Structure- and Property-Based Optimization of Efficient Pan-Bromodomain and Extra Terminal Inhibitors to Identify Oral and Intravenous Candidate I-BET787.

The bromodomain and extra terminal (BET) family of bromodomain-containing proteins are important epigenetic regulators that elicit their effect through binding histone tail N-acetyl lysine (KAc) post-translational modifications. Recognition of such markers has been implicated in a range of oncology and immune diseases and, as such, small-molecule inhibition of the BET family bromodomain-KAc protein-protein interaction has received significant interest as a therapeutic strategy, with several potential medicines under clinical evaluation. This work describes the structure- and property-based optimization of a ligand and lipophilic efficient pan-BET bromodomain inhibitor series to deliver candidate I-BET787 (70) that demonstrates efficacy in a mouse model of inflammation and suitable properties for both oral and intravenous (IV) administration. This focused two-phase explore-exploit medicinal chemistry effort delivered the candidate molecule in 3 months with less than 100 final compounds synthesized.

Enhancing torsional sampling using fully adaptive simulated tempering.

Enhanced sampling algorithms are indispensable when working with highly disconnected multimodal distributions. An important application of these is the conformational exploration of particular internal degrees of freedom of molecular systems. However, despite the existence of many commonly used enhanced sampling algorithms to explore these internal motions, they often rely on system-dependent parameters, which negatively impact efficiency and reproducibility. Here, we present fully adaptive simulated tempering (FAST), a variation of the irreversible simulated tempering algorithm, which continuously optimizes the number, parameters, and weights of intermediate distributions to achieve maximally fast traversal over a space defined by the change in a predefined thermodynamic control variable such as temperature or an alchemical smoothing parameter. This work builds on a number of previously published methods, such as sequential Monte Carlo, and introduces a novel parameter optimization procedure that can, in principle, be used in any expanded ensemble algorithms. This method is validated by being applied on a number of different molecular systems with high torsional kinetic barriers. We also consider two different soft-core potentials during the interpolation procedure and compare their performance. We conclude that FAST is a highly efficient algorithm, which improves simulation reproducibility and can be successfully used in a variety of settings with the same initial hyperparameters.

Structure-Guided Design of a Domain-Selective Bromodomain and Extra Terminal N-Terminal Bromodomain Chemical Probe.

Small-molecule-mediated disruption of the protein-protein interactions between acetylated histone tails and the tandem bromodomains of the bromodomain and extra-terminal (BET) family of proteins is an important mechanism of action for the potential modulation of immuno-inflammatory and oncology disease. High-quality chemical probes have proven invaluable in elucidating profound BET bromodomain biology, with seminal publications of both pan- and domain-selective BET family bromodomain inhibitors enabling academic and industrial research. To enrich the toolbox of structurally differentiated N-terminal bromodomain (BD1) BET family chemical probes, this work describes an analysis of the GSK BRD4 bromodomain data set through a lipophilic efficiency lens, which enabled identification of a BD1 domain-biased benzimidazole series. Structure-guided growth targeting a key Asp/His BD1/BD2 switch enabled delivery of GSK023, a high-quality chemical probe with 300-1000-fold BET BD1 domain selectivity and a phenotypic cellular fingerprint consistent with BET bromodomain inhibition.

Identification and Optimization of a Ligand-Efficient Benzoazepinone Bromodomain and Extra Terminal (BET) Family Acetyl-Lysine Mimetic into the Oral Candidate Quality Molecule I-BET432.

