Mechanisms of histone lysine-modifying enzymes: A computational perspective on the role of the protein environment

Approaching the catalytic mechanism of protein lysine methyltransferases by biochemical and simulation techniques

Protein lysine methyltransferases (PKMTs) transfer up to three methyl groups to the side chains of lysine residues in proteins and fulfill important regulatory functions by controlling protein stability, localization and protein/protein interactions. The methylation reactions are highly regulated, and aberrant methylation of proteins is associated with several types of diseases including neurologic disorders, cardiovascular diseases, and various types of cancer. This review describes novel insights into the catalytic machinery of various PKMTs achieved by the combined application of biochemical experiments and simulation approaches during the last years, focusing on clinically relevant and well-studied enzymes of this group like DOT1L, SMYD1-3, SET7/9, G9a/GLP, SETD2, SUV420H2, NSD1/2, different MLLs and EZH2. Biochemical experiments have unraveled many mechanistic features of PKMTs concerning their substrate and product specificity, processivity and the effects of somatic mutations observed in PKMTs in cancer cells. Structural data additionally provided information about the substrate recognition, enzyme-substrate complex formation, and allowed for simulations of the substrate peptide interaction and mechanism of PKMTs with atomistic resolution by molecular dynamics and hybrid quantum mechanics/molecular mechanics methods. These simulation technologies uncovered important mechanistic details of the PKMT reaction mechanism including the processes responsible for the deprotonation of the target lysine residue, essential conformational changes of the PKMT upon substrate binding, but also rationalized regulatory principles like PKMT autoinhibition. Further developments are discussed that could bring us closer to a mechanistic understanding of catalysis of this important class of enzymes in the near future. The results described here illustrate the power of the investigation of enzyme mechanisms by the combined application of biochemical experiments and simulation technologies.

Mechanistic Investigation of Lysine-Targeted Covalent Inhibition of PI3Kδ via ONIOM QM:QM Computations

Phosphoinositide 3-kinase (PI3K) enzymes are important drug targets, especially in oncology, and several inhibitors are currently under investigation in clinical trials for the treatment of lymphocytic leukemia, follicular lymphoma, breast, thyroid, colorectal, and lung cancer. Targeted covalent inhibitors hold significant promise for drug discovery research especially for kinases. Targeting the lysine residues attracts attention as a new strategy in designing targeted covalent inhibitors, since the lysine residue provides several advantages over the traditional cysteine residue. Recently, new highly selective covalent inhibitors of PI3Kδ with activated ester warheads, targeting the conserved Lys779 residue, were reported. Based on the observed kinetics, a covalent inhibition mechanism was proposed, but the atomistic details of the reaction are still not understood. Therefore, in the present work, we have conducted quantum chemical ONIOM M06-2X/6-31+G(d,p):PM6 calculations on the active site cluster structure of PI3Kδ to elucidate the microscopic details of the mechanism of the aminolysis reaction between Lys779 and the ester inhibitors. Our calculations clearly discriminate the noncovalent methyl ester inhibitor and the covalent inhibitors with activated phenolic esters. For the representative p-NO₂, p-F, p-H, and p-OCH₃ phenolic esters, the Gibbs free energy profiles of alternative mechanistic paths through either Asp782 or Asp911 demonstrate the modulatory role of active site aspartate residues. The most plausible path alters depending on the electron-withdrawing/donating nature of the p-substituted phenolate leaving group. Inhibitors with sufficiently strong electron-withdrawing group prefer direct dissociation of the leaving group from the tetrahedral zwitterion intermediate, while the ones with electron-donating group favor the formation of a neutral tetrahedral intermediate prior to the dissociation. The relative Gibbs free energy barriers of p-NO₂ < p-F < p-H < p-OCH₃ substituted phenyl esters display the same qualitative trend as the experimentally measured k_inact/K_I values. Our results provide in depth insight into the mechanism, which can pave the way for optimizing the inhibitor efficiency.

Cation-π interactions in protein-ligand binding: theory and data-mining reveal different roles for lysine and arginine

The interactions of neutral aromatic ligands with cationic arginine, histidine and lysine amino acid residues have been studied with ab initio calculations, symmetry adapted perturbation theory (SAPT), and a systematic meta-analysis of X-ray structures.

