Exploring Cocrystallized Aromatic Cage Binders to Target Histone Methylation Reader Proteins

Exploring Aromatic Cage Flexibility Using Cosolvent Molecular Dynamics Simulations─An In-Silico Case Study of Tudor Domains

Cosolvent molecular dynamics (MD) simulations have proven to be powerful in silico tools to predict hotspots for binding regions on protein surfaces. In the current study, the method was adapted and applied to two Tudor domain-containing proteins, namely Spindlin1 (SPIN1) and survival motor neuron protein (SMN). Tudor domains are characterized by so-called aromatic cages that recognize methylated lysine residues of protein targets. In the study, the conformational transitions from closed to open aromatic cage conformations were investigated by performing MD simulations with cosolvents using six different probe molecules. It is shown that a trajectory clustering approach in combination with volume and atomic distance tracking allows a reasonable discrimination between open and closed aromatic cage conformations and the docking of inhibitors yields very good reproducibility with crystal structures. Cosolvent MDs are suitable to capture the flexibility of aromatic cages and thus represent a promising tool for the optimization of inhibitors.

Trimethyllysine Reader Proteins Exhibit Widespread Charge-Agnostic Binding via Different Mechanisms to Cationic and Neutral Ligands

In the last 40 years, cation-π interactions have become part of the lexicon of noncovalent forces that drive protein binding. Indeed, tetraalkylammoniums are universally bound by aromatic cages in proteins, suggesting that cation-π interactions are a privileged mechanism for binding these ligands. A prominent example is the recognition of histone trimethyllysine (Kme3) by the conserved aromatic cage of reader proteins, dictating gene expression. However, two proteins have recently been suggested as possible exceptions to the conventional understanding of tetraalkylammonium recognition. To broadly interrogate the role of cation-π interactions in protein binding interactions, we report the first large-scale comparative evaluation of reader proteins for a neutral Kme3 isostere, experimental and computational mechanistic studies, and structural analysis. We find unexpected widespread binding of readers to a neutral isostere with the first examples of readers that bind the neutral isostere more tightly than Kme3. We find that no single factor dictates the charge selectivity, demonstrating the challenge of predicting such interactions. Further, readers that bind both cationic and neutral ligands differ in mechanism: binding Kme3 via cation-π interactions and the neutral isostere through the hydrophobic effect in the same aromatic cage. This discovery explains apparently contradictory results in previous studies, challenges traditional understanding of molecular recognition of tetraalkylammoniums by aromatic cages in myriad protein-ligand interactions, and establishes a new framework for selective inhibitor design by exploiting differences in charge dependence.

Challenges in natural product-based drug discovery assisted with in silico-based methods

The application of traditional medicine by humans for the treatment of ailments as well as improving the quality of life far outdates recorded history. To date, a significant percentage of humans, especially those living in developing/underprivileged communities still rely on traditional medicine for primary healthcare needs. In silico-based methods have been shown to play a pivotal role in modern pharmaceutical drug discovery processes. The application of these methods in identifying natural product (NP)-based hits has been successful. This is very much observed in many research set-ups that use rationally in silico-based methods in combination with experimental validation techniques. The combination has rendered the use of in silico-based approaches even more popular and successful in the investigation of NPs. However, identifying and proposing novel NP-based hits for experimental validation comes with several challenges such as the availability of compounds by suppliers, the huge task of separating pure compounds from complex mixtures, the quantity of samples available from the natural source to be tested, not to mention the potential ecological impact if the natural source is exhausted. Because most peer-reviewed publications are biased towards "positive results", these challenges are generally not discussed in publications. In this review, we highlight and discuss these challenges. The idea is to give interested scientists in this field of research an idea of what they can come across or should be expecting as well as prompting them on how to avoid or fix these issues.

Manipulating Cation-π Interactions with Genetically Encoded Tryptophan Derivatives

Cation-π interactions are the major noncovalent interactions for molecular recognition and play a central role in a broad area of chemistry and biology. Despite tremendous success in understanding the origin and biological importance of cation-π interactions, the design and synthesis of stronger cation-π interactions remain elusive. Here, we report an approach that greatly increases the binding energy of cation-π interactions by replacing Trp in the aromatic box with an electron-rich Trp derivative using the genetic code expansion strategy. The binding affinity between histone H3K4me3 and its reader is increased more than eightfold using genetically encoded 6-methoxy-Trp. Furthermore, through a systematic engineering process, we construct an H3K4me3 Super-Reader with single-digit nM affinity for H3K4me3 detection and imaging. More broadly, this approach paves the way for manipulating cation-π interactions for a variety of applications.

