Large-scale analysis of water stability in bromodomain binding pockets with grand canonical Monte Carlo

Lambda-ABF-OPES: Faster Convergence with High Accuracy in Alchemical Free Energy Calculations

Predicting the binding affinity between small molecules and target macromolecules while combining both speed and accuracy is a cornerstone of modern computational drug discovery, which is critical for accelerating therapeutic development. Despite recent progress in molecular dynamics (MD) simulations, such as advanced polarizable force fields and enhanced sampling techniques, estimating absolute binding free energies (ABFEs) remains computationally challenging. To overcome these difficulties, we introduce a highly efficient hybrid methodology that couples the Lambda-adaptive biasing force (Lambda-ABF) scheme with on-the-fly probability enhanced sampling (OPES). This approach achieves up to a 9-fold improvement in sampling efficiency and computational speed compared to the original Lambda-ABF when used in conjunction with the AMOEBA polarizable force field, yielding converged results at a fraction of the cost of standard techniques.

Binding-Site Purification of Actives (B-SPA) Enables Efficient Large-Scale Progression of Fragment Hits by Combining Multi-Step Array Synthesis With HT Crystallography

Fragment approaches are long-established in target-based ligand discovery, yet their full transformative potential lies dormant because progressing the initial weakly binding hits to potency remains a formidable challenge. The only credible progression paradigm involves multiple cycles of costly conventional design-make-test-analyse medicinal chemistry. We propose an alternative approach to fragment elaboration, namely performing large numbers of parallel and diverse automated multiple step reactions, and evaluating the binding of the crude reaction products by high-throughput protein X-ray crystallography. We show it is effective and low-cost to perform, in parallel, large numbers of non-uniform multi-step reactions, because, even without compound purification, crystallography provides a high-quality readout of binding. This can detect low-level binding of weakly active compounds, which the target binding site extracts directly from crude reaction mixtures. In this proof-of-concept study, we have expanded a fragment hit, from a crystal-based screen of the second bromodomain of pleckstrin homology domain-interacting protein (PHIP(2)), using array synthesis on low-cost robotics. We were able to implement 6 independent multi-step reaction routes of up to 5 steps, attempting the synthesis of 1876 diverse expansions, designs entirely driven by synthetic tractability. The expected product was present in 1108 (59%) crude reaction mixtures, detected by liquid chromatography mass spectrometry (LCMS). 22 individual products were resolved in the crystal structures of crude reaction mixtures added to crystals, providing an initial structure activity relationship map. 19 of these showed binding pose stability, while, through binding instability in the remaining 3 products, we could resolve a stereochemical preference for mixtures containing racemic compounds. One compound showed biochemical potency (IC50=34 μM) and affinity (Kd=50 μM) after resynthesis. This approach therefore lends itself to routine fragment progression, if coupled with algorithmically guided compound and reaction design and new formalisms for data analysis.

SMARCA2 protein: Structure, function and perspectives of drug design

SMARCA2 is an ATPase that regulates chromatin structure via ATP pathways, controlling cell division and differentiation. SMARCA2's bromodomain and ATPase domain, crucial for chromatin remodeling and cell regulation, are therapeutic targets in cancer treatment. This review explores the role of SMARCA2 in cancer development by studying its protein structure and physiological functions. It further discusses the roles and distinctions of SMARCA2 and its related family proteins in cancer. Additionally, this article categorizes known SMARCA2 inhibitors into four classes based on their basic structure and examines their structure-activity relationships (SAR). This review outlines the structural mechanisms of SMARCA2 inhibitors, highlighting interactions with specific amino acids. By analyzing the SAR of inhibitors, we propose a tailored inhibitor model for the bromodomain of SMARCA2, emphasizing α, γ-H-bond donors/acceptors, and β-rigid structures as crucial for effective binding. This research provides guidance for the design and optimization of future drugs targeting the SMARCA2 protein.

Modeling Ligand Binding Site Water Networks with Site Identification by Ligand Competitive Saturation: Impact on Ligand Binding Orientations and Relative Binding Affinities

Appropriate treatment of water contributions to protein-ligand interactions is a very challenging problem in the context of adequately determining the number of waters to investigate and undertaking conformational sampling of the ligands, the waters, and the surrounding protein. In the present study, an extension of the Site Identification by Ligand Competitive Saturation-Monte Carlo (SILCS-MC) docking approach is presented that enables the determination of the location of water molecules in the binding pocket and their impact on the predicted ligand binding orientation and affinities. The approach, termed SILCS-WATER, involves MC sampling of the ligand along with explicit water molecules in a binding site followed by selection of a subset of waters within specified energetic and distance cutoffs that contribute to ligand binding and orientation. To allow for convergence of both the water and ligand orientations, SILCS-WATER is based on just the overlap of the ligand and water with the SILCS FragMaps and the interaction energy between the waters and ligand. Results show that the SILCS-WATER methodology can capture important waters and improve ligand binding orientations. For 6 of 10 multiple ligand-protein systems, the method improved relative binding affinity prediction against experimental results, with substantial improvements in five systems, when compared to standard SILCS-MC. Improved reproduction of crystallographic ligand binding orientations is shown to be an indicator of when SILCS-WATER will yield improved binding affinity correlations. The method also identifies waters interacting with ligands that occupy unfavorable locations with respect to the protein whose displacement through the appropriate ligand modifications should improve ligand binding affinity. Results are consistent with the binding affinity being modeled as a ligand-water complex interacting with the protein. The presented approach offers new possibilities in revealing water networks and their contributions to the binding orientation and affinity of a ligand for a protein and is anticipated to be of utility for computer-aided drug design.

Study of Protein Hydration Water with the V4S Structural Index: Focus on Binding Site Description

V4S, a new structural indicator for water specially designed to be suitable for hydration and nanoconfined contexts, has been recently introduced and preliminarily applied for water in contact with self-assembled monolayers and graphene-like systems. This index enabled an accurate detection of defective high local density water molecules (called HDA-like given their structural resemblance with the high-density amorphous ice, HDA). In the present work, we shall apply this new metric to characterize protein hydration water with particular interest in protein binding sites. As a first result, we shall find that protein hydration water has a higher concentration of HDA-like molecular arrangements compared to the bulk. Significantly, we shall show that the concentration of HDA-like molecules sharply decreases beyond the first hydration layer. Finally, we shall also reveal a highly nonuniform spatial distribution of the V4S values for the first hydration shell on the protein surface, where the higher hydrophobicity inherent to the ligand binding site will be evident from an enrichment in HDA-like molecules as compared to the population exhibited by the global protein surface.

