Accelerated Enveloping Distribution Sampling to Probe the Presence of Water Molecules.

Determining the presence of water molecules at protein-ligand interfaces is still a challenging task in free-energy calculations. The inappropriate placement of water molecules results in the stabilization of wrong conformational orientations of the ligand. With classical alchemical perturbation methods, such as thermodynamic integration (TI), it is essential to know the amount of water molecules in the active site of the respective ligands. However, the resolution of the crystal structure and the correct assignment of the electron density do not always lead to a clear placement of water molecules. In this work, we apply the one-step perturbation method named accelerated enveloping distribution sampling (AEDS) to determine the presence of water molecules in the active site by probing them in a fast and straightforward way. Based on these results, we combined the AEDS method with standard TI to calculate accurate binding free energies in the presence of buried water molecules. The main idea is to perturb the water molecules with AEDS such that they are allowed to alternate between regular water molecules and non-interacting dummy particles while treating the ligand with TI over an alchemical pathway. We demonstrate the use of AEDS to probe the presence of water molecules for six different test systems. For one of these, previous calculations showed difficulties to reproduce the experimental binding free energies, and here, we use the combined TI-AEDS approach to tackle these issues.

Interaction preferences between protein side chains and key epigenetic modifications 5-methylcytosine, 5-hydroxymethycytosine and N6-methyladenine.

Covalent modifications of standard DNA/RNA nucleobases affect epigenetic regulation of gene expression by modulating interactions between nucleic acids and protein readers. We derive here the absolute binding free energies and analyze the binding modalities between key modified nucleobases 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC) and N6-methyladenine (m6A) and all non-prolyl/non-glycyl protein side chains using molecular dynamics simulations and umbrella sampling in both water and methanol, the latter mimicking the low dielectric environment at the dehydrated nucleic-acid/protein interfaces. We verify the derived affinities by comparing against a comprehensive set of high-resolution structures of nucleic-protein complexes involving 5mC. Our analysis identifies protein side chains that are highly tuned for detecting cytosine methylation as a function of the environment and can thus serve as microscopic readers of epigenetic marks. Conversely, we show that the relative ordering of sidechain affinities for 5hmC and m6A does not differ significantly from those for their precursor bases, cytosine and adenine, respectively, especially in the low dielectric environment. For those two modified bases, the effect is more nuanced and manifests itself primarily at the level of absolute changes in the binding free energy. Our results contribute towards establishing a quantitative foundation for understanding, predicting and modulating the interactions between modified nucleic acids and proteins at the atomistic level.

Optimization of Alchemical Pathways Using Extended Thermodynamic Integration.

Thermodynamic integration (TI) is a commonly used method to determine free-energy differences. One of its disadvantages is that many intermediate λ-states need to be sampled in order to be able to integrate accurately over ⟨∂H/∂λ⟩. Here, we use the recently introduced extended TI to study alternative parameterizations of H(λ) and its influence on the smoothness of the ⟨∂H/∂λ⟩ curves as well as the efficiency of the simulations. We find that the extended TI approach can be used to select curves of low curvature. An optimal parameterization is suggested for the calculation of hydration free energies. For calculations of relative binding free energies, we show that optimized parameterizations of the Hamiltonian in the unbound state also effectively lower the curvature in the bound state of the ligand.

Advances in the calculation of binding free energies.

In recent years, calculations of binding affinities from molecular simulations seem to have matured significantly. While the number of applications of such methods in drug design and biotechnology increases, the number of truly new methodological developments decreases. This review provides an overview of the current status of the field as reflected in recent publications. The focus is on the challenges that remain when using endstate, alchemical and pathway methods. For endstate methods this is the calculation of entropic contributions. For alchemical methods there are unsolved problems associated with the solvation of the active site, sampling slow degrees of freedom and when modifying the net charge. For pathway methods achieving sufficient sampling remains challenging. New trends are also highlighted, including the use of pathway methods for the quantification of protein-protein interactions.

A switch in nucleotide affinity governs activation of the Src and Tec family kinases.

