Raimondi, Suzanne L. Jacques, Megan Foley, Nigel J. Waters, Kevin W. Kuntz, Tim J. Wigle, Margaret Porter Scott, Robert A. Copeland, Jesse J. Smith, Richard Chesworth. Identification of a novel potent selective SMYD3 inhibitor with oral bioavailability. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr C85.

When the structure of a binding site is unknown, information is derived from the ligands known to bind there, which requires accurate ligand superposition, determined by the correct binding conformations. A novel program, SLATE, superposes ligands using a single point to represent each H-bonding group. The method is rapid enough to allow both of the ligands to flex during the superposition. SLATE is tested on thermolysin and α2-adrenoceptor ligands.

De novo drug design utilises site H-bonding atoms as anchor points to be spanned by a ligand. A problem frequently encountered is the need to select a subset of these points for use by the ligand. For example, there are 44 H-bonding regions in the HIV-protease binding cavity so if 5 points were required, there would be over 106 possible selections. H-bonding hotspots are positions of ligand atoms that could simultaneously form H-bonds to more than one atom on the receptor. There are fewer hotspots than site atoms, so they could provide a solution to the combinatorial selection problem. A method for hotspot calculation (HOTSPOT) is presented and tested with HIV-protease and a wide variety of other PDB complexes.