Identification of novel bromodomain inhibitors of Trypanosoma cruzi bromodomain factor 2 (TcBDF2) using a fluorescence polarization-based high-throughput assay

Bromodomains are structural folds present in all eukaryotic cells that bind to other proteins recognizing acetylated lysines. Most proteins with bromodomains are part of nuclear complexes that interact with acetylated histone residues and regulate DNA replication, transcription, and repair through chromatin structure remodeling. Bromodomain inhibitors are small molecules that bind to the hydrophobic pocket of bromodomains, interfering with the interaction with acetylated histones. Using a fluorescent probe, we have developed an assay to select inhibitors of the bromodomain factor 2 of Trypanosoma cruzi (TcBDF2) using fluorescence polarization. Initially, a library of 28,251 compounds was screened in an endpoint assay. The top 350-ranked compounds were further analyzed in a dose-response assay. From this analysis, seven compounds were obtained that had not been previously characterized as bromodomain inhibitors. Although these compounds did not exhibit significant trypanocidal activity, all showed bona fide interaction with TcBDF2 with dissociation constants between 1 and 3 µM validating these assays to search for bromodomain inhibitors.

A high-throughput molecular dynamics screening (HTMDS) approach to the design of novel cyclopeptide inhibitors of ATAD2B based on the non-canonical combinatorial library

Cyclic peptides (CPs) are a promising class of drugs because of their high biological activity and specificity. However, the design of CP remains challenging due to their conformational flexibility and difficulties in designing stable binding conformation. Herein, we present a high-throughput MD screening (HTMDS) process for the iterative design of stable CP binders with a combinatorial CP library composed of canonical and non-canonical amino acids. As a proof of concept, we apply our methods to design CP inhibitors for the bromodomain (BrD) of ATAD2B. 698,800 CP candidates with a total of 25,570 ns MD simulations were performed to study the protein-ligand binding interactions. The binding free energies (ΔGbind) estimated by MM/PBSA approach for eight lead CP designs were found to be low. CP-1st.43 was the best CP candidate with an estimated ΔGbind of -28.48 kcal/mol when compared to the standard inhibitor C-38 which has been experimentally validated and shown to exhibit ΔGbind of -17.11 kcal/mol. The major contribution of binding sites for BrD of ATAD2B involved the hydrogen-bonding anchor within the Aly-binding pocket, salt bridging, and hydrogen-bonding mediated stabilization of the ZA loop and BC loop, and the complementary Van der Waals attraction. Our methods demonstrate encouraging results by yielding conformationally stable and high-potential CP binders that should have potential applicability in future CP drug development.Communicated by Ramaswamy H. Sarma.

The application of WaterMap-guided structure-based virtual screening in novel drug discovery

INTRODUCTION

Nowadays, it is widely accepted that water molecules play a key role in binding a ligand to a molecular target. Neglecting water molecules in the process of molecular recognition was the result of several failures of the structure-based drug discovery campaigns. The application of WaterMap, in particular WaterMap-guided molecular docking, enables the reasonably accurate and quick description of the location and energetics of water molecules at the ligand-protein interface.

AREAS COVERED

In this review, the authors shortly discuss the importance of water in drug design and discovery and provide a brief overview of the computational approaches used to predict the solvent-related effects for the purposes of presenting WaterMap in the context of other available techniques and tools. A concise description of WaterMap concept is followed by the presentation of WaterMap-assisted virtual screening literature published between 2013 and 2023.

EXPERT OPINION

In recent years, WaterMap software has been extensively used to support structure-based drug design, in particular structure-based virtual screening. Indeed, it is a useful tool to rescore docking results considering water molecules in the binding pocket. Although WaterMap allows for the consideration of the dynamic behavior of water molecules in the binding site, for best accuracy, its application in conjunction with other techniques such as molecular mechanics-generalized Born surface area of FEP (Free Energy Perturbation) is recommended.

GNE-235: A Lead Compound Selective for the Second Bromodomain of PBRM1

Bromodomains are acetyl-lysine binding modules that are found in different classes of chromatin-interacting proteins. Among these are large chromatin remodeling complexes such as BAF and PBAF (variants of human SWI/SNF). Previous work has identified chemical probes targeting a subset of the bromodomains present in the BAF and PBAF complexes. Selective inhibitors of the individual bromodomains have proven challenging to discover, as the domains are highly similar. Here, elaboration of an aminopyridazine scaffold used previously to develop probes for the bromodomains of SMARCA2, SMARCA4, and the fifth bromodomain of PBRM1 yielded compounds with both potency and unusual selectivity for the second bromodomain of PBRM1. One of these, GNE-235, and its enantiomer control GNE-234 are suggested for initial cellular investigations of the function of the second bromodomain of PBRM1.

Selectivity Mechanism of Pyrrolopyridone Analogues Targeting Bromodomain 2 of Bromodomain-Containing Protein 4 from Molecular Dynamics Simulations

Bromodomain and extra-terminal domain (BET) proteins play an important role in epigenetic regulation and are linked to several diseases; therefore, they are interesting targets. BET has two bromodomains: bromodomain 1 (BD1) and BD2. Selective targeting of BD1 or BD2 may produce different activities and greater effects than pan-BD inhibitors. However, the selective mechanism of the specific core must be studied at the atomic level. This study determined the effectiveness of pyrrolopyridone analogues to selectively inhibit BD2 using a pan-BD inhibitor (ABBV-075) and a selective-BD2 inhibitor (ABBV-744). Molecular dynamics simulations and calculations of binding free energies were used to systematically study the selectivity of BD2 inhibition by the pyrrolopyridone analogues. Overall, the pyrrolopyridone analogue inhibitors targeting BD2 interacted mainly with the following amino acid pairs between bromodomain-containing protein 4 (BRD4)-BD1 and BRD4-BD2 complexes: I146/V439, N140/N433, D144/H437, P82/P375, V87/V380, D88/D381, and Y139/Y432. The pyrrolopyridone analogues targeting BRD4-BD2 were divided into five regions based on selectivity mechanism. These results suggest that the R3 and R5 regions of pyrrolopyridone analogues can be modified to improve the selectivity between BRD4-BD1 and BRD4-BD2. The selectivity of BD2 inhibition by pyrrolopyridone analogues can be used to design novel BD2 inhibitors based on a pyrrolopyridone core.