The bromodomain and extra terminal (BET) family of proteins are an integral part of human epigenome regulation, the dysregulation of which is implicated in multiple oncology and inflammatory diseases. Disrupting the BET family bromodomain acetyl-lysine (KAc) histone protein-protein interaction with small-molecule KAc mimetics has proven to be a disease-relevant mechanism of action, and multiple molecules are currently undergoing oncology clinical trials. This work describes an efficiency analysis of published GSK pan-BET bromodomain inhibitors, which drove a strategic choice to focus on the identification of a ligand-efficient KAc mimetic with the hypothesis that lipophilic efficiency could be drastically improved during optimization. This focus drove the discovery of the highly ligand-efficient and structurally distinct benzoazepinone KAc mimetic. Following crystallography to identify suitable growth vectors, the benzoazepinone core was optimized through an explore-exploit structure-activity relationship (SAR) approach while carefully monitoring lipophilic efficiency to deliver I-BET432 (41) as an oral candidate quality molecule.

Ensemble Simulations and Experimental Free Energy Distributions: Evaluation and Characterization of Isoxazole Amides as SMYD3 Inhibitors.

Optimization of binding affinities for ligands to their target protein is a primary objective in rational drug discovery. Herein, we report on a collaborative study that evaluates various compounds designed to bind to the SET and MYND domain-containing protein 3 (SMYD3). SMYD3 is a histone methyltransferase and plays an important role in transcriptional regulation in cell proliferation, cell cycle, and human carcinogenesis. Experimental measurements using the scintillation proximity assay show that the distributions of binding free energies from a large number of independent measurements exhibit non-normal properties. We use ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent) and TIES (thermodynamic integration with enhanced sampling) protocols to predict the binding free energies and to provide a detailed chemical insight into the nature of ligand-protein binding. Our results show that the 1-trajectory ESMACS protocol works well for the set of ligands studied here. Although one unexplained outlier exists, we obtain excellent statistical ranking across the set of compounds from the ESMACS protocol and good agreement between calculations and experiments for the relative binding free energies from the TIES protocol. ESMACS and TIES are again found to be powerful protocols for the accurate comparison of the binding free energies.

Enhancing Ligand and Protein Sampling Using Sequential Monte Carlo.

The sampling problem is one of the most widely studied topics in computational chemistry. While various methods exist for sampling along a set of reaction coordinates, many require system-dependent hyperparameters to achieve maximum efficiency. In this work, we present an alchemical variation of adaptive sequential Monte Carlo (SMC), an irreversible importance resampling method that is part of a well-studied class of methods that have been used in various applications but have been underexplored in computational biophysics. Afterward, we apply alchemical SMC on a variety of test cases, including torsional rotations of solvated ligands (butene and a terphenyl derivative), translational and rotational movements of protein-bound ligands, and protein side chain rotation coupled to the ligand degrees of freedom (T4-lysozyme, protein tyrosine phosphatase 1B, and transforming growth factor ß). We find that alchemical SMC is an efficient way to explore targeted degrees of freedom and can be applied to a variety of systems using the same hyperparameters to achieve a similar performance. Alchemical SMC is a promising tool for preparatory exploration of systems where long-timescale sampling of the entire system can be traded off against short-timescale sampling of a particular set of degrees of freedom over a population of conformers.

Identification of a Series of N-Methylpyridine-2-carboxamides as Potent and Selective Inhibitors of the Second Bromodomain (BD2) of the Bromo and Extra Terminal Domain (BET) Proteins.

Domain-specific BET bromodomain ligands represent an attractive target for drug discovery with the potential to unlock the therapeutic benefits of antagonizing these proteins without eliciting the toxicological aspects seen with pan-BET inhibitors. While we have reported several distinct classes of BD2 selective compounds, namely, GSK620, GSK549, and GSK046, only GSK046 shows high aqueous solubility. Herein, we describe the lead optimization of a further class of highly soluble compounds based upon a picolinamide chemotype. Focusing on achieving >1000-fold selectivity for BD2 over BD1 ,while retaining favorable physical chemical properties, compound 36 was identified as being 2000-fold selective for BD2 over BD1 (Brd4 data) with >1 mg/mL solubility in FaSSIF media. 36 represents a valuable new in vivo ready molecule for the exploration of the BD2 phenotype.

