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.

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.

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.

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.

Optimal water networks in protein cavities with GAsol and 3D-RISM.

Motivation: Water molecules in protein binding sites play essential roles in biological processes. The popular 3D-RISM prediction method can calculate the solvent density distribution within minutes, but is difficult to convert it into explicit water molecules. Results: We present GAsol, a tool that is capable of finding the network of water molecules that best fits a particular 3D-RISM density distribution in a fast and accurate manner and that outperforms other available tools by finding the globally optimal solution thanks to its genetic algorithm. Availability and implementation: https://github.com/accsc/GAsol. BSD 3-clauses license. Contact: alvaro.x.cortes@gsk.com. Supplementary information: Supplementary data are available at Bioinformatics online.

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/ .

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.

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.

G-protein-coupled receptor dynamics: dimerization and activation models compared with experiment.

Our previously derived models of the active state of the ß2-adrenergic receptor are compared with recently published X-ray crystallographic structures of activated GPCRs (G-protein-coupled receptors). These molecular dynamics-based models using experimental data derived from biophysical experiments on activation were used to restrain the receptor to an active state that gave high enrichment for agonists in virtual screening. The ß2-adrenergic receptor active model and X-ray structures are in good agreement over both the transmembrane region and the orthosteric binding site, although in some regions the active model is more similar to the active rhodopsin X-ray structures. The general features of the microswitches were well reproduced, but with minor differences, partly because of the unexpected X-ray results for the rotamer toggle switch. In addition, most of the interacting residues between the receptor and the G-protein were identified. This analysis of the modelling has also given important additional insight into GPCR dimerization: re-analysis of results on photoaffinity analogues of rhodopsin provided additional evidence that TM4 (transmembrane helix 4) resides at the dimer interface and that ligands such as bivalent ligands may pass between the mobile helices. A comparison, and discussion, is also carried out between the use of implicit and explicit solvent for active-state modelling.

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.

Oral cancer induced TRPV1 sensitization is mediated by PAR2 signaling in primary afferent neurons innervating the cancer microenvironment.

Oral cancer patients report sensitivity to spicy foods and liquids. The mechanism responsible for chemosensitivity induced by oral cancer is not known. We simulate oral cancer-induced chemosensitivity in a xenograft oral cancer mouse model using two-bottle choice drinking and conditioned place aversion assays. An anatomic basis of chemosensitivity is shown in increased expression of TRPV1 in anatomically relevant trigeminal ganglion (TG) neurons in both the xenograft and a carcinogen (4-nitroquinoline 1-oxide)-induced oral cancer mouse models. The percent of retrograde labeled TG neurons that respond to TRPV1 agonist, capsaicin, is increased along with the magnitude of response as measured by calcium influx, in neurons from the cancer models. To address the possible mechanism of TRPV1 sensitivity in tongue afferents, we study the role of PAR2, which can sensitize the TRPV1 channel. We show co-expression of TRPV1 and PAR2 on tongue afferents and using a conditioned place aversion assay, demonstrate that PAR2 mediates oral cancer-induced, TRPV1-evoked sensitivity in an oral cancer mouse model. The findings provide insight into oral cancer-mediated chemosensitivity.

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.

Modeling GPCR active state conformations: the ß(2)-adrenergic receptor.

The recent publication of several G protein-coupled receptor (GPCR) structures has increased the information available for homology modeling inactive class A GPCRs. Moreover, the opsin crystal structure shows some active features. We have therefore combined information from these two sources to generate an extensively validated model of the active conformation of the ß(2)-adrenergic receptor. Experimental information on fully active GPCRs from zinc binding studies, site-directed spin labeling, and other spectroscopic techniques has been used in molecular dynamics simulations. The observed conformational changes reside mainly in transmembrane helix 6 (TM6), with additional small but significant changes in TM5 and TM7. The active model has been validated by manual docking and is in agreement with a large amount of experimental work, including site-directed mutagenesis information. Virtual screening experiments show that the models are selective for ß-adrenergic agonists over other GPCR ligands, for (R)- over (S)-ß-hydroxy agonists and for ß(2)-selective agonists over ß(1)-selective agonists. The virtual screens reproduce interactions similar to those generated by manual docking. The C-terminal peptide from a model of the stimulatory G protein, readily docks into the active model in a similar manner to which the C-terminal peptide from transducin, docks into opsin, as shown in a recent opsin crystal structure. This GPCR-G protein model has been used to explain site-directed mutagenesis data on activation. The agreement with experiment suggests a robust model of an active state of the ß(2)-adrenergic receptor has been produced. The methodology used here should be transferable to modeling the active state of other GPCRs.

Variability of judgments of capacity: experience of capacity evaluators in a study of research consent capacity.

BACKGROUND: Assessment of decision-making capacity is a common and important function of psychiatric consultants. However, the sources of variability in evaluators' judgments have not been well characterized. OBJECTIVE: To examine the degree and potential sources of variability in the categorical capacity judgments of experienced psychiatrists. METHOD: The setting was a study comparing the decision-making capacities of 188 persons with Alzheimer's disease to appoint a research proxy and to consent to two hypothetical randomized controlled trials for dementia (a new drug RCT and a neurosurgical RCT). We compared five experienced consultation psychiatrists' capacity judgments for 555 videotaped capacity interviews. Both quantitative and qualitative data were used. RESULTS: Pair wise kappa statistics ranged from slight agreement (0.17) to substantial agreement (0.64) with group kappa statistics ranging from fair to moderate agreement (0.40 to 0.45) for the psychiatrists' judgments regarding the three capacities. The sources of variability included varying "strictness" among judges, moderate test-retest reliability within judges, the relative novelty of assessing decision-making capacity for research participation decisions, as well as the limitations of the methods used to obtain capacity judgments in the study. DISCUSSION: There is considerable variability in capacity judgments of experienced consultation psychiatrists regarding the capacities to appoint a research proxy and to consent to research. The potential sources of variability identified in this study may provide starting points for more effective training in capacity assessment.

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.

Optimization of a Series of 2,3-Dihydrobenzofurans as Highly Potent, Second Bromodomain (BD2)-Selective, Bromo and Extra-Terminal Domain (BET) Inhibitors.

Herein, a series of 2,3-dihydrobenzofurans have been developed as highly potent bromo and extra-terminal domain (BET) inhibitors with 1000-fold selectivity for the second bromodomain (BD2) over the first bromodomain (BD1). Investment in the development of two orthogonal synthetic routes delivered inhibitors that were potent and selective but had raised in vitro clearance and suboptimal solubility. Insertion of a quaternary center into the 2,3-dihydrobenzofuran core blocked a key site of metabolism and improved the solubility. This led to the development of inhibitor 71 (GSK852): a potent, 1000-fold-selective, highly soluble compound with good in vivo rat and dog pharmacokinetics.

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.

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).

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.