Molecular Dynamics Simulations of Bromodomains Reveal Binding-Site Flexibility and Multiple Binding Modes of the Natural Ligand Acetyl-Lysine

Integrated Anchored Stapling and Hierarchical Dynamics: MSICDA-Driven CREBBP Bromodomain Inhibition

Despite recent success in the computational approaches of cyclic peptide design, current studies face challenges in modeling noncanonical amino acids and nonstandard cyclizations due to limited data. To address this challenge, we developed an integrated framework for the tailored design of stapled peptides (SPs) targeting the bromodomain of CREBBP (CREBBP-BrD). We introduce a powerful combination of anchored stapling and hierarchical molecular dynamics to design and optimize SPs by employing the MultiScale integrative conformational dynamics assessment (MSICDA) strategy, which involves an initial virtual screening of over 1.5 million SPs, followed by comprehensive simulations amounting to 154.54 μs across 5418 of instances. The MSICDA method provides a detailed and holistic stability view of peptide-protein interactions, systematically isolated optimized peptides and identified two leading candidates, DA#430 and DA#99409, characterized by their enhanced stability, optimized binding, and high affinity toward the CREBBP-BrD. In cell-free assays, DA#430 and DA#99409 exhibited 2- to 12-fold greater potency than inhibitor SGC-CBP30. Cell studies revealed higher peptide selectivity for cancerous versus normal cells over small molecules. DA#430 combined with (+)-JQ-1 showed promising synergistic effects. Our approach enables the identification of peptides with optimized binding, high affinity, and enhanced stability, leading to more precise and effective cyclic peptide design, thereby establishing MSICDA as a generalizable and transformative tool for uncovering novel targeted drug development in various therapeutic areas.

An Updated Review on Developing Small Molecule Kinase Inhibitors Using Computer-Aided Drug Design Approaches

Small molecule kinase inhibitors (SMKIs) are of heightened interest in the field of drug research and development. There are 79 (as of July 2023) small molecule kinase inhibitors that have been approved by the FDA and hundreds of kinase inhibitor candidates in clinical trials that have shed light on the treatment of some major diseases. As an important strategy in drug design, computer-aided drug design (CADD) plays an indispensable role in the discovery of SMKIs. CADD methods such as docking, molecular dynamic, quantum mechanics/molecular mechanics, pharmacophore, virtual screening, and quantitative structure-activity relationship have been applied to the design and optimization of small molecule kinase inhibitors. In this review, we provide an overview of recent advances in CADD and SMKIs and the application of CADD in the discovery of SMKIs.

Dynamics of the Histone Acetyltransferase Lysine-Rich Loop in the Catalytic Core of the CREB-Binding Protein

The tight control of transcriptional coactivators is a fundamental aspect of gene expression in cells. The regulation of the CREB-binding protein (CBP) and p300 coactivators, two paralog multidomain proteins, involves an autoinhibitory loop (AIL) of the histone acetyltransferase (HAT) domain. There is experimental evidence for the AIL engaging with the HAT binding site, thus interrupting the acetylation of histone tails or other proteins. Both CBP and p300 contain a domain of about 110 residues (called the bromodomain) that recognizes histone tails with one or more acetylated lysine side chains. Here, we investigate by molecular dynamics simulations whether the AIL of CBP (residues 1556-1618) acetylated at the side chain of Lys1595 can bind to the bromodomain. The structural instability and fast unbinding kinetics of the AIL from the bromodomain pocket suggest that the AIL is not a ligand of the bromodomain on the same protein chain. This is further supported by the absence of strong and persistent contacts at the binding interface. Furthermore, the simulations of unbinding show an initial fast detachment of the acetylated lysine and a slower phase necessary for complete AIL dissociation. We provide further evidence for the instability of the AIL intramolecular binding by comparison with a natural ligand, the histone peptide H3K56ac, which shows higher stability in the pocket.

In silico design and molecular basis for the selectivity of Olinone toward the first over the second bromodomain of BRD4

Bromodomains (BrDs), a conserved structural module in chromatin-associated proteins, are well known for recognizing ε-N-acetyl lysine residues on histones. One of the most relevant BrDs is BRD4, a tandem BrD containing protein (BrD1 and BrD2) that plays a critical role in numerous diseases including cancer. Growing evidence shows that the two BrDs of BRD4 have different biological functions; hence selective ligands that can be used to study their functions are of great interest. Here, as a follow-up of our previous work, we first provide a detailed characterization study of the in silico rational design of Olinone as part of a series of five tetrahydropyrido indole-based compounds as BRD4 BrD1 inhibitors. Additionally, we investigated the molecular basis for Olinone's selective recognition by BrD1 over BrD2. Molecular dynamics simulations, free energy calculations, and conformational analyses of the apo-BRD4-BrD1|2 and BRD4-BrD1|2/Olinone complexes showed that Olinone's selectivity is facilitated by five key residues: Leu92 in BrD1|385 in BrD2 of ZA loop, Asn140|433, Asp144|His437 and Asp145|Glu438 of BC loop, and Ile146|Val49 of helix C. Furthermore, the difference in hydrogen bonds number and in mobility of the ZA and BC loops of the acetyl-lysine binding site between BRD4 BrD1/Olinone and BrD2/Olinone complexes also contribute to the difference in Olinone's binding affinity and selectivity toward BrD1 over BrD2. Altogether, our computer-aided molecular design techniques can effectively guide the development of small-molecule BRD4 BrD1 inhibitors, explain their selectivity origin, and further open doors to the design of new therapeutically improved derivatives.