Fragment-based Scaffold Hopping: Identification of Potent, Selective, and Highly Soluble Bromo and Extra Terminal Domain (BET) Second Bromodomain (BD2) Inhibitors.

The profound efficacy of pan-BET inhibitors is well documented, but these epigenetic agents have shown pharmacology-driven toxicity in oncology clinical trials. The opportunity to identify inhibitors with an improved safety profile by selective targeting of a subset of the eight bromodomains of the BET family has triggered extensive medicinal chemistry efforts. In this article, we disclose the identification of potent and selective drug-like pan-BD2 inhibitors such as pyrazole 23 (GSK809) and furan 24 (GSK743) that were derived from the pyrrole fragment 6. We transpose the key learnings from a previous pyridone series (GSK620 2 as a representative example) to this novel class of inhibitors, which are characterized by significantly improved solubility relative to our previous research.

Discovery of a Highly Selective BET BD2 Inhibitor from a DNA-Encoded Library Technology Screening Hit.

Second-generation bromodomain and extra terminal (BET) inhibitors, which selectively target one of the two bromodomains in the BET proteins, have begun to emerge in the literature. These inhibitors aim to help determine the roles and functions of each domain and assess whether they can demonstrate an improved safety profile in clinical settings compared to pan-BET inhibitors. Herein, we describe the discovery of a novel BET BD2-selective chemotype using a structure-based drug design from a hit identified by DNA-encoded library technologies, showing a structural differentiation from key previously reported greater than 100-fold BD2-selective chemotypes GSK620, GSK046, and ABBV-744. Following a structure-based hypothesis for the selectivity and optimization of the physicochemical properties of the series, we identified 60 (GSK040), an in vitro ready and in vivo capable BET BD2-inhibitor of unprecedented selectivity (5000-fold) against BET BD1, excellent selectivity against other bromodomains, and good physicochemical properties. This novel chemical probe can be added to the toolbox used in the advancement of epigenetics research.

Template-Hopping Approach Leads to Potent, Selective, and Highly Soluble Bromo and Extraterminal Domain (BET) Second Bromodomain (BD2) Inhibitors.

A number of reports have recently been published describing the discovery and optimization of bromo and extraterminal inhibitors which are selective for the second bromodomain (BD2); these include our own work toward GSK046 (3) and GSK620 (5). This paper describes our approach to mitigating the genotoxicity risk of GSK046 by replacement of the acetamide functionality with a heterocyclic ring. This was followed by a template-hopping and hybridization approach, guided by structure-based drug design, to incorporate learnings from other BD2-selective series, optimize the vector for the amide region, and explore the ZA cleft, leading to the identification of potent, selective, and bioavailable compounds 28 (GSK452), 39 (GSK737), and 36 (GSK217).

Sensitivity of Binding Free Energy Calculations to Initial Protein Crystal Structure.

Binding free energy calculations using alchemical free energy (AFE) methods are widely considered to be the most rigorous tool in the computational drug discovery arsenal. Despite this, the calculations suffer from accuracy, precision, and reproducibility issues. In this publication, we perform a high-throughput study of more than a thousand AFE calculations, utilizing over 220 µs of total sampling time, on three different protein systems to investigate the impact of the initial crystal structure on the resulting binding free energy values. We also consider the influence of equilibration time and discover that the initial crystal structure can have a significant effect on free energy values obtained at short timescales that can manifest itself as a free energy difference of more than 1 kcal/mol. At longer timescales, these differences are largely overtaken by important rare events, such as torsional ligand motions, typically resulting in a much higher uncertainty in the obtained values. This work emphasizes the importance of rare event sampling and long-timescale dynamics in free energy calculations even for routinely performed alchemical perturbations. We conclude that an optimal protocol should not only concentrate computational resources on achieving convergence in the alchemical coupling parameter (λ) space but also on longer simulations and multiple repeats.

GSK973 Is an Inhibitor of the Second Bromodomains (BD2s) of the Bromodomain and Extra-Terminal (BET) Family.

