A Transferable Non-bonded Pairwise Force Field to Model Zinc Interactions in Metalloproteins

DP/MM: A Hybrid Model for Zinc-Protein Interactions in Molecular Dynamics

Zinc-containing proteins are vital for many biological processes, yet accurately modeling them using classical force fields is hindered by complicated polarization and charge transfer effects. This study introduces DP/MM, a hybrid force field scheme that utilizes a deep potential model to correct the atomic forces of zinc ions and their coordinated atoms, elevating them from MM to QM levels of accuracy. Trained on the difference between MM and QM atomic forces across diverse zinc coordination groups, the DP/MM model faithfully reproduces structural characteristics of zinc coordination during simulations, such as the tetrahedral coordination of Cys4 and Cys3His1 groups. Furthermore, DP/MM allows water exchange in the zinc coordination environment. With its unique blend of accuracy, efficiency, flexibility, and transferability, DP/MM serves as a valuable tool for studying structures and dynamics of zinc-containing proteins and also represents a pioneering approach in the evolving landscape of machine learning potentials for molecular modeling.

QM/MM and MM MD Simulations on Enzymatic Degradation of the Nerve Agent VR by Phosphotriesterase

V-type nerve agents are hardly degraded by phosphotriesterase (PTE). Interestingly, the PTE variant of BHR-73MNW can effectively improve the hydrolytic efficiency of VR, especially for its Sp-enantiomer. Here, the whole enzymatic degradation of both Sp and Rp enantiomers of VR by the wild-type PTE and its variant BHR-73MNW was investigated by quantum mechanics/molecular mechanics (QM/MM) calculations and MM molecular dynamics simulations. Present results indicate that the degradation of VR can be initiated by the nucleophilic attack of the bridging OH- and the zinc-bound water molecule. The QM/MM-predicted energy barriers for the hydrolytic process of Sp-VR are 19.8 kcal mol-1 by the variant with water as a nucleophile and 22.0 kcal mol-1 by the wild-type PTE with OH- as a nucleophile, and corresponding degraded products are bound to the dinuclear metal site in monodentate and bidentate coordination modes, respectively. The variant effectively increases the volume of the large pocket, allowing more water molecules to enter the active pocket and resulting in the improvement of the degradation efficiency of Sp-VR. The hydrolysis of Rp-VR is triggered only by the hydroxide with an energy span of 20.6 kcal mol-1 for the wild-type PTE and 20.7 kcal mol-1 for the variant BHR-73-MNW PTE. Such mechanistic insights into the stereoselective degradation of VR by PTE and the role of water may inspire further studies to improve the catalytic efficiency of PTE toward the detoxification of nerve agents.

Supramolecular Combination Chemotherapy: Cucurbit[8]uril Complex Enhanced Platinum Drug Infiltration and Modified Nanomechanical Property of Colorectal Cancer Cells

Combination chemotherapy is recognized as a vital medical treatment for cancer, but it has not achieved clinical ideal effects of combination therapy. Herein, we designed a supramolecular combination chemotherapy strategy based on cucurbit[8]uril (CB[8]), which can be facilely assembled into dual platinum drugs. Interestingly, employing the CB[8] carrier led to a greater than 10-fold intracellular Pt content compared to that of dual drugs at 4 h, and the CB[8] complex (CLE) can enhance the infiltration of platinum drugs in colorectal tumor cells tremendously. The platinum drugs can be released from CLE through consuming more tumor biomarker spermidine. Through analyzing the nanomechanical property of the colorectal tumor cellular surface by bioscope AFM, it was revealed that CLE modified the property by decreasing the adhesion and increasing the stiffness. This study provided a facile and sensitive strategy for improving combination chemotherapy by supramolecular materials.

Automatically Constructed Neural Network Potentials for Molecular Dynamics Simulation of Zinc Proteins

The development of accurate and efficient potential energy functions for the molecular dynamics simulation of metalloproteins has long been a great challenge for the theoretical chemistry community. An artificial neural network provides the possibility to develop potential energy functions with both the efficiency of the classical force fields and the accuracy of the quantum chemical methods. In this work, neural network potentials were automatically constructed by using the ESOINN-DP method for typical zinc proteins. For the four most common zinc coordination modes in proteins, the potential energy, atomic forces, and atomic charges predicted by neural network models show great agreement with quantum mechanics calculations and the neural network potential can maintain the coordination geometry correctly. In addition, MD simulation and energy optimization with the neural network potential can be readily used for structural refinement. The neural network potential is not limited by the function form and complex parameterization process, and important quantum effects such as polarization and charge transfer can be accurately considered. The algorithm proposed in this work can also be directly applied to proteins containing other metal ions.

