Interaction Energies in Complexes of Zn and Amino Acids: A Comparison of Ab Initio and Force Field Based Calculations

Parameterization of a Fluctuating Charge Model for Complexes Containing 3d Transition Metals

Metalloproteins widely exist in biology, playing pivotal roles in diverse life processes. Meanwhile, molecular dynamics (MD) simulations based on classical force fields has emerged as an important tool in scientific research. Partial charges are critical parameters within classical force fields and usually derived from quantum mechanical (QM) calculations. However, QM calculations are often time-consuming and prone to basis set dependence. Alternatively, fluctuating charge (FQ) models offer another avenue for partial charge derivation, which has significant speed advantages and can be used for large-scale screening. Building upon our previous work, which introduced an FQ model for zinc-containing complexes, herein we extend this model to include additional 3d transition metals which are important to the life sciences, namely chromium, manganese, iron, cobalt, and nickel. Employing CM5 charges as target for parametrization, our FQ model accurately reproduces partial charges for 3d metal complexes featuring biologically relevant ligands. Furthermore, by using atomic charges derived by our FQ model, MD simulations have been performed. These charges showed excellent performance in simulating proteomic metal sites housing multiple metal ions, specifically, a metalloprotein containing an iron-sulfur cluster and another containing a dimanganese metal site, showcasing comparable performance to those of RESP charges. We anticipate that our study can accelerate the parametrization of atomic charges for metalloproteins featuring 3d transition metals, thereby facilitating simulations of relevant systems.

Unravelling the potential of L-carnosine analog-based nano-assemblies as pH-responsive therapeutics in treating glioma: an in vitro perspective

Self-assembled small peptide-based nanoparticles (NPs) constitute a major section of the biomimetic smart NPs owing to their excellent compatibility and minimal adverse effects in the biological system. Here, we have designed a modified L-carnosine dipeptide analog, "Fmoc-β-Ala-L-His-(Trt)-o-methyl formate", which was assembled along with a modified single amino acid, Fmoc-Arg-(Pbf)-OH and zinc ions to form stable and mono-dispersed L-carnosine analog NPs (CaNPs) with inherent anti-cancer properties. Furthermore, the CaNPs demonstrated an average size of ∼200 nm, making them suitable to invade the tumor site by following the enhanced permeability and retention (EPR) effect. Our studies depicted a remarkable cancer cell killing ability of the NPs of ∼82% in C6 glioma cells. Thereafter, cellular investigations were performed in C6 cells to analyze the influence of the NPs on cellular cytoskeleton integrity by using a phalloidin assay and anti-cancer efficacy by using calcein AM/PI, and an apoptosis assay further indicated their anti-cancer effect. Additionally, the NPs negatively impacted the ability of C6 cells to migrate across a premade scratch (∼44% wound closure) demonstrating their tendency to halt cancer cell migration and metastasis. Also, our NPs depicted ∼19.51 ± 0.17% permeability across the bEnd.3 transwell model establishing their BBB penetrability. Collectively, our results could positively implicate the successful anti-cancer potential of the minimalistic, biologically compliant, L-carnosine analog (Ca)-based nanostructures in glioma.

QM/MM-Based Energy Decomposition Analysis Method for Large Systems

In this work, a QM/MM-based EDA method, called GKS-EDA(QM/MM), is proposed. As an extension of GKS-EDA, this scheme divides the total interaction energy into electrostatic, exchange-repulsion, polarization, and correlation/dispersion terms. GKS-EDA(QM/MM) can be applied to describe the interactions of large-scale systems combined with various QM/MM platforms. By using the examples of a hydrated hydronium ion complex in water solution, the barnase-barstar complex, and MMP-13-pyrimidinetrione in a metalloprotein, the capability of GKS-EDA(QM/MM) for various interactions in large systems is validated.

Development of a Fluctuating Charge Model for Zinc-Containing Metalloproteins

Metalloproteins widely exist in biology and play important roles in various processes. To accurately simulate metalloprotein systems, modeling polarization and charge transfer effects is vital. The fluctuating charge (FQ) model can efficiently generate atomic charges and simulate the charge transfer effect; it has been developed for a wide range of applications, but few models have been specifically tailored for metalloproteins. In this study, we present a fluctuating charge model specifically for zinc-containing metalloproteins based on the extended charge equilibration (EQeq) scheme. Our model was parametrized to reproduce CM5 charges instead of RESP/CHELPG charges because the former is less dependent on the conformation or basis set, does not suffer from unphysical charges for buried atoms, and is still being able to well reproduce the molecular dipoles. During our study, we found that adding the Pauling-bond-order-like term (referred to as the "+C term" in a previous study) between the zinc ion and ligating atoms significantly improves the model's performance. Although our model was trained for four-coordinated zinc sites only, our results indicated it can well describe the atomic charges in diverse zinc sites. Morever, our model was used to generate partial charges for the metal sites in three different zinc-containing metalloproteins (with four-, five-, and six-coordinated metal sites, respectively). These charges exhibited performance comparable to that of the RESP charges in molecular dynamics (MD) simulations. Additional tests indicated our model could also well reproduce the CM5 charges when geometric changes were involved. Those results indicate that our model can efficiently calculate the atomic charges for metal sites and well simulate the charge transfer effect, which marks an important step toward developing versatile polarizable force fields for metalloproteins.

