On the use of one-step perturbation to investigate the dependence of NOE-derived atom–atom distance bound violations of peptides upon a variation of force-field parameters

Recognition of N6-Methyladenosine by the YTHDC1 YTH Domain Studied by Molecular Dynamics and NMR Spectroscopy: The Role of Hydration

The YTH domain of YTHDC1 belongs to a class of protein "readers", recognizing the N6-methyladenosine (m⁶A) chemical modification in mRNA. Static ensemble-averaged structures revealed details of N6-methyl recognition via a conserved aromatic cage. Here, we performed molecular dynamics (MD) simulations along with nuclear magnetic resonance (NMR) and isothermal titration calorimetry (ITC) to examine how dynamics and solvent interactions contribute to the m⁶A recognition and negative selectivity toward an unmethylated substrate. The structured water molecules surrounding the bound RNA and the methylated substrate's ability to exclude bulk water molecules contribute to the YTH domain's preference for m⁶A. Intrusions of bulk water deep into the binding pocket disrupt binding of unmethylated adenosine. The YTHDC1's preference for the 5'-Gm⁶A-3' motif is partially facilitated by a network of water-mediated interactions between the 2-amino group of the guanosine and residues in the m⁶A binding pocket. The 5'-Im⁶A-3' (where I is inosine) motif can be recognized too, but disruption of the water network lowers affinity. The D479A mutant also disrupts the water network and destabilizes m⁶A binding. Our interdisciplinary study of the YTHDC1 protein-RNA complex reveals an unusual physical mechanism by which solvent interactions contribute toward m⁶A recognition.

Hamiltonian Reweighing To Refine Protein Backbone Dihedral Angle Parameters in the GROMOS Force Field

Molecular dynamics simulations of proteins depend critically on the underlying force field, which may be parameterized against experimental data or high-quality quantum calculations. Here, we develop search algorithms based on Monte Carlo and steepest descent calculations to optimize the backbone dihedral angle parameters from a single reference simulation. We apply these tools to improve the agreement between simulations of single, capped amino acids and experimentally determined J values and secondary structure propensities of these molecules. The parameters are further refined based on simulations of a set of seven proteins and finally validated in simulations on a large set of 52 protein structures. Improvements in the dihedral angle distributions are observed, and structural propensities of the proteins are reproduced very well. Overall, the GROMOS 54A8_bb parameter set forms an improvement to previous parameter sets, both for small molecules and for protein simulations.

Optimization of Protein Backbone Dihedral Angles by Means of Hamiltonian Reweighting

Molecular dynamics simulations depend critically on the accuracy of the underlying force fields in properly representing biomolecules. Hence, it is crucial to validate the force-field parameter sets in this respect. In the context of the GROMOS force field, this is usually achieved by comparing simulation data to experimental observables for small molecules. In this study, we develop new amino acid backbone dihedral angle potential energy parameters based on the widely used 54A7 parameter set by matching to experimental J values and secondary structure propensity scales. In order to find the most appropriate backbone parameters, close to 100 000 different combinations of parameters have been screened. However, since the sheer number of combinations considered prohibits actual molecular dynamics simulations for each of them, we instead predicted the values for every combination using Hamiltonian reweighting. While the original 54A7 parameter set fails to reproduce the experimental data, we are able to provide parameters that match significantly better. However, to ensure applicability in the context of larger peptides and full proteins, further studies have to be undertaken.

Pyranose dehydrogenase ligand promiscuity: a generalized approach to simulate monosaccharide solvation, binding, and product formation

The flavoenzyme pyranose dehydrogenase (PDH) from the litter decomposing fungus Agaricus meleagris oxidizes many different carbohydrates occurring during lignin degradation. This promiscuous substrate specificity makes PDH a promising catalyst for bioelectrochemical applications. A generalized approach to simulate all 32 possible aldohexopyranoses in the course of one or a few molecular dynamics (MD) simulations is reported. Free energy calculations according to the one-step perturbation (OSP) method revealed the solvation free energies (ΔG_solv) of all 32 aldohexopyranoses in water, which have not yet been reported in the literature. The free energy difference between β- and α-anomers (ΔG_β-α) of all d-stereoisomers in water were compared to experimental values with a good agreement. Moreover, the free-energy differences (ΔG) of the 32 stereoisomers bound to PDH in two different poses were calculated from MD simulations. The relative binding free energies (ΔΔG_bind) were calculated and, where available, compared to experimental values, approximated from K_m values. The agreement was very good for one of the poses, in which the sugars are positioned in the active site for oxidation at C1 or C2. Distance analysis between hydrogens of the monosaccharide and the reactive N5-atom of the flavin adenine dinucleotide (FAD) revealed that oxidation is possible at HC1 or HC2 for pose A, and at HC3 or HC4 for pose B. Experimentally detected oxidation products could be rationalized for the majority of monosaccharides by combining ΔΔG_bind and a reweighted distance analysis. Furthermore, several oxidation products were predicted for sugars that have not yet been tested experimentally, directing further analyses. This study rationalizes the relationship between binding free energies and substrate promiscuity in PDH, providing novel insights for its applicability in bioelectrochemistry. The results suggest that a similar approach could be applied to study promiscuity of other enzymes.

Generally, enzymes are perceived as being specific for both their substrates and the reaction they catalyze. This standard paradigm started to shift and currently enzyme promiscuity towards various substrates is perceived rather as the rule than the exception. Enzyme promiscuity seems to be vital for proteins to acquire new functions, and therefore for evolution itself. The driving forces for promiscuity are manifold and consequently challenging to study. Binding free energies, which can be calculated from computer simulations, represent a convenient measure for them. Here, we investigate the binding free energies between the enzyme pyranose dehydrogenase (PDH) and a sugar-substrate by computational means. PDH has an extraordinarily promiscuous substrate-specificity, making it interesting for e.g. bioelectrochemical applications. By introducing modifications to the sugar-structure used for the molecular dynamics simulations, we could simultaneously study all 32 possible aldohexopyranoses from a single simulation. This saves costly computational resources and time for setting up and analyzing the simulations. We could nicely reproduce experimental results and predict so far undetected sugar-oxidation products, directing further experiments. This study gives novel insights into PDH's substrate promiscuity and the enzyme's applicability. A similar approach could be applied to study the promiscuity of other enzymes.