The role of loop dynamics in the prediction of ligand-protein binding enthalpy

The enthalpic and entropic components of ligand-protein binding free energy reflect the interactions and dynamics between ligand and protein. Despite decades of study, our understanding and hence our ability to predict these individual components remains poor. In recent years, there has been substantial effort and success in the prediction of relative and absolute binding free energies, but the prediction of the enthalpic (and entropic) contributions in biomolecular systems remains challenging. Indeed, it is not even clear what kind of performance in terms of accuracy could currently be obtained for such systems. It is, however, relatively straight-forward to compute the enthalpy of binding. We thus evaluated the performance of absolute enthalpy of binding calculations using molecular dynamics simulation for ten inhibitors against a member of the bromodomain family, BRD4-1, against isothermal titration calorimetry data. Initial calculations, with the AMBER force-field showed good agreement with experiment (R² = 0.60) and surprisingly good accuracy with an average of root-mean-square error (RMSE) = 2.49 kcal mol^-1. Of the ten predictions, three were obvious outliers that were all over-predicted compared to experiment. Analysis of various simulation factors, including parameterization, buffer concentration and conformational dynamics, revealed that the behaviour of a loop (the ZA loop on the periphery of the binding site) strongly dictates the enthalpic prediction. Consistent with previous observations, the loop exists in two distinct conformational states and by considering one or the other or both states, the prediction for the three outliers can be improved dramatically to the point where the R² = 0.95 and the accuracy in terms of RMSE improves to 0.90 kcal mol^-1. However, performance across force-fields is not consistent: if OPLS and CHARMM are used, different outliers are observed and the correlation with the ZA loop behaviour is not recapitulated, likely reflecting parameterization as a confounding problem. The results provide a benchmark standard for future study and comparison.

Accounting for Solvation Correlation Effects on the Thermodynamics of Water Networks in Protein Cavities

Macromolecular recognition and ligand binding are at the core of biological function and drug discovery efforts. Water molecules play a significant role in mediating the protein-ligand interaction, acting as more than just the surrounding medium by affecting the thermodynamics and thus the outcome of the binding process. As individual water contributions are impossible to measure experimentally, a range of computational methods have emerged to identify hydration sites in protein pockets and characterize their energetic contributions for drug discovery applications. Even though several methods model solvation effects explicitly, they focus on determining the stability of specific water sites independently and neglect solvation correlation effects upon replacement of clusters of water molecules, which typically happens in hit-to-lead optimization. In this work, we rigorously determine the conjoint effects of replacing all combinations of water molecules in protein binding pockets through the use of the RE-EDS multistate free-energy method, which combines Hamiltonian replica exchange (RE) and enveloping distribution sampling (EDS). Applications on the small bovine pancreatic trypsin inhibitor and four proteins of the bromodomain family illustrate the extent of solvation correlation effects on water thermodynamics, with the favorability of replacement of the water sites by pharmacophore probes highly dependent on the composition of the water network and the pocket environment. Given the ubiquity of water networks in biologically relevant protein targets, we believe our approach can be helpful for computer-aided drug discovery by providing a pocket-specific and a priori systematic consideration of solvation effects on ligand binding and selectivity.

Water Networks in Complexes between Proteins and FDA-Approved Drugs

Water molecules at protein-ligand interfaces are often of significant pharmaceutical interest, owing in part to the entropy which can be released upon the displacement of an ordered water by a therapeutic compound. Protein structures may not, however, completely resolve all critical bound water molecules, or there may be no experimental data available. As such, predicting the location of water molecules in the absence of a crystal structure is important in the context of rational drug design. Grand canonical Monte Carlo (GCMC) is a computational technique that is gaining popularity for the simulation of buried water sites. In this work, we assess the ability of GCMC to accurately predict water binding locations, using a dataset that we have curated, containing 108 unique structures of complexes between proteins and Food and Drug Administration (FDA)-approved small-molecule drugs. We show that GCMC correctly predicts 81.4% of nonbulk crystallographic water sites to within 1.4 Å. However, our analysis demonstrates that the reported performance of water prediction methods is highly sensitive to the way in which the performance is measured. We also find that crystallographic water sites with more protein/ligand hydrogen bonds and stronger electron density are more reliably predicted by GCMC. An analysis of water networks revealed that more than half of the structures contain at least one ligand-contacting water network. In these cases, displacement of a water site by a ligand modification might yield unexpected results if the larger network is destabilized. Cooperative effects between waters should therefore be explicitly considered in structure-based drug design.

Structural and functional role of invariant water molecules in matrix metalloproteinases: a data-mining approach

Matrix metalloproteinases (MMPs) are a family of zinc-dependent endopeptidases known to degrade extracellular matrix (ECM). Being involved in many biological and physiological processes of tissue remodeling, MMPs play a crucial role in many pathological conditions such as arthritis, cancer, cardiovascular diseases, etc. Typically, MMPs possess a propeptide, a zinc-containing catalytic domain, a hinge region and a hemopexin domain. Based on their structural domain organization and substrates, MMPs are classified into six different classes, viz. collagenases, stromelysins, gelatinases, matrilysins, membrane-type and other MMPs. As per previous studies, a set of invariant water (IW) molecules of MMP-1 (a collagenase) play a significant role in stabilizing their catalytic domain. However, a functional role of IW molecule in other classes of MMPs has not been reported yet. Thus, in this study, IW molecules of MMPs from different classes were located and their plausible role(s) have been assigned. The results suggest that IW molecules anchor the structurally and functionally essential metal ions present in the vicinity of the active site of MMPs. Further, they (in)directly interlink different structural features and bridge the active site metal ions of MMPs. This study provides the key IW molecules that are structurally and functionally relevant to MMPs and hence, in turn, might facilitate the development of potent generalized inhibitor(s) against different classes of MMPs. Communicated by Ramaswamy H. Sarma.

Identification of Histone Peptide Binding Specificity and Small-Molecule Ligands for the TRIM33α and TRIM33β Bromodomains

TRIM33 is a member of the tripartite motif (TRIM) family of proteins, some of which possess E3 ligase activity and are involved in the ubiquitin-dependent degradation of proteins. Four of the TRIM family proteins, TRIM24 (TIF1α), TRIM28 (TIF1β), TRIM33 (TIF1γ) and TRIM66, contain C-terminal plant homeodomain (PHD) and bromodomain (BRD) modules, which bind to methylated lysine (KMe_n) and acetylated lysine (KAc), respectively. Here we investigate the differences between the two isoforms of TRIM33, TRIM33α and TRIM33β, using structural and biophysical approaches. We show that the N1039 residue, which is equivalent to N140 in BRD4(1) and which is conserved in most BRDs, has a different orientation in each isoform. In TRIM33β, this residue coordinates KAc, but this is not the case in TRIM33α. Despite these differences, both isoforms show similar affinities for H3_1-27K18Ac, and bind preferentially to H3_1-27K9Me₃K18Ac. We used this information to develop an AlphaScreen assay, with which we have identified four new ligands for the TRIM33 PHD-BRD cassette. These findings provide fundamental new information regarding which histone marks are recognized by both isoforms of TRIM33 and suggest starting points for the development of chemical probes to investigate the cellular function of TRIM33.