GM-DockZn: a geometry matching-based docking algorithm for zinc proteins

Motivation

Molecular docking is a widely used technique for large-scale virtual screening of the interactions between small-molecule ligands and their target proteins. However, docking methods often perform poorly for metalloproteins due to additional complexity from the three-way interactions among amino-acid residues, metal ions and ligands. This is a significant problem because zinc proteins alone comprise about 10% of all available protein structures in the protein databank. Here, we developed GM-DockZn that is dedicated for ligand docking to zinc proteins. Unlike the existing docking methods developed specifically for zinc proteins, GM-DockZn samples ligand conformations directly using a geometric grid around the ideal zinc-coordination positions of seven discovered coordination motifs, which were found from the survey of known zinc proteins complexed with a single ligand.

Results

GM-DockZn has the best performance in sampling near-native poses with correct coordination atoms and numbers within the top 50 and top 10 predictions when compared to several state-of-the-art techniques. This is true not only for a non-redundant dataset of zinc proteins but also for a homolog set of different ligand and zinc-coordination systems for the same zinc proteins. Similar superior performance of GM-DockZn for near-native-pose sampling was also observed for docking to apo-structures and cross-docking between different ligand complex structures of the same protein. The highest success rate for sampling nearest near-native poses within top 5 and top 1 was achieved by combining GM-DockZn for conformational sampling with GOLD for ranking. The proposed geometry-based sampling technique will be useful for ligand docking to other metalloproteins.

Availability and implementation

GM-DockZn is freely available at www.qmclab.com/ for academic users.

Supplementary information

Supplementary data are available at Bioinformatics online.

How to complete the tautomerization and substrate-assisted activation prior to C–C bond fission by meta-cleavage product hydrolase LigY?

Two feasible binding modes could complete the C–C bond fission of the substrate. One is the bidentate mode and five-coordination, and the other is the monodentate mode and five-coordination.

Upgrading and Validation of the AMBER Force Field for Histidine and Cysteine Zinc(II)-Binding Residues in Sites with Four Protein Ligands

We developed and validated a novel force field in the context of the AMBER parameterization for the simulation of zinc(II)-binding proteins. The proposed force field assumes nonbonded spherical interactions between the central zinc(II) and the coordinating residues. A crucial innovative aspect of our approach is to account for the polarization effects of the cation by redefining the atomic charges of the coordinating residues and an adjustment of Lennard-Jones parameters of Zn-interacting atoms to reproduce mean distance distributions. The optimal transferable parametrization was obtained by performing accurate quantum mechanical calculations on a training set of high-quality protein structures, encompassing the most common folds of zinc(II) sites. The addressed sites contain a zinc(II) ion tetra-coordinated by histidine and cysteine residues and represent about 70% of all physiologically relevant zinc(II) sites in the Protein Data Bank. Molecular dynamics simulations with explicit solvent, carried out on several zinc(II)-binding proteins not included in the training set, show that our model for zinc(II) sites preserves the tetra-coordination of the metal site with remarkable stability, yielding zinc(II)-X mean distances similar to experimental data. Finally, the model was tested by evaluating the zinc(II)-binding affinities, using the alchemical free energy perturbation approach. The calculated dissociation constants correlate satisfactorily with the experimental counterpart demonstrating the validity and transferability of the proposed parameterization for zinc(II)-binding proteins.

Development of Nonbonded Models for Metal Cations Using the Electronic Continuum Correction

The parametrization of classical nonbonded models of metal ions has been widely addressed in the recent years. Despite the continuous development of novel and more physically inspired functional forms, the 12-6 Lennard-Jones plus Coulomb potential is still the most adopted force field in molecular dynamics (MD) codes, owing to its simple form and easy implementation. However, due to the integer formal charge, unpolarizable force fields of ions may suffer from overestimated interatomic electrostatic interactions, leading to nonphysical clustering or repulsion between such full charges. The electronic continuum correction (ECC) can fix this problem through a simple inclusion of solvent polarization effects via ionic charge rescaling. In this work, the development of novel nonbonded models for mono, divalent, and highly charged metal ions is presented. For each metal species, the ionic charge has been scaled, according to the ECC. Lennard-Jones parameters have been optimized using experimental structural and thermodynamic properties as target quantities. Performances of the proposed models are discussed and compared with the literature data, while transferability attitudes among different and well-known water models are evaluated. © 2019 Wiley Periodicals, Inc.