Cheminformatics Explorations of Natural Products

The chemistry of natural products is fascinating and has continuously attracted the attention of the scientific community for many reasons including, but not limited to, biosynthesis pathways, chemical diversity, the source of bioactive compounds and their marked impact on drug discovery. There is a broad range of experimental and computational techniques (molecular modeling and cheminformatics) that have evolved over the years and have assisted the investigation of natural products. Herein, we discuss cheminformatics strategies to explore the chemistry and applications of natural products. Since the potential synergisms between cheminformatics and natural products are vast, we will focus on three major aspects: (1) exploration of the chemical space of natural products to identify bioactive compounds, with emphasis on drug discovery; (2) assessment of the toxicity profile of natural products; and (3) diversity analysis of natural product collections and the design of chemical collections inspired by natural sources.

Focused conformational sampling in proteins

A detailed understanding of the conformational dynamics of biological molecules is difficult to obtain by experimental techniques due to resolution limitations in both time and space. Computer simulations avoid these in theory but are often too short to sample rare events reliably. Here we show that the progress index-guided sampling (PIGS) protocol can be used to enhance the sampling of rare events in selected parts of biomolecules without perturbing the remainder of the system. The method is very easy to use as it only requires as essential input a set of several features representing the parts of interest sufficiently. In this feature space, new states are discovered by spontaneous fluctuations alone and in unsupervised fashion. Because there are no energetic biases acting on phase space variables or projections thereof, the trajectories PIGS generates can be analyzed directly in the framework of transition networks. We demonstrate the possibility and usefulness of such focused explorations of biomolecules with two loops that are part of the binding sites of bromodomains, a family of epigenetic "reader" modules. This real-life application uncovers states that are structurally and kinetically far away from the initial crystallographic structures and are also metastable. Representative conformations are intended to be used in future high-throughput virtual screening campaigns.

Aromatic Rings Commonly Used in Medicinal Chemistry: Force Fields Comparison and Interactions With Water Toward the Design of New Chemical Entities

The identification of lead compounds usually includes a step of chemical diversity generation. Its rationale may be supported by both qualitative (SAR) and quantitative (QSAR) approaches, offering models of the putative ligand-receptor interactions. In both scenarios, our understanding of which interactions functional groups can perform is mostly based on their chemical nature (such as electronegativity, volume, melting point, lipophilicity etc.) instead of their dynamics in aqueous, biological solutions (solvent accessibility, lifetime of hydrogen bonds, solvent structure etc.). As a consequence, it is challenging to predict from 2D structures which functional groups will be able to perform interactions with the target receptor, at which intensity and relative abundance in the biological environment, all of which will contribute to ligand potency and intrinsic activity. With this in mind, the aim of this work is to assess properties of aromatic rings, commonly used for drug design, in aqueous solution through molecular dynamics simulations in order to characterize their chemical features and infer their impact in complexation dynamics. For this, common aromatic and heteroaromatic rings were selected and received new atomic charge set based on the direction and module of the dipole moment from MP2/6-31G^* calculations, while other topological terms were taken from GROMOS53A6 force field. Afterwards, liquid physicochemical properties were simulated for a calibration set composed by nearly 40 molecules and compared to their respective experimental data, in order to validate each topology. Based on the reliance of the employed strategy, we expanded the dataset to more than 100 aromatic rings. Properties in aqueous solution such as solvent accessible surface area, H-bonds availability, H-bonds residence time, and water structure around heteroatoms were calculated for each ring, creating a database of potential interactions, shedding light on features of drugs in biological solutions, on the structural basis for bioisosterism and on the enthalpic/entropic costs for ligand-receptor complexation dynamics.

Chemical Space Expansion of Bromodomain Ligands Guided by in Silico Virtual Couplings (AutoCouple)

Expanding the chemical space and simultaneously ensuring synthetic accessibility is of upmost importance, not only for the discovery of effective binders for novel protein classes but, more importantly, for the development of compounds against hard-to-drug proteins. Here, we present AutoCouple, a de novo approach to computational ligand design focused on the diversity-oriented generation of chemical entities via virtual couplings. In a benchmark application, chemically diverse compounds with low-nanomolar potency for the CBP bromodomain and high selectivity against the BRD4(1) bromodomain were achieved by the synthesis of about 50 derivatives of the original fragment. The binding mode was confirmed by X-ray crystallography, target engagement in cells was demonstrated, and antiproliferative activity was showcased in three cancer cell lines. These results reveal AutoCouple as a useful in silico coupling method to expand the chemical space in hit optimization campaigns resulting in potent, selective, and cell permeable bromodomain ligands.