Best practices for constructing, preparing, and evaluating protein-ligand binding affinity benchmarks [Article v0.1]

Free energy calculations are rapidly becoming indispensable in structure-enabled drug discovery programs. As new methods, force fields, and implementations are developed, assessing their expected accuracy on real-world systems (benchmarking) becomes critical to provide users with an assessment of the accuracy expected when these methods are applied within their domain of applicability, and developers with a way to assess the expected impact of new methodologies. These assessments require construction of a benchmark-a set of well-prepared, high quality systems with corresponding experimental measurements designed to ensure the resulting calculations provide a realistic assessment of expected performance when these methods are deployed within their domains of applicability. To date, the community has not yet adopted a common standardized benchmark, and existing benchmark reports suffer from a myriad of issues, including poor data quality, limited statistical power, and statistically deficient analyses, all of which can conspire to produce benchmarks that are poorly predictive of real-world performance. Here, we address these issues by presenting guidelines for (1) curating experimental data to develop meaningful benchmark sets, (2) preparing benchmark inputs according to best practices to facilitate widespread adoption, and (3) analysis of the resulting predictions to enable statistically meaningful comparisons among methods and force fields. We highlight challenges and open questions that remain to be solved in these areas, as well as recommendations for the collection of new datasets that might optimally serve to measure progress as methods become systematically more reliable. Finally, we provide a curated, versioned, open, standardized benchmark set adherent to these standards (PLBenchmarks) and an open source toolkit for implementing standardized best practices assessments (arsenic) for the community to use as a standardized assessment tool. While our main focus is free energy methods based on molecular simulations, these guidelines should prove useful for assessment of the rapidly growing field of machine learning methods for affinity prediction as well.

GNE-064: A Potent, Selective, and Orally Bioavailable Chemical Probe for the Bromodomains of SMARCA2 and SMARCA4 and the Fifth Bromodomain of PBRM1

Bromodomains are acetyllysine recognition domains present in a variety of human proteins. Bromodomains also bind small molecules that compete with acetyllysine, and therefore bromodomains have been targets for drug discovery efforts. Highly potent and selective ligands with good cellular permeability have been proposed as chemical probes for use in exploring the functions of many of the bromodomain proteins. We report here the discovery of a class of such inhibitors targeting the family VIII bromodomains of SMARCA2 (BRM) and SMARCA4 (BRG1), and PBRM1 (polybromo-1) bromodomain 5. We propose one example from this series, GNE-064, as a chemical probe for the bromodomains SMARCA2, SMARCA4, and PBRM1(5) with the potential for in vivo use.

SAMPL7 protein-ligand challenge: A community-wide evaluation of computational methods against fragment screening and pose-prediction

A novel crystallographic fragment screening data set was generated and used in the SAMPL7 challenge for protein-ligands. The SAMPL challenges prospectively assess the predictive power of methods involved in computer-aided drug design. Application of various methods to fragment molecules are now widely used in the search for new drugs. However, there is little in the way of systematic validation specifically for fragment-based approaches. We have performed a large crystallographic high-throughput fragment screen against the therapeutically relevant second bromodomain of the Pleckstrin-homology domain interacting protein (PHIP2) that revealed 52 different fragments bound across 4 distinct sites, 47 of which were bound to the pharmacologically relevant acetylated lysine (Kac) binding site. These data were used to assess computational screening, binding pose prediction and follow-up enumeration. All submissions performed randomly for screening. Pose prediction success rates (defined as less than 2 Å root mean squared deviation against heavy atom crystal positions) ranged between 0 and 25% and only a very few follow-up compounds were deemed viable candidates from a medicinal-chemistry perspective based on a common molecular descriptors analysis. The tight deadlines imposed during the challenge led to a small number of submissions suggesting that the accuracy of rapidly responsive workflows remains limited. In addition, the application of these methods to reproduce crystallographic fragment data still appears to be very challenging. The results show that there is room for improvement in the development of computational tools particularly when applied to fragment-based drug design.

Enhancing Sampling of Water Rehydration on Ligand Binding: A Comparison of Techniques

Water often plays a key role in protein structure, molecular recognition, and mediating protein-ligand interactions. Thus, free energy calculations must adequately sample water motions, which often proves challenging in typical MD simulation time scales. Thus, the accuracy of methods relying on MD simulations ends up limited by slow water sampling. Particularly, as a ligand is removed or modified, bulk water may not have time to fill or rearrange in the binding site. In this work, we focus on several molecular dynamics (MD) simulation-based methods attempting to help rehydrate buried water sites: BLUES, using nonequilibrium candidate Monte Carlo (NCMC); grand, using grand canonical Monte Carlo (GCMC); and normal MD. We assess the accuracy and efficiency of these methods in rehydrating target water sites. We selected a range of systems with varying numbers of waters in the binding site, as well as those where water occupancy is coupled to the identity or binding mode of the ligand. We analyzed the rehydration of buried water sites in binding pockets using both clustering of trajectories and direct analysis of electron density maps. Our results suggest both BLUES and grand enhance water sampling relative to normal MD and grand is more robust than BLUES, but also that water sampling remains a major challenge for all of the methods tested. The lessons we learned for these methods and systems are discussed.

A Structure-based Design Approach for Generating High Affinity BRD4 D1-Selective Chemical Probes

Chemical probes for epigenetic proteins are essential tools for dissecting the molecular mechanisms for gene regulation and therapeutic development. The bromodomain and extra-terminal (BET) proteins are master transcriptional regulators. Despite promising therapeutic targets, selective small molecule inhibitors for a single bromodomain remain an unmet goal due to their high sequence similarity. Here, we address this challenge via a structure-activity relationship study using 1,4,5-trisubstituted imidazoles against the BRD4 N-terminal bromodomain (D1). Leading compounds 26 and 30 have 15 and 18 nM affinity against BRD4 D1 and over 500-fold selectivity against BRD2 D1 and BRD4 D2 via ITC. Broader BET selectivity was confirmed by fluorescence anisotropy, thermal shift, and CETSA. Despite BRD4 engagement, BRD4 D1 inhibition was unable to reduce c-Myc expression at low concentration in multiple myeloma cells. Conversely, for inflammation, IL-8 and chemokine downregulation were observed. These results provide new design rules for selective inhibitors of an individual BET bromodomain.