Transition Metal Ion Interactions with Disordered Amyloid-β Peptides in the Pathogenesis of Alzheimer's Disease: Insights from Computational Chemistry Studies

Monomers and oligomers of the amyloid-β peptide aggregate to form the fibrils found in the brains of Alzheimer's disease patients. These monomers and oligomers are largely disordered and can interact with transition metal ions, affecting the mechanism and kinetics of amyloid-β aggregation. Due to the disordered nature of amyloid-β, its rapid aggregation, as well as solvent and paramagnetic effects, experimental studies face challenges in the characterization of transition metal ions bound to amyloid-β monomers and oligomers. The details of the coordination chemistry between transition metals and amyloid-β obtained from experiments remain debated. Furthermore, the impact of transition metal ion binding on the monomeric or oligomeric amyloid-β structures and dynamics are still poorly understood. Computational chemistry studies can serve as an important complement to experimental studies and can provide additional knowledge on the binding between amyloid-β and transition metal ions. Many research groups conducted first-principles calculations, ab initio molecular dynamics simulations, quantum mechanics/classical mechanics simulations, and classical molecular dynamics simulations for studying the interplay between transition metal ions and amyloid-β monomers and oligomers. This review summarizes the current understanding of transition metal interactions with amyloid-β obtained from computational chemistry studies. We also emphasize the current view of the coordination chemistry between transition metal ions and amyloid-β. This information represents an important foundation for future metal ion chelator and drug design studies aiming to combat Alzheimer's disease.

Molecular Dynamics Investigation into the Effect of Zinc(II) on the Structure and Membrane Interactions of the Antimicrobial Peptide Clavanin A

Clavanin A (ClavA) is an antimicrobial peptide (AMP) whose antimicrobial activity is enhanced in the presence of Zn(II) ions. The antimicrobial activity of ClavA has been shown to increase 16-fold in the presence of Zn(II) ions. In this study, we investigate the potential sources of this enhancement, namely, the effect of Zn(II) binding on the helical conformation of ClavA and on the ClavA interaction with a model for gram-negative bacterial membranes. In addition, we investigate the effect of Zn(II) on the membrane mechanical properties. We employed all-atom equilibrium molecular dynamics simulations initiated from both fully helical and random coil structures of ClavA. We observe that Zn(II) can stabilize an existing helical conformation in the Zn(II)-binding region, but we do not observe induction of helical conformations in systems initiated in random coil configurations. Zn(II) binding to ClavA provides more favorable electrostatics for membrane association in the C-terminal region. This is evidenced by longer and stronger C-terminal-lipid interactions. Zn(II) is also capable of modulating the membrane properties in a manner which favors ClavA insertion and the potential for enhanced translocation into the cell. This work provides insights into the role of divalent metal cations in the antimicrobial activity of ClavA. This information can be used for the development of synthetic AMPs containing motifs that can bind metals (metalloAMPs) for therapeutic and medical purposes.

A Fragment Quantum Mechanical Method for Metalloproteins

An accurate energy calculation of metalloprotein is of crucial importance and also a theoretical challenge. In this work, a metal molecular fractionation with conjugate caps (metal-MFCC) approach is developed for efficient linear-scaling quantum calculation of potential energy and atomic forces of metalloprotein. In this approach, the potential energy of a given protein is calculated by a linear combination of potential energies of the neighboring residues, two-body interaction energy between non-neighboring residues that are spatially in close contact and the potential energy of the metal binding group. The calculation of each fragment is embedded in a field of point charges representing the remaining protein environment. Numerical studies were carried out to check the performance of this method, and the calculated potential energies and atomic forces all show excellent agreement with the full system calculations at the M06-2X/6-31G(d) level. By combining the energy calculation with molecular dynamic simulation, we performed an ab initio structural optimization for a zinc finger protein with high efficiency. The present metal-MFCC approach is linear-scaling with a low prefactor and trivially parallelizable. The individual fragment typically contains about 50 atoms, and it is thus possible to be calculated at higher levels of the quantum chemistry method. This fragment method can be routinely applied to perform structural optimization and ab initio molecular dynamic simulation for metalloproteins of any size.