Pan-BET inhibitors have shown profound efficacy in a number of in vivo preclinical models and have entered the clinic in oncology trials where adverse events have been reported. These inhibitors interact equipotently with the eight bromodomains of the BET family of proteins. To better understand the contribution of each domain to their efficacy and to improve from their safety profile, selective inhibitors are required. This Letter discloses the profile of GSK973, a highly selective inhibitor of the second bromodomains of the BET proteins that has undergone extensive preclinical in vitro and in vivo characterization.

The Optimization of a Novel, Weak Bromo and Extra Terminal Domain (BET) Bromodomain Fragment Ligand to a Potent and Selective Second Bromodomain (BD2) Inhibitor.

The profound efficacy, yet associated toxicity of pan-BET inhibitors is well documented. The possibility of an ameliorated safety profile driven by significantly selective (>100-fold) inhibition of a subset of the eight bromodomains is enticing, but challenging given the close homology. Herein, we describe the X-ray crystal structure-directed optimization of a novel weak fragment ligand with a pan-second bromodomain (BD2) bias, to potent and highly BD2 selective inhibitors. A template hopping approach, enabled by our parallel research into an orthogonal template (15, GSK046), was the basis for the high selectivity observed. This culminated in two tool molecules, 20 (GSK620) and 56 (GSK549), which showed an anti-inflammatory phenotype in human whole blood, confirming their cellular target engagement. Excellent broad selectivity, developability, and in vivo oral pharmacokinetics characterize these tools, which we hope will be of broad utility to the field of epigenetics research.

ProtoCaller: Robust Automation of Binding Free Energy Calculations.

ProtoCaller is a Python library distributed through Anaconda which automates relative protein-ligand binding free energy calculations in GROMACS. It links a number of popular specialized tools used to perform protein setup and parametrization, such as PDB2PQR, Modeller, and AmberTools. ProtoCaller supports commonly used AMBER force fields with additional cofactor parameters, and AM1-BCC is used to derive ligand charges. ProtoCaller also comes with an extensive PDB parser, an enhanced maximum common substructure algorithm providing improved ligand-ligand mapping, and a light GROMACS wrapper for running multiple molecular dynamics simulations. ProtoCaller is highly relevant to most researchers in the field of biomolecular simulation, allowing a customizable balance between automation and user intervention.

Cocktailed fragment screening by X-ray crystallography of the antibacterial target undecaprenyl pyrophosphate synthase from Acinetobacter baumannii.

Direct soaking of protein crystals with small-molecule fragments grouped into complementary clusters is a useful technique when assessing the potential of a new crystal system to support structure-guided drug discovery. It provides a robustness check prior to any extensive crystal screening, a double check for assay binding cutoffs and structural data for binding pockets that may or may not be picked out in assay measurements. The structural output from this technique for three novel fragment molecules identified to bind to the antibacterial target Acinetobacter baumannii undecaprenyl pyrophosphate synthase are reported, and the different physicochemical requirements of a successful antibiotic are compared with traditional medicines.

Exploring Ligand Stability in Protein Crystal Structures Using Binding Pose Metadynamics.

Identification of correct protein-ligand binding poses is important in structure-based drug design and crucial for the evaluation of protein-ligand binding affinity. Protein-ligand coordinates are commonly obtained from crystallography experiments that provide a static model of an ensemble of conformations. Binding pose metadynamics (BPMD) is an enhanced sampling method that allows for an efficient assessment of ligand stability in solution. Ligand poses that are unstable under the bias of the metadynamics simulation are expected to be infrequently occupied in the energy landscape, thus making minimal contributions to the binding affinity. Here, the robustness of the method is studied using crystal structures with ligands known to be incorrectly modeled, as well as 63 structurally diverse crystal structures with ligand fit to electron density from the Twilight database. Results show that BPMD can successfully differentiate compounds whose binding pose is not supported by the electron density from those with well-defined electron density.