Comparative Analysis of Sulfonium-π, Ammonium-π, and Sulfur-π Interactions and Relevance to SAM-Dependent Methyltransferases

We report the measurement and analysis of sulfonium-π, thioether-π, and ammonium-π interactions in a β-hairpin peptide model system, coupled with computational investigation and PDB analysis. These studies indicated that the sulfonium-π interaction is the strongest and that polarizability contributes to the stronger interaction with sulfonium relative to ammonium. Computational studies demonstrate that differences in solvation of the trimethylsulfonium versus the trimethylammonium group also contribute to the stronger sulfonium-π interaction. In comparing sulfonium-π versus sulfur-π interactions in proteins, analysis of SAM- and SAH-bound enzymes in the PDB suggests that aromatic residues are enriched in close proximity to the sulfur of both SAM and SAH, but the populations of aromatic interactions of the two cofactors are not significantly different, with the exception of the Me-π interactions in SAM, which are the most prevalent interaction in SAM but are not possible for SAH. This suggests that the weaker interaction energies due to loss of the cation-π interaction in going from SAM to SAH may contribute to turnover of the cofactor.

AroCageDB: A Web-Based Resource for Aromatic Cage Binding Sites and Their Intrinsic Ligands

While aromatic cages have extensively been investigated in the context of structural biology, molecular recognition, and drug discovery, there exist to date no comprehensive resource for proteins sharing this conserved structural motif. To this end, we parsed the Protein Data Bank and thus constructed the Aromatic Cage Database (AroCageDB), a database for investigating the binding pocket descriptors and ligand binding space of aromatic-cage-containing proteins (ACCPs). AroCageDB contains 487 unique ACCPs bound to 890 unique ligands, for a total of 1636 complexes. This web-accessible database provides a user-friendly interface for the interactive visualization of ligand-bound ACCP structures, with a variety of search options that will open up opportunities for structural analyses and drug discovery campaigns. AroCageDB is freely available at http://www.pharmbioinf.uni-freiburg.de/arocagedb/.

Exploring aromatic cage flexibility of the histone methyllysine reader protein Spindlin1 and its impact on binding mode prediction: an in silico study

Some of the main challenges faced in drug discovery are pocket flexibility and binding mode prediction. In this work, we explored the aromatic cage flexibility of the histone methyllysine reader protein Spindlin1 and its impact on binding mode prediction by means of in silico approaches. We first investigated the Spindlin1 aromatic cage plasticity by analyzing the available crystal structures and through molecular dynamic simulations. Then we assessed the ability of rigid docking and flexible docking to rightly reproduce the binding mode of a known ligand into Spindlin1, as an example of a reader protein displaying flexibility in the binding pocket. The ability of induced fit docking was further probed to test if the right ligand binding mode could be obtained through flexible docking regardless of the initial protein conformation. Finally, the stability of generated docking poses was verified by molecular dynamic simulations. Accurate binding mode prediction was obtained showing that the herein reported approach is a highly promising combination of in silico methods able to rightly predict the binding mode of small molecule ligands in flexible binding pockets, such as those observed in some reader proteins.

MeCP2: latest insights fundamentally change our understanding of its interactions with chromatin and its functional attributes

Methyl CpG binding protein 2 (MeCP2) was initially isolated as an exclusive reader of DNA methylated at CpG. This recognition site, was subsequently extended to other DNA methylated residues and it has been the persisting dogma that binding to methylated DNA constitutes its physiologically relevant role. As we review here, two very recent papers fundamentally change our understanding of the interactions of this protein with chromatin, as well as its functional attributes. In the first one, the protein has been shown to bind to tri-methylated histone H3 (H3K27me3), providing a hint for what might turn out to be the first described chromodomain-containing protein reader in the animal kingdom, and unequivocally demonstrates the ability of MeCP2 to bind to nonmethylated CpG regions of the genome. The second paper reports how the protein dynamically participates in the formation of constitutive heterochromatin condensates. Histone H3K27me3 is a critical component of this form of chromatin.