Structure of tRNA-Modifying Enzyme TiaS and Motions of Its Substrate Binding Zinc Ribbon

The accurate modification of the tRNA^Ile anticodon wobble cytosine 34 is critical for AUA decoding in protein synthesis. Archaeal tRNA^Ile2 cytosine 34 is modified with agmatine in the presence of ATP by TiaS (tRNA^Ile2 agmatidine synthetase). However, no structure of apo-form full-length TiaS is available currently. Here, the crystal structures of apo TiaS and a complex of TiaS-agmatine-AMPPCP-Mg are presented, with properly folded zinc ribbon and Cys4-zinc coordination identified. Compared with tRNA^Ile2-bound form, the architecture of apo TiaS shows a totally different conformation of zinc ribbon. Molecular dynamics simulations of the docking complex between free-state TiaS and tRNA^Ile2 suggest that zinc ribbon domain is capable of performing large-scale motions to sample substrate binding-competent conformation. Principle component analysis and normal mode analysis show consistent results about the relative directionality of functionally correlated zinc ribbon motions. Apo TiaS and TiaS-agmatine-AMPPCP-Mg/TiaS-AMPCPP-Mg complex structures capture two snapshots of the flexible ATP-Mg binding p2loop step-by-step stabilization. Research from this study provides new insight into TiaS functional mechanism and the dynamic feature of zinc ribbons.

Prediction of Protein-compound Binding Energies from Known Activity Data: Docking-score-based Method and its Applications

We used protein-compound docking simulations to develop a structure-based quantitative structure-activity relationship (QSAR) model. The prediction model used docking scores as descriptors. The binding free energy was approximated by a weighted average of docking scores for multiple proteins. This approximation was based on a pharmacophore model of receptor pockets and compounds. The weights of the docking scores were restricted to small values to avoid unrealistic weights by a regularization term. Additional outlier elimination improved the results. We applied this method to two groups of targets. The first target was the kinase family. The cross-validation results of 107 kinase proteins showed that the RMSE of predicted binding free energies was 1.1 kcal/mol. The second target was the matrix metalloproteinase (MMP) family, which has been difficult for docking programs. MMPs require metal-binding groups in their inhibitor structures in many cases. A quantum effect contributes to the metal-ligand interaction. Despite this difficulty, the present method worked well for the MMPs. This method showed that the RMSE of predicted binding free energies was 1.1 kcal/mol. In comparison, with the original docking method the RMSE was 1.7 kcal/mol. The results suggest that the present QSAR model should be applied to general target proteins.

Force Field Parametrization of Metal Ions from Statistical Learning Techniques

A novel statistical procedure has been developed to optimize the parameters of nonbonded force fields of metal ions in soft matter. The criterion for the optimization is the minimization of the deviations from ab initio forces and energies calculated for model systems. The method exploits the combination of the linear ridge regression and the cross-validation techniques with the differential evolution algorithm. Wide freedom in the choice of the functional form of the force fields is allowed since both linear and nonlinear parameters can be optimized. In order to maximize the information content of the data employed in the fitting procedure, the composition of the training set is entrusted to a combinatorial optimization algorithm which maximizes the dissimilarity of the included instances. The methodology has been validated using the force field parametrization of five metal ions (Zn²⁺, Ni²⁺, Mg²⁺, Ca²⁺, and Na⁺) in water as test cases.

Metal Ion Modeling Using Classical Mechanics

Metal ions play significant roles in numerous fields including chemistry, geochemistry, biochemistry, and materials science. With computational tools increasingly becoming important in chemical research, methods have emerged to effectively face the challenge of modeling metal ions in the gas, aqueous, and solid phases. Herein, we review both quantum and classical modeling strategies for metal ion-containing systems that have been developed over the past few decades. This Review focuses on classical metal ion modeling based on unpolarized models (including the nonbonded, bonded, cationic dummy atom, and combined models), polarizable models (e.g., the fluctuating charge, Drude oscillator, and the induced dipole models), the angular overlap model, and valence bond-based models. Quantum mechanical studies of metal ion-containing systems at the semiempirical, ab initio, and density functional levels of theory are reviewed as well with a particular focus on how these methods inform classical modeling efforts. Finally, conclusions and future prospects and directions are offered that will further enhance the classical modeling of metal ion-containing systems.