Discovery of Novel BRD4 Ligand Scaffolds by Automated Navigation of the Fragment Chemical Space

Fragment-based drug discovery (FBDD) is a very effective hit identification method. However, the evolution of fragment hits into suitable leads remains challenging and largely artisanal. Fragment evolution is often scaffold-centric, meaning that its outcome depends crucially on the chemical structure of the starting fragment. Considering that fragment screening libraries cover only a small proportion of the corresponding chemical space, hits should be seen as probes highlighting privileged areas of the chemical space rather than actual starting points. We have developed an automated computational pipeline to mine the chemical space around any specific fragment hit, rapidly finding analogues that share a common interaction motif but are structurally novel and diverse. On a prospective application on the bromodomain-containing protein 4 (BRD4), starting from a known fragment, the platform yields active molecules with nonobvious scaffold changes. The procedure is fast and inexpensive and has the potential to uncover many hidden opportunities in FBDD.

Selectively targeting individual bromodomain: Drug discovery and molecular mechanisms

Bromodomain-containing proteins include bromodomain and extra-terminal (BET) and non-BET families. Due to the conserved bromodomain (BD) module between BD-containing proteins, and especially BETs with each member having two BDs (BD1 and BD2), the high degree of structural similarity makes BD-selective inhibitors much difficult to be designed. However, increasing evidences emphasized that individual BDs had distinct functions and different cellular phenotypes after pharmacological inhibition, and selectively targeting one of the BDs could result in a different efficacy and tolerability profile. This review is to summarize the pioneering progress of BD-selective inhibitors targeting BET and non-BET proteins, focusing on their structural features, biological activity, therapeutic application and experimental/theoretical mechanisms. The present proteolysis targeting chimeras (PROTAC) degraders targeting BDs, and clinical status of BD-selective inhibitors were also analyzed, providing a new insight into future direction of bromodomain-selective drug discovery.

Design and Synthesis of LM146, a Potent Inhibitor of PB1 with an Improved Selectivity Profile over SMARCA2

PB1 is a bromodomain-containing protein hypothesized to act as the nucleosome-recognition subunit of the PBAF complex. Although PB1 is a key component of the PBAF chromatin remodeling complex, its exact role has not been elucidated due to the lack of potent and selective inhibitors. Chemical probes that target specific bromodomains within the complex would constitute highly valuable tools to characterize the function and therapeutic pertinence of PB1 and of each of its bromodomains. Here, we report the design and synthesis of lead compound LM146, which displays strong stabilization of the second and fifth bromodomains of PB1 as shown by DSF. LM146 does not interact with bromodomains outside of sub-family VIII and binds to PB1(2), PB1(5), and SMARCA2B with K _D values of 110, 61, and 2100 nM, respectively, providing a ∼34-fold selectivity profile for PB1(5) over SMARCA2.

Water molecules at protein-drug interfaces: computational prediction and analysis methods

The fundamental importance of water molecules at drug-protein interfaces is now widely recognised and a significant feature in structure-based drug design. Experimental methods for analysing the role of water in drug binding have many challenges, including the accurate location of bound water molecules in crystal structures, and problems in resolving specific water contributions to binding thermodynamics. Computational analyses of binding site water molecules provide an alternative, and in principle complete, structural and thermodynamic picture, and their use is now commonplace in the pharmaceutical industry. In this review, we describe the computational methodologies that are available and discuss their strengths and weaknesses. Additionally, we provide a critical analysis of the experimental data used to validate the methods, regarding the type and quality of experimental structural data. We also discuss some of the fundamental difficulties of each method and suggest directions for future study.

Discovery of a hidden transient state in all bromodomain families

Bromodomains (BDs) are small protein modules that interact with acetylated marks in histones. These posttranslational modifications are pivotal to regulate gene expression, making BDs promising targets to treat several diseases. While the general structure of BDs is well known, their dynamical features and their interplay with other macromolecules are poorly understood, hampering the rational design of potent and selective inhibitors. Here, we combine extensive molecular dynamics simulations, Markov state modeling, and available structural data to reveal a transiently formed state that is conserved across all BD families. It involves the breaking of two backbone hydrogen bonds that anchor the ZA-loop with the αA helix, opening a cryptic pocket that partially occludes the one associated to histone binding. By analyzing more than 1,900 experimental structures, we unveil just two adopting the hidden state, explaining why it has been previously unnoticed and providing direct structural evidence for its existence. Our results suggest that this state is an allosteric regulatory switch for BDs, potentially related to a recently unveiled BD-DNA-binding mode.

Water-mediated structural rearrangement establishes active conformation of caspases for apoptosis and inflammation

Caspases are cysteine-dependent aspartate-specific proteases that play a crucial role in apoptosis (or programmed cell death) and inflammation. Based on their function, caspases are majorly categorized into apoptotic (initiator/apical and effector/executioner) and inflammatory caspases. Caspases undergo transition from an inactive zymogen to an active caspase to accomplish their function. This transition demands structural rearrangements which are most prominent at the active site loops and are imperative for the catalytic activity of caspases. In effector caspase-3, the structural rearrangement in the active site loop is shown to be facilitated by a set of invariant water (IW) molecules. However, the atomic details involving their role in stabilizing the active conformation have not been reported yet. Moreover, it is not known whether water molecules are essential for the active conformation in all caspases. Thus, in this study, we located IW molecules in initiator, effector, and inflammatory caspases to understand their precise role in rendering the structural arrangement of active caspases. Furthermore, IW molecules involved in anchoring the fragments of the protomer and rendering regulated flaccidity to caspases were identified. Location and identification of IW molecules interacting with amino acid residues involved in establishing the active conformation in the caspases might facilitate the design of potent inhibitors during up-regulated caspase activity in neurodegenerative and immune disorders. Communicated by Ramaswamy H. Sarma.