We have studied the cation–π interactions of neutral aromatic ligands with the cationic amino acid residues arginine, histidine and lysine using ab initio calculations, symmetry adapted perturbation theory (SAPT), and a systematic meta-analysis of all available Protein Data Bank (PDB) X-ray structures. Quantum chemical potential energy surfaces (PES) for these interactions were obtained at the DLPNO-CCSD(T) level of theory and compared against the empirical distribution of 2012 unique protein–ligand cation–π interactions found in X-ray crystal structures. We created a workflow to extract these structures from the PDB, filtering by interaction type and residue pK_a. The gas phase cation–π interaction of lysine is the strongest by more than 10 kcal mol^–1, but the empirical distribution of 582 X-ray structures lies away from the minimum on the interaction PES. In contrast, 1381 structures involving arginine match the underlying calculated PES with good agreement. SAPT analysis revealed that underlying differences in the balance of electrostatic and dispersion contributions are responsible for this behavior in the context of the protein environment. The lysine–arene interaction, dominated by electrostatics, is greatly weakened by a surrounding dielectric medium and causes it to become essentially negligible in strength and without a well-defined equilibrium separation. The arginine–arene interaction involves a near equal mix of dispersion and electrostatic attraction, which is weakened to a much smaller degree by the surrounding medium. Our results account for the paucity of cation–π interactions involving lysine, even though this is a more common residue than arginine. Aromatic ligands are most likely to interact with cationic arginine residues as this interaction is stronger than for lysine in higher polarity surroundings.

QM/MM Investigation of Substrate and Product Specificities of Suv4-20h2: How Does This Enzyme Generate Dimethylated H4K20 from Monomethylated Substrate?

Protein lysine methyltransferases (PKMTs) catalyze the methylation of lysine residues on histone proteins in the regulation of chromatin structure and gene expression. In contrast to many other PKMTs for which unmodified lysine is the methylation target, the enzymes in the Suv4-20 family are able to generate dimethylated product (H4K20me2) based exclusively on the monomethylated H4K20 substrate (H4K20me1). The origin of such substrate/product specificity is still not clear. Here, molecular dynamics (MD) and free energy (potential of mean force) simulations are undertaken using quantum mechanical/molecular mechanical (QM/MM) potentials to understand the substrate/product specificities of Suv4-20h2, a member of the Suv4-20 family. The free energy barriers for mono-, di-, and trimethylation in Suv4-20h2 obtained from the simulations are found to be well correlated with the specificities observed experimentally with the allowed dimethylation based on the H4K20me1 substrate and prohibited monomethylation and trimethylation based on H4K20 and H4K20me2, respectively. It is demonstrated that the reason for the relatively efficient dimethylation is an effective transition state (TS) stabilization through strengthening the CH···O interactions as well as the presence of a cation-π interaction at the transition state. The simulations also show that the failures of Suv4-20h2 to catalyze monomethylation and trimethylation are due, respectively, to a less effective TS stabilization and inability of the reactant complex containing H4K20me2 to adopt a reactive (near attack) configuration for methyl transfer. The results suggest that care must be exercised in the prediction of the substrate specificity based only on the existence of near attack configurations in substrate complexes.

Building a More Predictive Protein Force Field: A Systematic and Reproducible Route to AMBER-FB15

The increasing availability of high-quality experimental data and first-principles calculations creates opportunities for developing more accurate empirical force fields for simulation of proteins. We developed the AMBER-FB15 protein force field by building a high-quality quantum chemical data set consisting of comprehensive potential energy scans and employing the ForceBalance software package for parameter optimization. The optimized potential surface allows for more significant thermodynamic fluctuations away from local minima. In validation studies where simulation results are compared to experimental measurements, AMBER-FB15 in combination with the updated TIP3P-FB water model predicts equilibrium properties with equivalent accuracy, and temperature dependent properties with significantly improved accuracy, in comparison with published models. We also discuss the effect of changing the protein force field and water model on the simulation results.

Cation–π interactions in CREBBP bromodomain inhibition: an electrostatic model for small-molecule binding affinity and selectivity

A new model is presented to explain and predict binding affinity of aromatic and heteroaromatic ligands for the CREBBP bromodomain based on cation–π interaction strength.