VFFDT: A New Software for Preparing AMBER Force Field Parameters for Metal-Containing Molecular Systems

Force fields are fundamental to molecular dynamics simulations. However, the incompleteness of force field parameters has been a long-standing problem, especially for metal-related systems. In our previous work, we adopted the Seminario method based on the Hessian matrix to systematically derive the zinc-related force field parameters for AMBER. In this work, in order to further simplify the whole protocol, we have implemented a user-friendly Visual Force Field Derivation Toolkit (VFFDT) to derive the force field parameters via simply clicking on the bond or angle in the 3D viewer, and we have further extended our previous program to support the Hessian matrix output from a variety of quantum mechanics (QM) packages, including Gaussian 03/09, ORCA 3.0, QChem, GAMESS-US, and MOPAC 2009/2012. In this toolkit, a universal VFFDT XYZ file format containing the raw Hessian matrix is available for all of the QM packages, and an instant force field parametrization protocol based on a semiempirical quantum mechanics (SQM) method is introduced. The new function that can automatically obtain the relevant parameters for zinc, copper, iron, etc., which can be exported in AMBER Frcmod format, has been added. Furthermore, our VFFDT program can read and write files in AMBER Prepc, AMBER Frcmod, and AMBER Mol2 format and can also be used to customize, view, copy, and paste the force field parameters in the context of the 3D viewer, which provides utilities complementary to ANTECHAMBER, MCPB, and MCPB.py in the AmberTools.

Thiol versus hydroxamate as zinc binding group in HDAC inhibition: An ab initio QM/MM molecular dynamics study

Zinc-dependent histone deacetylases (HDACs) play a critical role in transcriptional repression and gene silencing, and are among the most attractive targets for the development of new therapeutics against cancer and various other diseases. Two HDAC inhibitors have been approved by FDA as anti-cancer drugs: one is SAHA whose hydroxamate is directly bound to zinc, the other is FK228 whose active form may use thiol as the zinc binding group. In spite of extensive studies, it remains to be ambiguous regarding how thiol and hydroxamate are bound to the zinc active site of HDACs. In this work, our computational approaches center on Born-Oppenheimer ab initio quantum mechanical/molecular mechanical (QM/MM) molecular dynamics with umbrella sampling, which allow for modeling of the zinc active site with reasonable accuracy while properly including dynamics and effects of protein environment. Meanwhile, an improved short-long effective function (SLEF2) to describe non-bonded interactions between zinc and other atoms has been employed in initial MM equilibrations. Our ab initio QM/MM MD simulations have confirmed that hydroxamate is neutral when it is bound to HDAC8, and found that thiol is deprotonated when directly bound to zinc in the HDAC active site. By comparing thiol and hydroxamate, our results elucidated the differences in their binding environment in the HDAC active sites, and emphasized the importance of the linker design to achieve more specific binding toward class IIa HDACs.

Development and Application of a Nonbonded Cu(2+) Model That Includes the Jahn-Teller Effect

Metal ions are both ubiquitous to and crucial in biology. In classical simulations, they are typically described as simple van der Waals spheres, making it difficult to provide reliable force field descriptions for them. An alternative is given by nonbonded dummy models, in which the central metal atom is surrounded by dummy particles that each carry a partial charge. While such dummy models already exist for other metal ions, none is available yet for Cu(2+) because of the challenge to reproduce the Jahn-Teller distortion. This challenge is addressed in the current study, where, for the first time, a dummy model including a Jahn-Teller effect is developed for Cu(2+). We successfully validate its usefulness by studying metal binding in two biological systems: the amyloid-β peptide and the mixed-metal enzyme superoxide dismutase. We believe that our parameters will be of significant value for the computational study of Cu(2+)-dependent biological systems using classical models.

Developing accurate molecular mechanics force fields for conjugated molecular systems

A rapid method to parameterize the intramolecular component of classical force fields is proposed and applied to a molecular semiconductor, oligomers of conjugated polymers and a biological chromophore.