Selective N-Terminal BET Bromodomain Inhibitors by Targeting Non-Conserved Residues and Structured Water Displacement*

Bromodomain and extra-terminal (BET) family proteins, BRD2-4 and T, are important drug targets; however, the biological functions of each bromodomain remain ill-defined. Chemical probes that selectively inhibit a single BET bromodomain are lacking, although pan inhibitors of the first (D1), and second (D2), bromodomain are known. Here, we develop selective BET D1 inhibitors with preferred binding to BRD4 D1. In competitive inhibition assays, we show that our lead compound is 9-33 fold selective for BRD4 D1 over the other BET bromodomains. X-ray crystallography supports a role for the selectivity based on reorganization of a non-conserved lysine and displacement of an additional structured water in the BRD4 D1 binding site relative to our prior lead. Whereas pan-D1 inhibitors displace BRD4 from MYC enhancers, BRD4 D1 inhibition in MM.1S cells is insufficient for stopping Myc expression and may lead to its upregulation. Future analysis of BRD4 D1 gene regulation may shed light on differential BET bromodomain functions.

Pan-SMARCA/PB1 Bromodomain Inhibitors and Their Role in Regulating Adipogenesis

Accessibility of the human genome is modulated by the ATP-driven SWI/SNF chromatin remodeling multiprotein complexes BAF (BRG1/BRM-associated factor) and PBAF (polybromo-associated BAF factor), which involves reading of acetylated histone tails by the bromodomain-containing proteins SMARCA2 (BRM), SMARCA4 (BRG1), and polybromo-1. Dysregulation of chromatin remodeling leads to aberrant cell proliferation and differentiation. Here, we have characterized a set of potent and cell-active bromodomain inhibitors with pan-selectivity for canonical family VIII bromodomains. Targeted SWI/SNF bromodomain inhibition blocked the expression of key genes during adipogenesis, including the transcription factors PPARγ and C/EBPα, and impaired the differentiation of 3T3-L1 murine fibroblasts into adipocytes. Our data highlight the role of SWI/SNF bromodomains in adipogenesis and provide a framework for the development of SWI/SNF bromodomain inhibitors for indirect targeting of key transcription factors regulating cell differentiation.

Comparing Fragment Binding Poses Prediction Using HSP90 as a Key Study: When Bound Water Makes the Difference

Fragment-Based Drug Discovery (FBDD) approaches have gained popularitynot only in industry but also in academic research institutes. However, the computational prediction of the binding mode adopted by fragment-like molecules within a protein binding site is still a very challenging task. One of the most crucial aspects of fragment binding is related to the large amounts of bound waters in the targeted binding pocket. The binding affinity of fragmentsmay not be sufficientto displace the bound water molecules. In the present work, we confirmed the importance of the bound water molecules in the correct prediction of the fragment binding mode. Moreover, we investigate whether the use of methods based on explicit solvent molecular dynamics simulations can improve the accuracy of fragment posing. The protein chosen for this study is HSP-90.

The KDEL trafficking receptor exploits pH to tune the strength of an unusual short hydrogen bond

The endoplasmic reticulum (ER) is the main site of protein synthesis in eukaryotic cells and requires a high concentration of luminal chaperones to function. During protein synthesis, ER luminal chaperones are swept along the secretory pathway and must be retrieved to maintain cell viability. ER protein retrieval is achieved by the KDEL receptor, which recognises a C-terminal Lys-Asp-Glu-Leu (KDEL) sequence. Recognition of ER proteins by the KDEL receptor is pH dependent, with binding occurring under acidic conditions in the Golgi and release under conditions of higher pH in the ER. Recent crystal structures of the KDEL receptor in the apo and peptide bound state suggested that peptide binding drives the formation of a short-hydrogen bond that locks the KDEL sequence in the receptor and activates the receptor for COPI binding in the cytoplasm. Using quantum mechanical calculations we demonstrate that the strength of this short hydrogen bond is reinforced following protonation of a nearby histidine, providing a conceptual link between receptor protonation and KDEL peptide binding. Protonation also controls the water networks adjacent to the peptide binding site, leading to a conformational change that ultimately allows the receptor-complex to be recognized by the COPI system.

Current advances on the development of BET inhibitors: insights from computational methods

Epigenetics was coined almost 70 years ago for the description of heritable phenotype without altering DNA sequences. Research on the field has uncovered significant roles of such mechanisms, that account for the biogenesis of several diseases. Further studies have led the way for drug development which targets epi-enzymes, mainly for cancer treatment. Of the numerous epi-targets involved with histone acetylation, bromodomains have captured the spotlight of drug discovery focused on novel therapies. However, due to high sequence identity, the development of potent and selective inhibitors poses a significant challenge. Herein, we discuss recent computational developments on BET inhibitors and other methods that may be applied for drug discovery in general. As a proof-of-concept, we discuss a virtual screening to identify novel BET inhibitors based on coumarin derivatives. From public data, we identified putative structure-activity relationships of coumarin scaffold and propose R-group modifications for BET selectivity. Results showed that the optimization and design of novel coumarins could be further explored.

Combining Machine Learning and Enhanced Sampling Techniques for Efficient and Accurate Calculation of Absolute Binding Free Energies

Calculating absolute binding free energies is challenging and important. In this paper, we test some recently developed metadynamics-based methods and develop a new combination with a Hamiltonian replica-exchange approach. The methods were tested on 18 chemically diverse ligands with a wide range of different binding affinities to a complex target; namely, human soluble epoxide hydrolase. The results suggest that metadynamics with a funnel-shaped restraint can be used to calculate, in a computationally affordable and relatively accurate way, the absolute binding free energy for small fragments. When used in combination with an optimal pathlike variable obtained using machine learning or with the Hamiltonian replica-exchange algorithm SWISH, this method can achieve reasonably accurate results for increasingly complex ligands, with a good balance of computational cost and speed. An additional benefit of using the combination of metadynamics and SWISH is that it also provides useful information about the role of water in the binding mechanism.

Application of Atypical Acetyl-lysine Methyl Mimetics in the Development of Selective Inhibitors of the Bromodomain-Containing Protein 7 (BRD7)/Bromodomain-Containing Protein 9 (BRD9) Bromodomains

Non-BET bromodomain-containing proteins have become attractive targets for the development of novel therapeutics targeting epigenetic pathways. To help facilitate the target validation of this class of proteins, structurally diverse small-molecule ligands and methodologies to produce selective inhibitors in a predictable fashion are in high demand. Herein, we report the development and application of atypical acetyl-lysine (KAc) methyl mimetics to take advantage of the differential stability of conserved water molecules in the bromodomain binding site. Discovery of the n-butyl group as an atypical KAc methyl mimetic allowed generation of 31 (GSK6776) as a soluble, permeable, and selective BRD7/9 inhibitor from a pyridazinone template. The n-butyl group was then used to enhance the bromodomain selectivity of an existing BRD9 inhibitor and to transform pan-bromodomain inhibitors into BRD7/9 selective compounds. Finally, a solvent-exposed vector was defined from the pyridazinone template to enable bifunctional molecule synthesis, and affinity enrichment chemoproteomic experiments were used to confirm several of the endogenous protein partners of BRD7 and BRD9, which form part of the chromatin remodeling PBAF and BAF complexes, respectively.