Discovery of a Bromodomain and Extraterminal Inhibitor with a Low Predicted Human Dose through Synergistic Use of Encoded Library Technology and Fragment Screening.

The bromodomain and extraterminal (BET) family of bromodomain-containing proteins are important regulators of the epigenome through their ability to recognize N-acetyl lysine (KAc) post-translational modifications on histone tails. These interactions have been implicated in various disease states and, consequently, disruption of BET-KAc binding has emerged as an attractive therapeutic strategy with a number of small molecule inhibitors now under investigation in the clinic. However, until the utility of these advanced candidates is fully assessed by these trials, there remains scope for the discovery of inhibitors from new chemotypes with alternative physicochemical, pharmacokinetic, and pharmacodynamic profiles. Herein, we describe the discovery of a candidate-quality dimethylpyridone benzimidazole compound which originated from the hybridization of a dimethylphenol benzimidazole series, identified using encoded library technology, with an N-methyl pyridone series identified through fragment screening. Optimization via structure- and property-based design led to I-BET469, which possesses favorable oral pharmacokinetic properties, displays activity in vivo, and is projected to have a low human efficacious dose.

A Perspective on Water Site Prediction Methods for Structure Based Drug Design.

Over the last decade, a number of computational methods have been developed, which attempt to evaluate the thermodynamic properties of individual water molecules at the solute-solvent interface, in order to assess contributions to protein-ligand binding. In some cases, these tools tell us what we already know, e.g. that hydrophobic pockets prefer lipophilic substituents, and in other cases the methods only seem to add clarity when retrospectively applied. Hence we have grappled with how to utilize such approaches to understand non-intuitive results and to generate chemistry ideas that otherwise would not have been developed. Here we provide our perspective on these methods and describe how results have been interpreted and applied. We include examples from GSK and elsewhere that highlight how water methods have been (1) utilized retrospectively to explain non-intuitive structure- activity relationships and (2) applied prospectively for chemistry design. Finally, we discuss where this field of study could lead to maximal impact in drug discovery research.

WONKA and OOMMPPAA: analysis of protein-ligand interaction data to direct structure-based drug design.

In this work, two freely available web-based interactive computational tools that facilitate the analysis and interpretation of protein-ligand interaction data are described. Firstly, WONKA, which assists in uncovering interesting and unusual features (for example residue motions) within ensembles of protein-ligand structures and enables the facile sharing of observations between scientists. Secondly, OOMMPPAA, which incorporates protein-ligand activity data with protein-ligand structural data using three-dimensional matched molecular pairs. OOMMPPAA highlights nuanced structure-activity relationships (SAR) and summarizes available protein-ligand activity data in the protein context. In this paper, the background that led to the development of both tools is described. Their implementation is outlined and their utility using in-house Structural Genomics Consortium (SGC) data sets and openly available data from the PDB and ChEMBL is described. Both tools are freely available to use and download at http://wonka.sgc.ox.ac.uk/WONKA/ and http://oommppaa.sgc.ox.ac.uk/OOMMPPAA/.

OOMMPPAA: a tool to aid directed synthesis by the combined analysis of activity and structural data.

There is an ever increasing resource in terms of both structural information and activity data for many protein targets. In this paper we describe OOMMPPAA, a novel computational tool designed to inform compound design by combining such data. OOMMPPAA uses 3D matched molecular pairs to generate 3D ligand conformations. It then identifies pharmacophoric transformations between pairs of compounds and associates them with their relevant activity changes. OOMMPPAA presents this data in an interactive application providing the user with a visual summary of important interaction regions in the context of the binding site. We present validation of the tool using openly available data for CDK2 and a GlaxoSmithKline data set for a SAM-dependent methyl-transferase. We demonstrate OOMMPPAA's application in optimizing both potency and cell permeability and use OOMMPPAA to highlight nuanced and cross-series SAR. OOMMPPAA is freely available to download at http://oommppaa.sgc.ox.ac.uk/OOMMPPAA/ .