Parametrization of DFTB3/3OB for magnesium and zinc for chemical and biological applications

We report the parametrization of the approximate density functional theory, DFTB3, for magnesium and zinc for chemical and biological applications. The parametrization strategy follows that established in previous work that parametrized several key main group elements (O, N, C, H, P, and S). This 3OB set of parameters can thus be used to study many chemical and biochemical systems. The parameters are benchmarked using both gas-phase and condensed-phase systems. The gas-phase results are compared to DFT (mostly B3LYP), ab initio (MP2 and G3B3), and PM6, as well as to a previous DFTB parametrization (MIO). The results indicate that DFTB3/3OB is particularly successful at predicting structures, including rather complex dinuclear metalloenzyme active sites, while being semiquantitative (with a typical mean absolute deviation (MAD) of ∼3–5 kcal/mol) for energetics. Single-point calculations with high-level quantum mechanics (QM) methods generally lead to very satisfying (a typical MAD of ∼1 kcal/mol) energetic properties. DFTB3/MM simulations for solution and two enzyme systems also lead to encouraging structural and energetic properties in comparison to available experimental data. The remaining limitations of DFTB3, such as the treatment of interaction between metal ions and highly charged/polarizable ligands, are also discussed.

AutoDock4(Zn): an improved AutoDock force field for small-molecule docking to zinc metalloproteins

Zinc is present in a wide variety of proteins and is important in the metabolism of most organisms. Zinc metalloenzymes are therapeutically relevant targets in diseases such as cancer, heart disease, bacterial infection, and Alzheimer's disease. In most cases a drug molecule targeting such enzymes establishes an interaction that coordinates with the zinc ion. Thus, accurate prediction of the interaction of ligands with zinc is an important aspect of computational docking and virtual screening against zinc containing proteins. We have extended the AutoDock force field to include a specialized potential describing the interactions of zinc-coordinating ligands. This potential describes both the energetic and geometric components of the interaction. The new force field, named AutoDock4Zn, was calibrated on a data set of 292 crystal complexes containing zinc. Redocking experiments show that the force field provides significant improvement in performance in both free energy of binding estimation as well as in root-mean-square deviation from the crystal structure pose. The new force field has been implemented in AutoDock without modification to the source code.

Taking into Account the Ion-induced Dipole Interaction in the Nonbonded Model of Ions

Metal ions exist in almost half of the proteins in the protein databank and they serve as structural, electron-transfer and catalytic elements in the metabolic processes of organisms. Molecular Dynamics (MD) simulation is a powerful tool that provides information about biomolecular systems at the atomic level. Coupled with the growth in computing power, algorithms like the Particle Mesh Ewald (PME) method have become the accepted standard when dealing with long-range interactions in MD simulations. The nonbonded model of metal ions consists of an electrostatic plus 12-6 Lennard Jones (LJ) potential and is used largely because of its speed relative to more accurate models. In previous work we found that ideal parameters do not exist that reproduce several experimental properties for M(II) ions simultaneously using the nonbonded model coupled with the PME method due to the underestimation of metal ion-ligand interactions. Via a consideration of the nature of the nonbonded model, we proposed that the observed error largely arises from overlooking charge-induced dipole interactions. The electrostatic plus 12-6 LJ potential model works reasonably well for neutral systems but does struggle with more highly charged systems. In the present work we designed and parameterized a new nonbonded model for metal ions by adding a 1/r4 term to the 12-6 model. We call it the 12-6-4 LJ-type nonbonded model due to its mathematical construction. Parameters were determined for 16 +2 metal ions for the TIP3P, SPC/E and TIP4PEW water models. The final parameters reproduce the experimental hydration free energies (HFE), ion-oxygen distances (IOD) in the first solvation shell and coordination numbers (CN) accurately for the metal ions investigated. Preliminary tests on MgCl2 at different concentrations in aqueous solution and Mg2+--nucleic acid systems show reasonable results suggesting that the present parameters can work in mixed systems. The 12-6-4 LJ-type nonbonded model is readily adopted into standard force fields like AMBER, CHARMM and OPLS-AA with only a modest computational overhead. The new nonbonded model doesn't consider charge-transfer effects explicitly and, hence, may not suitable for the simulation of systems where charge-transfer effects play a decisive role.