dMM-PBSA: A New HADDOCK Scoring Function for Protein-Peptide Docking

Molecular-docking programs coupled with suitable scoring functions are now established and very useful tools enabling computational chemists to rapidly screen large chemical databases and thereby to identify promising candidate compounds for further experimental processing. In a broader scenario, predicting binding affinity is one of the most critical and challenging components of computer-aided structure-based drug design. The development of a molecular docking scoring function which in principle could combine both features, namely ranking putative poses and predicting complex affinity, would be of paramount importance. Here, we systematically investigated the performance of the MM-PBSA approach, using two different Poisson-Boltzmann solvers (APBS and DelPhi), in the currently rising field of protein-peptide interactions (PPIs), identifying the correct binding conformations of 19 different protein-peptide complexes and predicting their binding free energies. First, we scored the decoy structures from HADDOCK calculation via the MM-PBSA approach in order to assess the capability of retrieving near-native poses in the best-scoring clusters and of evaluating the corresponding free energies of binding. MM-PBSA behaves well in finding the poses corresponding to the lowest binding free energy, however the built-in HADDOCK score shows a better performance. In order to improve the MM-PBSA-based scoring function, we dampened the MM-PBSA solvation and coulombic terms by 0.2, as proposed in the HADDOCK score and LIE approaches. The new dampened MM-PBSA (dMM-PBSA) outperforms the original MM-PBSA and ranks the decoys structures as the HADDOCK score does. Second, we found a good correlation between the dMM-PBSA and HADDOCK scores for the near-native clusters of each system and the experimental binding energies, respectively. Therefore, we propose a new scoring function, dMM-PBSA, to be used together with the built-in HADDOCK score in the context of protein-peptide docking simulations.

Fragment-Based Design of Selective Nanomolar Ligands of the CREBBP Bromodomain

Novel ligands of the CREBBP bromodomain were identified by fragment-based docking. The in silico discovered hits have been optimized by chemical synthesis into selective nanomolar compounds, thereby preserving the ligand efficiency. The selectivity for the CREBBP bromodomain over other human bromodomain subfamilies has achieved by a benzoate moiety which was predicted by docking to be involved in favorable electrostatic interactions with the Arg1173 side chain, a prediction that could be verified a posteriori by the high-resolution crystal structure of the CREBBP bromodomain in complex with ligand 6 and also by MD simulations (see Xu, M.; Unzue, A.; Dong, J.; Spiliotopoulos, D.; Nevado, C.; Caflisch, A. Discovery of CREBBP bromodomain inhibitors by high-throughput docking and hit optimization guided by molecular dynamics. J. Med. Chem. 2015, DOI: 10.1021/acs.jmedchem.5b00171).

Observed bromodomain flexibility reveals histone peptide- and small molecule ligand-compatible forms of ATAD2

Preventing histone recognition by bromodomains emerges as an attractive therapeutic approach in cancer. Overexpression of ATAD2 (ATPase family AAA domain-containing 2 isoform A) in cancer cells is associated with poor prognosis making the bromodomain of ATAD2 a promising epigenetic therapeutic target. In the development of an in vitro assay and identification of small molecule ligands, we conducted structure-guided studies which revealed a conformationally flexible ATAD2 bromodomain. Structural studies on apo-, peptide-and small molecule-ATAD2 complexes (by co-crystallization) revealed that the bromodomain adopts a 'closed', histone-compatible conformation and a more 'open' ligand-compatible conformation of the binding site respectively. An unexpected conformational change of the conserved asparagine residue plays an important role in driving the peptide-binding conformation remodelling. We also identified dimethylisoxazole-containing ligands as ATAD2 binders which aided in the validation of the in vitro screen and in the analysis of these conformational studies.

Insight into the key interactions of bromodomain inhibitors based on molecular docking, interaction fingerprinting, molecular dynamics and binding free energy calculation

The interaction mechanism of bromodomain inhibitors was investigated using interaction fingerprinting and binding free energy based methods.

High-resolution visualisation of the states and pathways sampled in molecular dynamics simulations

We have recently developed a scalable algorithm for ordering the instantaneous observations of a dynamical system evolving continuously in time. Here, we apply the method to long molecular dynamics trajectories. The procedure requires only a pairwise, geometrical distance as input. Suitable annotations of both structural and kinetic nature reveal the free energy basins visited by biomolecules. The profile is supplemented by a trace of the temporal evolution of the system highlighting the sequence of events. We demonstrate that the resultant SAPPHIRE (States And Pathways Projected with HIgh REsolution) plots provide a comprehensive picture of the thermodynamics and kinetics of complex, molecular systems exhibiting dynamics covering a range of time and length scales. Information on pathways connecting states and the level of recurrence are quickly inferred from the visualisation. The considerable advantages of our approach are speed and resolution: the SAPPHIRE plot is scalable to very large data sets and represents every single snapshot. This minimizes the risk of missing states because of overlap or prior coarse-graining of the data.