Methyl‐Induced Polarization Destabilizes the Noncovalent Interactions of N‐Methylated Lysines

Abstract

Lysine methylation can modify noncovalent interactions by altering lysine's hydrophobicity as well as its electronic structure. Although the ramifications of the former are documented, the effects of the latter remain largely unknown. Understanding the electronic structure is important for determining how biological methylation modulates proteinÀ protein binding, and the impact of artificial methylation experiments in which methylated lysines are used as spectroscopic probes and protein crystallization facilitators. The benchmarked first-principles calculations undertaken here reveal that methyl-induced polarization weakens the electrostatic attraction of amines with protein functional groups -salt bridges, hydrogen bonds and cation-π interactions weaken by as much as 10.3, 7.9 and 3.5 kT, respectively. Multipole analysis shows that weakened electrostatics is due to the altered inductive effects, which overcome increased attraction from methyl-enhanced polarizability and dispersion. Due to their fundamental nature, these effects are expected to be present in many cases. A survey of methylated lysines in protein structures reveals several cases in which methyl-induced polarization is the primary driver of altered noncovalent interactions; in these cases, destabilizations are found to be in the 0.6-4.7 kT range. The clearest case of where methyl-induced polarization plays a dominant role in regulating biological function is that of the PHD1-PHD2 domain, which recognizes lysine-methylated states on histones. These results broaden our understanding of how methylation modulates noncovalent interactions.

Reading and erasing of the phosphonium analogue of trimethyllysine by epigenetic proteins

“…Quantum chemical calculations were performed with the Amsterdam Density Functional software (ADF) 53 using dispersioncorrected density functional theory at the BLYP-D3BJ/TZ2P level of theory 54 . Our BLYP-D3BJ/TZ2P approach provided results that are in excellent agreement with those of a recent high-level CCSD(T) benchmark study by Varma and coworkers (Supplementary Table 6) 55 . Solvation in water was simulated by means of the conductor like screening model (COSMO) of solvation implemented in ADF [56][57][58][59] .…”

Inclusion of High-Field Target Data in AMOEBA’s Calibration Improves Predictions of Protein–Ion Interactions

“…We note, however, that some of the error in the AMOEBA FF may be artifactual due to the inherent bias in the reference QM method that we are using. We have reported previously that the employed PBE0+vdW DFT tends to overbind monovalent cations by 1–2 kcal/mol compared to CCSD­(T)/CBS. − …”

“…First, it is shown that PBE0 + vdW yields an accuracy of 0.3 kcal/mol in comparison to “gold standard” quantum chemical reference data for a wide range of intermolecular interactions in molecular dimers . Second, we have reported previously − that compared to quantum Monte Carlo calculations and CCSD­(T) calculations in the complete basis set (CBS) limit, PBE0 + vdW yields a MAE of 0.93 kcal/mol for interaction energies of monovalent cations (Na + , K + , and NH 4 + ) with homogeneous clusters of various small molecules (waters, alcohols, amides, aromatics, and carboxylates). At the same time, we do note that the error in PBE0 + vdW is systematic with respect to quantum Monte Carlo simulations and CCSD­(T)/CBS in that PBE0 + vdW generally overbinds.…”

“…To remedy this, we first used high-level QM methods, including quantum Monte Carlo and CCSD­(T), which were made accessible only recently, to generate the necessary benchmarking data. ,− Then, we explored two approaches to improve the polarization model. Both yielded comparable improvements.…”

“…Carbonyls, carboxylates, and hydroxyls are the three primary chemical groups in proteins that are known to interact with Na + and K + ions. , We then evaluate the performance of the recalibrated protein FF in predicting ion–protein interaction energies of ion clusters extracted from the protein data bank (PDB). Reference values for ion–protein interaction energies are obtained from vdW-inclusive density functional theory (DFT) that we have, over the past years, systematically benchmarked for ion–ligand interactions against experiments and “gold-standard” QM methods, including quantum Monte Carlo and CCSD­(T). ,− We examine whether the recalibrated AMOEBA FF retains its intrinsic reliability in reproducing reference experimental data on protein structure and dynamics in the condensed phase. …”