Thermodynamics of Metal-Acetate Interactions

Metal ions play crucial roles in protein- and ligand-mediated interactions. They not only act as catalysts to facilitate biological processes but are also important as protein structural elements. Accurately predicting metal ion interactions in computational studies has always been a challenge, and various methods have been suggested to improve these interactions. One such method is the 12-6-4 Lennard-Jones (LJ)-type nonbonded model. Using this model, it has been possible to successfully reproduce the experimental properties of metal ions in aqueous solution. The model includes induced dipole interactions typically ignored in the standard 12-6 LJ nonbonded model. In this we expand the applicability of this model to metal ion-carboxylate interactions. Using 12-6-4 parameters that reproduce the solvation free energies of the metal ions leads to an overestimation of metal ion-acetate interactions, thus, prompting us to fine-tune the model to specifically handle the latter. We also show that the standard 12-6 LJ model significantly falls short in reproducing the experimental binding free energy between acetate and 11 metal ions (Ni(II), Mg(II), Cu(II), Zn(II), Co(II), Cu(I), Fe(II), Mn(II), Cd(II), Ca(II), and Ag(I)). In this study, we describe optimized C4 parameters for the 12-6-4 LJ nonbonded model to be used with three widely employed water models (Transferable Intermolecular Potential with 3 Points (TIP3P), Simple Point Charge Extended (SPC/E), and Optimal Point Charge (OPC) water models). These parameters can accurately match the experimental binding free energy between 11 metal ions and acetate. These parameters can be applied to the study of metalloproteins and transition metal ion channels and transporters, as acetate serves as a representative of the negatively charged amino acid side chains from aspartate and glutamate.

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.

Multiscale QM/MM Simulations Identify the Roles of Asp239 and 1-OH···Nucleophile in Transition State Stabilization in Arabidopsis thaliana Cell-Wall Invertase 1

Arabidopsis thaliana cell-wall invertase 1 (AtCWIN1), a key enzyme in sucrose metabolism in plants, catalyzes the hydrolysis of sucrose into fructose and glucose. AtCWIN1 belongs to the glycoside hydrolase GH-J clan, where two carboxylate residues (Asp23 and Glu203 in AtCWIN1) are well documented as a nucleophile and an acid/base catalyst. However, details at the atomic level about the role of neighboring residues and enzyme-substrate interactions during catalysis are not fully understood. Here, quantum mechanical/molecular mechanical (QM/MM) free-energy simulations were carried out to clarify the origin of the observed decreased rates in Asp239Ala, Asp239Asn, and Asp239Phe in AtCWIN1 compared to the wild type and delineate the role of Asp239 in catalysis. The glycosylation and deglycosylation steps were considered in both wild type and mutants. Deglycosylation is predicted to be the rate-determining step in the reaction, with a calculated overall free-energy barrier of 15.9 kcal/mol, consistent with the experimental barrier (15.3 kcal/mol). During the reaction, the -1 furanosyl ring underwent a conformational change corresponding to 3E ↔ [E2]⧧ ↔ 1E according to the nomenclature of saccharide structures along the full catalytic reaction. Asp239 was found to stabilize not only the transition state but also the fructosyl-enzyme intermediate, which explains findings from previous structural and mutagenesis experiments. The 1-OH···nucleophile interaction has been found to provide an important contribution to the transition state stabilization, with a contribution of ∼7 kcal/mol, and affected glycosylation more significantly than deglycosylation. This study provides molecular insights that improve the current understanding of sucrose binding and hydrolysis in members of clan GH-J, which may benefit protein engineering research. Finally, a rationale on the sucrose inhibitor configuration in chicory 1-FEH IIa, proposed a long time ago in the literature, is also provided based on the QM/MM calculations.

Modeling of minimal systems based on ATP-Zn coordination for chemically fueled self-assembly

Following nature's example, there is currently strong interest in using adenosine 5'-triphosphate (ATP) as a fuel for the self-assembly of functional materials with transient/non-equilibrium behaviours. These hold great promise for applications, e.g. in catalysis and drug delivery. In a recent seminal work [Maiti et al., Nat. Chem., 2016, 8, 725], binding of ATP to the metallosurfactant zinc hexadecyl-1,4,7-triazacyclononane ([ZnC₁₆ TACN]²⁺) was exploited to produce ATP-fueled transient vesicles. Crucial to the complex formation is the ability of ATP to bind to the metal ion. As a first step to unveil the key elements underlying this process, we investigate the interaction of ATP with Zn²⁺ and with methyl-1,4,7-triazacyclononane ([ZnCH₃ TACN]²⁺), using all-atom molecular dynamics simulations. The free energy landscape of the complex formation is sampled using well-tempered metadynamics with three collective variables, corresponding to the coordination numbers of Zn²⁺ with the oxygen atoms of the three phosphate groups. We find that the structure of the ternary complex is controlled by direct triphosphate coordination to zinc, with a minor role played by the interactions between ATP and CH₃ TACN which, however, may be important for the build-up of supramolecular assemblies.