Utilizing Grand Canonical Monte Carlo Methods in Drug Discovery

The concepts behind targeting waters for potency and selectivity gains have been well documented and explored, although maximizing such potential gains can prove to be challenging. This problem is exacerbated in cases where there are multiple interacting waters, wherein perturbation of one water can affect the free energy landscape of the remaining waters. Knowing the right modification a priori is challenging, and computational approaches are ideally suited to help answer the key question of which substitution is best to try. Here, we use Grand Canonical Monte Carlo and the recent Grand Canonical Alchemical Perturbation methods to both understand and predict the effect of ligand-mediated water displacement when more than one water molecule is involved, as well as to understand how exploiting water networks can help govern selectivity.

SAR by (Protein-Observed) 19F NMR

Inhibitor discovery for protein-protein interactions has proven difficult due to the large protein surface areas and dynamic interfaces involved. This is particularly the case when targeting transcription-factor-protein interactions. To address this challenge, structural biology approaches for ligand discovery using X-ray crystallography, mass spectrometry, and nuclear magnetic resonance (NMR) spectroscopy have had a significant impact on advancing small molecule inhibitors into the clinic, including the U.S. Food and Drug Administration approved drug, Venetoclax. Inspired by the protein-observed NMR approach using ¹H-¹⁵N-HSQC NMR which detects chemical shift perturbations of ¹⁵N-labeled amides, we have applied a complementary protein-observed ¹⁹F NMR approach using ¹⁹F-labeled side-chains that are enriched at protein-protein-interaction interfaces. This protein-observed ¹⁹F NMR assay is abbreviated PrOF NMR to distinguish the experiment from the more commonly employed ligand-observed ¹⁹F NMR methods. In this Account, we describe our efforts using PrOF NMR as a ligand discovery tool, particularly for fragment-based ligand discovery (FBLD). We metabolically label the aromatic amino acids on proteins due to the enrichment of aromatic residues at protein interfaces. We choose the ¹⁹F nucleus due to its high signal sensitivity and the hyperresponsiveness of ¹⁹F to changes in chemical environment. Simultaneous labeling with two different types of fluorinated aromatic amino acids for PrOF NMR has also been achieved. We first describe the technical aspects of considering the application of PrOF NMR for characterizing native protein-protein interactions and for ligand screening. Several test cases are further described with a focus on a transcription factor coactivator interaction with the KIX domain of CBP/p300 and two epigenetic regulatory domains, the bromodomains of BRD4 and BPTF. Through these case studies, we highlight medicinal chemistry applications in FBLD, selectivity screens, structure-activity relationship (SAR) studies, and ligand deconstruction approaches. These studies have led to the discovery of some of the first inhibitors for BPTF and a novel inhibitor class for the N-terminal bromodomain of BRD4. The speed, ease of interpretation, and relatively low concentration of protein needed for NMR-based binding experiments affords a rapid, structural biology-based method to discover and characterize both native and new ligands for bromodomains, and it may find utility in the study of additional epigenetic proteins and transcription-factor-protein interactions.

Comprehensive evaluation of the MM-GBSA method on bromodomain-inhibitor sets

MM-PB/GBSA methods represent a higher-level scoring theory than docking. This study reports an extensive testing of different MM-GBSA scoring schemes on two bromodomain (BRD) datasets. The first set is composed of 24 BRPF1 complexes, and the second one is a nonredundant set constructed from the PDBbind and composed of 28 diverse BRD complexes. A variety of MM-GBSA schemes were analyzed to evaluate the performance of four protocols with different numbers of minimization and MD steps, 10 different force fields and three different water models. Results showed that neither additional MD steps nor unfixing the receptor atoms improved scoring or ranking power. On the contrary, our results underscore the advantage of fixing receptor atoms or limiting the number of MD steps not only for a reduction in the computational costs but also for boosting the prediction accuracy. Among Amber force fields tested, ff14SB and its derivatives rather than ff94 or polarized force fields provided the most accurate scoring and ranking results. The TIP3P water model yielded the highest scoring and ranking power compared to the others. Posing power was further evaluated for the BRPF1 set. A slightly better posing power for the protocol which uses both minimization and MD steps with a fixed receptor than the one which uses only minimization with a fully flexible receptor-ligand system was observed. Overall, this study provides insights into the usage of the MM-GBSA methods for screening of BRD inhibitors, substantiating the benefits of shorter protocols and latest force fields and maintaining the crystal waters for accuracy.

A Qualified Success: Discovery of a New Series of ATAD2 Bromodomain Inhibitors with a Novel Binding Mode Using High-Throughput Screening and Hit Qualification

The bromodomain of ATAD2 has proved to be one of the least-tractable proteins within this target class. Here, we describe the discovery of a new class of inhibitors by high-throughput screening and show how the difficulties encountered in establishing a screening triage capable of finding progressible hits were overcome by data-driven optimization. Despite the prevalence of nonspecific hits and an exceptionally low progressible hit rate (0.001%), our optimized hit qualification strategy employing orthogonal biophysical methods enabled us to identify a single active series. The compounds have a novel ATAD2 binding mode with noncanonical features including the displacement of all conserved water molecules within the active site and a halogen-bonding interaction. In addition to reporting this new series and preliminary structure-activity relationship, we demonstrate the value of diversity screening to complement the knowledge-based approach used in our previous ATAD2 work. We also exemplify tactics that can increase the chance of success when seeking new chemical starting points for novel and less-tractable targets.

Bromodomains: a new target class for drug development

Less than a decade ago, it was shown that bromodomains, acetyl lysine 'reader' modules found in proteins with varied functions, were highly tractable small-molecule targets. This is an unusual property for protein-protein or protein-peptide interaction domains, and it prompted a wave of chemical probe discovery to understand the biological potential of new agents that targeted bromodomains. The original examples, inhibitors of the bromodomain and extra-terminal (BET) class of bromodomains, showed enticing anti-inflammatory and anticancer activities, and several compounds have since advanced to human clinical trials. Here, we review the current state of BET inhibitor biology in relation to clinical development, and we discuss the next wave of bromodomain inhibitors with clinical potential in oncology and non-oncology indications. The lessons learned from BET inhibitor programmes should affect efforts to develop drugs that target non-BET bromodomains and other epigenetic readers.