Rational Design of Particle Mesh Ewald Compatible Lennard-Jones Parameters for +2 Metal Cations in Explicit Solvent

Metal ions play significant roles in biological systems. Accurate molecular dynamics (MD) simulations on these systems require a validated set of parameters. Although there are more detailed ways to model metal ions, the nonbonded model, which employs a 12-6 Lennard-Jones (LJ) term plus an electrostatic potential is still widely used in MD simulations today due to its simple form. However, LJ parameters have limited transferability due to different combining rules, various water models and diverse simulation methods. Recently, simulations employing a Particle Mesh Ewald (PME) treatment for long-range electrostatics have become more and more popular owing to their speed and accuracy. In the present work we have systematically designed LJ parameters for 24 +2 metal (M(II)) cations to reproduce different experimental properties appropriate for the Lorentz-Berthelot combining rules and PME simulations. We began by testing the transferability of currently available M(II) ion LJ parameters. The results showed that there are differences between simulations employing Ewald summation with other simulation methods and that it was necessary to design new parameters specific for PME based simulations. Employing the thermodynamic integration (TI) method and performing periodic boundary MD simulations employing PME, allowed for the systematic investigation of the LJ parameter space. Hydration free energies (HFEs), the ion-oxygen distance in the first solvation shell (IOD) and coordination numbers (CNs) were obtained for various combinations of the parameters of the LJ potential for four widely used water models (TIP3P, SPC/E, TIP4P and TIP4PEW). Results showed that the three simulated properties were highly correlated. Meanwhile, M(II) ions with the same parameters in different water models produce remarkably different HFEs but similar structural properties. It is difficult to reproduce various experimental values simultaneously because the nonbonded model underestimates the interaction between the metal ions and water molecules at short range. Moreover, the extent of underestimation increases successively for the TIP3P, SPC/E, TIP4PEW and TIP4P water models. Nonetheless, we fitted a curve to describe the relationship between ε (the well depth) and radius (Rmin/2) from experimental data on noble gases to facilitate the generation of the best possible compromise models. Hence, by targeting different experimental values, we developed three sets of parameters for M(II) cations for three different water models (TIP3P, SPC/E and TIP4PEW). These parameters we feel represent the best possible compromise that can be achieved using the nonbonded model for the ions in combination with simple water models. From a computational uncertainty analysis we estimate that the uncertainty in our computed HFEs is on the order of ±1kcal/mol. Further improvements will require more advanced non-bonded models likely with inclusion of polarization.

Solution NMR refinement of a metal ion bound protein using metal ion inclusive restrained molecular dynamics methods

Correctly calculating the structure of metal coordination sites in a protein during the process of nuclear magnetic resonance (NMR) structure determination and refinement continues to be a challenging task. In this study, we present an accurate and convenient means by which to include metal ions in the NMR structure determination process using molecular dynamics (MD) simulations constrained by NMR-derived data to obtain a realistic and physically viable description of the metal binding site(s). This method provides the framework to accurately portray the metal ions and its binding residues in a pseudo-bond or dummy-cation like approach, and is validated by quantum mechanical/molecular mechanical (QM/MM) MD calculations constrained by NMR-derived data. To illustrate this approach, we refine the zinc coordination complex structure of the zinc sensing transcriptional repressor protein Staphylococcus aureus CzrA, generating over 130 ns of MD and QM/MM MD NMR-data compliant sampling. In addition to refining the first coordination shell structure of the Zn(II) ion, this protocol benefits from being performed in a periodically replicated solvation environment including long-range electrostatics. We determine that unrestrained (not based on NMR data) MD simulations correlated to the NMR data in a time-averaged ensemble. The accurate solution structure ensemble of the metal-bound protein accurately describes the role of conformational sampling in allosteric regulation of DNA binding by zinc and serves to validate our previous unrestrained MD simulations of CzrA. This methodology has potentially broad applicability in the structure determination of metal ion bound proteins, protein folding and metal template protein-design studies.