The Tec kinases, closely related to Src family kinases, are essential for lymphocyte function in the adaptive immune system. Whilst the Src and Abl kinases are regulated by tail phosphorylation and N-terminal myristoylation respectively, the Tec kinases are notable for the absence of either regulatory element. We have found that the inactive conformations of the Tec kinase Itk and Src preferentially bind ADP over ATP, stabilising both proteins. We demonstrate that Itk adopts the same conformation as Src and that the autoinhibited conformation of Src is independent of its C-terminal tail. Allosteric activation of both Itk and Src depends critically on the disruption of a conserved hydrophobic stack that accompanies regulatory domain displacement. We show that a conformational switch permits the exchange of ADP for ATP, leading to efficient autophosphorylation and full activation. In summary, we propose a universal mechanism for the activation and autoinhibition of the Src and Tec kinases.

Dependence of Binding Free Energies between RNA Nucleobases and Protein Side Chains on Local Dielectric Properties.

In order to fully understand the microscopic origins of binding specificity between nucleic acids and proteins, it is imperative to study the dependence of the binding preferences between nucleobases and protein side chains on the properties of the environment. Here, we employ molecular dynamics simulations and umbrella sampling to derive the potentials of mean force and the associated absolute binding free energies between the four standard RNA nucleobases and the side chains of aspartic acid and tryptophan in water/methanol mixtures exhibiting a wide range of dielectric constants. In addition to their opposing character when it comes to hydrophobicity, aspartate and tryptophan side chains were chosen because they exhibit the greatest change in binding free energies with nucleobases between pure water and methanol environments. We exploit a strong linear dependence of the derived ΔG values on the mole fraction of methanol to estimate the binding free energies of all possible combinations of different standard RNA nucleobases and side chains at multiple values of dielectric constants. Finally, we critically assess the recently proposed complementarity hypothesis concerning direct, coaligned binding between mRNAs and their cognate proteins in light of the present results.

Absolute binding-free energies between standard RNA/DNA nucleobases and amino-acid sidechain analogs in different environments.

Despite the great importance of nucleic acid-protein interactions in the cell, our understanding of their physico-chemical basis remains incomplete. In order to address this challenge, we have for the first time determined potentials of mean force and the associated absolute binding free energies between all standard RNA/DNA nucleobases and amino-acid sidechain analogs in high- and low-dielectric environments using molecular dynamics simulations and umbrella sampling. A comparison against a limited set of available experimental values for analogous systems attests to the quality of the computational approach and the force field used. Overall, our analysis provides a microscopic picture behind nucleobase/sidechain interaction preferences and creates a unified framework for understanding and sculpting nucleic acid-protein interactions in different contexts. Here, we use this framework to demonstrate a strong relationship between nucleobase density profiles of mRNAs and nucleobase affinity profiles of their cognate proteins and critically analyze a recent hypothesis that the two may be capable of direct, complementary interactions.

Comparison of thermodynamic integration and Bennett acceptance ratio for calculating relative protein-ligand binding free energies.

The performances of Bennett's acceptance ratio method and thermodynamic integration (TI) for the calculation of free energy differences in protein simulations are compared. For the latter, the standard trapezoidal rule, Simpson's rule, and Clenshaw-Curtis integration are used as numerical integration methods. We evaluate the influence of the number and definition of intermediate states on the precision, accuracy, and efficiency of the free energy calculations. Our results show that non-equidistantly spaced intermediate states are in some cases beneficial for the TI methods. Using several combinations of softness parameters and the λ power dependence, it is shown that these benefits are strongly dependent on the shape of the integrand. Although TI is more user-friendly due to its simplicity, it was found that Bennett's acceptance ratio method is the more efficient method. It is also the least dependent on the choice of the intermediate states, making it more robust than TI.

Protein-Ligand Binding from Distancefield Distances and Hamiltonian Replica Exchange Simulations.