A chemical toolbox for the study of bromodomains and epigenetic signaling

Bromodomains (BRDs) are conserved protein interaction modules which recognize (read) acetyl-lysine modifications, however their role(s) in regulating cellular states and their potential as targets for the development of targeted treatment strategies is poorly understood. Here we present a set of 25 chemical probes, selective small molecule inhibitors, covering 29 human bromodomain targets. We comprehensively evaluate the selectivity of this probe-set using BROMOscan and demonstrate the utility of the set identifying roles of BRDs in cellular processes and potential translational applications. For instance, we discovered crosstalk between histone acetylation and the glycolytic pathway resulting in a vulnerability of breast cancer cell lines under conditions of glucose deprivation or GLUT1 inhibition to inhibition of BRPF2/3 BRDs. This chemical probe-set will serve as a resource for future applications in the discovery of new physiological roles of bromodomain proteins in normal and disease states, and as a toolset for bromodomain target validation.

Bromodomains are conserved protein interaction modules that recognize acetyl-lysine modifications. Here the authors present a set of 25 selective small molecule inhibitors covering 29 human bromodomain targets and comprehensively evaluate the selectivity of this probe-set.

Solvents to Fragments to Drugs: MD Applications in Drug Design

Simulations of molecular dynamics (MD) are playing an increasingly important role in structure-based drug discovery (SBDD). Here we review the use of MD for proteins in aqueous solvation, organic/aqueous mixed solvents (MDmix) and with small ligands, to the classic SBDD problems: Binding mode and binding free energy predictions. The simulation of proteins in their condensed state reveals solvent structures and preferential interaction sites (hot spots) on the protein surface. The information provided by water and its cosolvents can be used very effectively to understand protein ligand recognition and to improve the predictive capability of well-established methods such as molecular docking. The application of MD simulations to the study of the association of proteins with drug-like compounds is currently only possible for specific cases, as it remains computationally very expensive and labor intensive. MDmix simulations on the other hand, can be used systematically to address some of the common tasks in SBDD. With the advent of new tools and faster computers we expect to see an increase in the application of mixed solvent MD simulations to a plethora of protein targets to identify new drug candidates.

Ligand Binding Free Energies with Adaptive Water Networks: Two-Dimensional Grand Canonical Alchemical Perturbations

Computational methods to calculate ligand binding affinities are increasing in popularity, due to improvements in simulation algorithms, computational resources, and easy-to-use software. However, issues can arise in relative ligand binding free energy simulations if the ligands considered have different active site water networks, as simulations are typically performed with a predetermined number of water molecules (fixed N ensembles) in preassigned locations. If an alchemical perturbation is attempted where the change should result in a different active site water network, the water molecules may not be able to adapt appropriately within the time scales of the simulations—particularly if the active site is occluded. By combining the grand canonical ensemble (μVT) to sample active site water molecules, with conventional alchemical free energy methods, the water network is able to dynamically adapt to the changing ligand. We refer to this approach as grand canonical alchemical perturbation (GCAP). In this work we demonstrate GCAP for two systems; Scytalone Dehydratase (SD) and Adenosine A_2A receptor. For both systems, GCAP is shown to perform well at reproducing experimental binding affinities. Calculating the relative binding affinities with a naïve, conventional attempt to solvate the active site illustrates how poor results can be if proper consideration of water molecules in occluded pockets is neglected. GCAP results are shown to be consistent with time-consuming double decoupling simulations. In addition, by obtaining the free energy surface for ligand perturbations, as a function of both the free energy coupling parameter and water chemical potential, it is possible to directly deconvolute the binding energetics in terms of protein–ligand direct interactions and protein binding site hydration.

From bench to bedside, via desktop. Recent advances in the application of cutting-edge in silico tools in the research of drugs targeting bromodomain modules

The discipline of drug discovery has greatly benefited by computational tools and in silico algorithms aiming at rationalization of many related processes, from the stage of early hit identification to the preclinical phases of drug candidate validation. The various methodologies referred to as molecular modeling tools span a broad spectrum of applications, from straightforward approaches such as virtual screening of compound libraries to more advanced techniques involving the precise estimation of free energy upon binding of the candidate drug to its macromolecular target. To this end, we report an overview of specific studies where implementation of such sophisticated modeling algorithms has shown to be indispensable for addressing challenging systems and biological questions otherwise difficult to answer. We focus our attention on the emerging field of bromodomain inhibitors. Bromodomains are small modules involved in epigenetic signaling and currently comprise high-priority targets for developing both drug candidates and chemical probes for basic biomedical research. We attempt a critical presentation of selected cases utilizing cutting-edge in silico methodologies, with our main emphasis being on absolute or relative free energy simulations, on implementation of quantum-mechanics level calculations and on characterization of solvent thermodynamics. We discuss the advantages and strengths as well as the drawbacks and weaknesses of computational tools utilized in those works and we attempt to comment on specific issues related to their integration into the regular medicinal chemistry practice. Our conclusion is that while such methods indeed represent highly promising resources for further advancing the discipline, their application is not always trivial.

Molecular Basis for the N-Terminal Bromodomain-and-Extra-Terminal-Family Selectivity of a Dual Kinase-Bromodomain Inhibitor

As regulators of transcription, epigenetic proteins that interpret post-translational modifications to N-terminal histone tails are essential for maintaining cellular homeostasis. When dysregulated, "reader" proteins become drivers of disease. In the case of bromodomains, which recognize N-ε-acetylated lysine, selective inhibition of individual bromodomain-and-extra-terminal (BET)-family bromodomains has proven challenging. We describe the >55-fold N-terminal-BET bromodomain selectivity of 1,4,5-trisubstituted-imidazole dual kinase-bromodomain inhibitors. Selectivity for the BRD4 N-terminal bromodomain (BRD4(1)) over its second bromodomain (BRD4(2)) arises from the displacement of ordered waters and the conformational flexibility of lysine-141 in BRD4(1). Cellular efficacy was demonstrated via reduction of c-Myc expression, inhibition of NF-κB signaling, and suppression of IL-8 production through potential synergistic inhibition of BRD4(1) and p38α. These dual inhibitors provide a new scaffold for domain-selective inhibition of BRD4, the aberrant function of which plays a key role in cancer and inflammatory signaling.