A simple but effective modeling strategy for structural properties of non-heme Fe(II) sites in proteins: test of force field models and application to proteins in the AlkB family

To facilitate computational study of proteins in the AlkB family and related α-ketoglutarate/Fe(II)-dependent dioxygenases, we have tested a simple modeling strategy for the non-heme Fe(II) site in which the iron is represented by a simple +2 point charge with Lennard-Jones parameters. Calculations for an AlkB active site model in the gas phase and ∼150 ns molecular dynamics (MD) simulations for two enzyme-dsDNA complexes (E. coli AlkB-dsDNA and ABH2-dsDNA) suggest that this simple modeling strategy provides a satisfactory description of structural properties of the Fe(II) site in AlkB enzymes, provided that care is exercised to control the binding mode of carboxylate (Asp) to the iron. MD simulations using the model for AlkB-dsDNA and ABH2-dsDNA systems find that although the structural features for the latter are overall in good agreement with the crystal structure, the dsDNA, and AlkB-dsDNA interface undergo substantial changes during the MD simulations from the crystal structure. Even for ABH2, new interactions form between a long loop region and dsDNA upon structural relaxation of the loop, supporting the role of this loop in DNA binding despite the lack of interactions between them in the crystal structure. Analysis of DNA backbone torsional distributions helps identify regions that adopt strained conformations. Collectively, the results highlight that crystal packing may have a significant impact on the structure of protein-DNA complexes; the simulations also provide additional insights regarding why AlkB and ABH2 prefer single-strand and double-strand DNA, respectively, as substrate.

Structures and free energy landscapes of aqueous zinc(II)-bound amyloid-β(1-40) and zinc(II)-bound amyloid-β(1-42) with dynamics

Binding of divalent metal ions with intrinsically disordered fibrillogenic proteins, such as amyloid-β (Aβ), influences the aggregation process and the severity of neurodegenerative diseases. The Aβ monomers and oligomers are the building blocks of the aggregates. In this work, we report the structures and free energy landscapes of the monomeric zinc(II)-bound Aβ40 (Zn:Aβ40) and zinc(II)-bound Aβ42 (Zn:Aβ42) intrinsically disordered fibrillogenic metallopeptides in an aqueous solution by utilizing an approach that employs first principles calculations and parallel tempering molecular dynamics simulations. The structural and thermodynamic properties, including the secondary and tertiary structures and conformational Gibbs free energies of these intrinsically disordered metallopeptide alloforms, are presented. The results show distinct differing characteristics for these metallopeptides. For example, prominent β-sheet formation in the N-terminal region (Asp1, Arg5, and Tyr10) of Zn:Aβ40 is significantly decreased or lacking in Zn:Aβ42. Our findings indicate that blocking multiple reactive residues forming abundant β-sheet structure located in the central hydrophobic core and C-terminal regions of Zn:Aβ42 via antibodies or small organic molecules might help to reduce the aggregation of Zn(II)-bound Aβ42. Furthermore, we find that helix formation increases but β-sheet formation decreases in the C-terminal region upon Zn(II) binding to Aβ. This depressed β-sheet formation in the C-terminal region (Gly33-Gly38) in monomeric Zn:Aβ42 might be linked to the formation of amorphous instead of fibrillar aggregates of Zn:Aβ42.

Simulations of allosteric motions in the zinc sensor CzrA

The zinc sensing transcriptional repressor Staphylococcus aureus CzrA represents an excellent model system to understand how metal sensor proteins maintain cellular metal homeostasis. Zn(II) binding induces a quaternary structural switch from a "closed" conformation to a more "open" conformation, reducing the DNA binding affinity by 4 orders of magnitude. In this study, we use classical molecular dynamics and quantum mechanical/molecular mechanical molecular dynamics simulations to investigate the molecular basis for the large conformational motions and allosteric coupling free energy (~6 kcal/mol) associated with Zn(II) binding. Our simulations successfully capture the closed to open allosteric switching in DNA bound CzrA on Zn(II) binding. They reveal that zinc binding quenches global conformational sampling by CzrA, whereas DNA binding enhances the mobility of residues in the allosteric metal binding sites. These findings are in close agreement with experiments. We also identify networks of residues involved in correlated and anticorrelated motions that connect the metal binding and DNA binding sites. Our analysis of the essential dynamics shows metal ion binding to be the primary driving force for the quaternary structural change in CzrA. We also show that Zn(II) binding limits the conformational space sampled by CzrA and causes the electrostatic surface potential at the DNA binding interface to become less favorable toward DNA binding. Finally, our simulations provide strong support for a proposed hydrogen-bonding pathway that physically connects the metal binding residue, His97, to the DNA binding interface through the αR helix that is present only in the Zn(II)-bound state. Overall, our simulations provide molecular-level insights into the mechanism of allosteric regulation by CzrA and demonstrate the importance of protein motion in its biological activity.