The calculation of protein-ligand binding free energies is an important goal in the field of computational chemistry. Applying path-sampling methods for this purpose involves calculating the associated potential of mean force (PMF) and gives insight into the binding free energy along the binding process. Without a priori knowledge about the binding path, sampling reversible binding can be difficult to achieve. To alleviate this problem, we introduce the distancefield (DF) as a reaction coordinate for such calculations. DF is a grid-based method in which the shortest distance between the binding site and a ligand is determined avoiding routes that pass through the protein. Combining this reaction coordinate with Hamiltonian replica exchange molecular dynamics (HREMD) allows for the reversible binding of the ligand to the protein. A comparison is made between umbrella sampling using regular distance restraints and HREMD with DF restraints to study aspirin binding to the protein phospholipase A2. Although the free energies of binding are similar for both methods, the increased sampling with HREMD has a significant influence on the shape of the PMF. A remarkable agreement between the calculated binding free energies from the PMF and the experimental estimate is obtained.

Malleability and versatility of cytochrome P450 active sites studied by molecular simulations.

As the most important phase I drug metabolizing enzymes, the human Cytochromes P450 display an enormous versatility in the molecular structures of possible substrates. Individual isoforms may preferentially bind specific classes of molecules, but also within these classes, some isoforms show remarkable levels of promiscuity. In this work, we try to link this promiscuity to the versatility and malleability of the active site at the hand of examples from our own work. Mainly focusing on the flexibility of protein structures and the presence or absence of water molecules, we establish molecular reasons for observed promiscuity, determine the relevant factors to take into account when predicting binding poses and rationalize the role of individual interactions in the process of ligand binding. A high level of active site flexibility does not only allow for the binding of a large variety of substrates and inhibitors, but also appears to be important to facilitate ligand binding and unbinding.

Efficient and Accurate Free Energy Calculations on Trypsin Inhibitors.

Several combinations of free energy calculation methods have been applied to determine the relative free energies of binding between eight para-substituted benzamidines in complex with the serine protease trypsin. With the aim to improve efficiency and maintain accuracy, the linear response approximation (LRA), linear interaction energy (LIE) and third power fitting (TPF) are combined with the one-step perturbation (OSP) to determine the polar and apolar contributions to the free energy, respectively. It is shown that the combination TPF/OSP gives the most accurate results and is 4.5 times more efficient than the rigorous thermodynamic integration (TI). By projecting the electrostatic preorganization energy from the OSP simulations, an increase in efficiency of a factor 7.5 can even be achieved. Loss of accuracy with respect to the TI data is limited to 3.9 and 5.6 kJ/mol, respectively, making it an attractive approach for lead optimization programs in drug research.

Free energy calculations of protein-ligand interactions.

In the calculation of free energies of binding for protein-ligand complexes, we distinguish endpoint methods, methods involving alchemical modifications and methods that physically displace the ligand from the protein. Most methodological advances seem to come from a clever combination of multiple existing methods to enhance the sampling or to utilize specific advantages of various approaches. The coupling parameters common in thermodynamic integration and in Hamiltonian replica exchange are for instance combined to yield replica exchange thermodynamic integration. As new methods mostly aim to improve efficiency or to attain more complete sampling, there are good prospects to understand and tackle the sampling problem better and to shift the focus towards the scoring problem in the context of more robust and accurate force fields.

Impact of plasticity and flexibility on docking results for cytochrome P450 2D6: a combined approach of molecular dynamics and ligand docking.

Cytochrome P450s (CYPs) exhibit a large plasticity and flexibility in the active site allowing for the binding of a large variety of substrates. The impact of plasticity and flexibility on ligand binding is investigated by docking 65 known CYP2D6 substrates to an ensemble of 2500 protein structures. The ensemble was generated by molecular dynamics simulations of CYP2D6 in complex with five representative substrates. The effect of induced fit, the conformation of Phe483, and thermal motion on the accuracy of site of metabolism (SOM) predictions is analyzed. For future predictions, the three most essential CYP2D6 structures were selected which are suitable for different kinds of ligands. We have developed a binary decision tree to decide which protein structure to dock the ligand into, such that each ligand needs to be docked only once, leading to successful SOM prediction in 80% of the substrates.