Estimating the Gibbs Hydration Energies of Actinium and Trans-Plutonium Actinides

The use of actinides for medical, scientific and technological purposes has gained momentum in the recent years. This creates a need to understand their interactions with biomolecules, both at the interface and as they become complexed. Calculation of the Gibbs binding energies of the ions to biomolecules, i. e., the Gibbs energy change associated with a transfer of an ion from the water phase to its binding site, could help to understand the actinides' toxicities and to design agents that bind them with high affinities. To this end, there is a need to obtain accurate reference values for actinide hydration, that for most actinides are not available from experiment. In this study, a set of ionic radii is developed that enables future calculations of binding energies for Pu³⁺ and five actinides with renewed scientific and technological interest: Ac³⁺ , Am³⁺ , Cm³⁺ , Bk³⁺ and Cf³⁺ . Reference hydration energies were calculated using quantum chemistry and ion solvation theory and agree well for all ions except Ac³⁺ , where ion solvation theory seems to underestimate the magnitude of the Gibbs hydration energy. The set of radii and reference energies that are presented here provide means to calculate binding energies for actinides and biomolecules.

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.

Exploring human porphobilinogen synthase metalloprotein by quantum biochemistry and evolutionary methods

Previous studies have shown the porphobilinogen synthase (PBGS) zinc-binding mechanism and its conservation among the living cells. However, the precise molecular interaction of zinc with the active center of the enzyme is unknown. In particular, quantum chemistry techniques within the density functional theory (DFT) framework have been the key methodology to describe metalloproteins, when one is looking for a compromise between accuracy and computational feasibility. Considering this, we used DFT-based models within the molecular fractionation with conjugate caps scheme to evaluate the binding energy features of zinc interacting with the human PBGS. Besides, phylogenetic and clustering analyses were successfully employed in extracting useful information from protein sequences to identify groups of conserved residues that build the ions-binding site. Our results also report a conservative assessment of the relevant amino acids, as well as the benchmark analysis of the calculation models used. The most relevant intermolecular interactions in Zn2+-PBGS are due to the amino acids CYS0122, CYS0124, CYS0132, ASP0169, SER0168, ARG0221, HIS0131, ASP0120, GLY0133, VAL0121, ARG0209, and ARG0174. Among these residues, we highlighted ASP0120, GLY0133, HIS0131, SER0168, and ARG0209 by co-occurring in all clusters generated by unsupervised clustering analysis. On the other hand, the triple cysteines at 2.5 Å from zinc (CYS0122, CYS0124, and CYS0132) have the highest energy attraction and are absent in the taxa Viridiplantae, Sar, Rhodophyta, and some Bacteria. Additionally, the performance of the DFT-based models shows that the processing time-dependence is more associated with the choice of the basis set than the exchange-correlation functional.

Dynamical Oligomerisation of Histidine Rich Intrinsically Disordered ProteinS Is Regulated through Zinc-Histidine Interactions

Intrinsically disordered proteins (IDPs) can form functional oligomers and in some cases, insoluble disease related aggregates. It is therefore vital to understand processes and mechanisms that control pathway distribution. Divalent cations including Zn²⁺ can initiate IDP oligomerisation through the interaction with histidine residues but the mechanisms of doing so are far from understood. Here we apply a multi-disciplinary approach using small angle X-ray scattering, nuclear magnetic resonance spectroscopy, calorimetry and computations to show that that saliva protein Histatin 5 forms highly dynamic oligomers in the presence of Zn²⁺. The process is critically dependent upon interaction between Zn²⁺ ions and distinct histidine rich binding motifs which allows for thermodynamic switching between states. We propose a molecular mechanism of oligomerisation, which may be generally applicable to other histidine rich IDPs. Finally, as Histatin 5 is an important saliva component, we suggest that Zn²⁺ induced oligomerisation may be crucial for maintaining saliva homeostasis.

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.

Study of interactions between metal ions and protein model compounds by energy decomposition analyses and the AMOEBA force field

The interactions between metal ions and proteins are ubiquitous in biology. The selective binding of metal ions has a variety of regulatory functions. Therefore, there is a need to understand the mechanism of protein-ion binding. The interactions involving metal ions are complicated in nature, where short-range charge-penetration, charge transfer, polarization, and many-body effects all contribute significantly, and a quantitative description of all these interactions is lacking. In addition, it is unclear how well current polarizable force fields can capture these energy terms and whether these polarization models are good enough to describe the many-body effects. In this work, two energy decomposition methods, absolutely localized molecular orbitals and symmetry-adapted perturbation theory, were utilized to study the interactions between Mg²⁺/Ca²⁺ and model compounds for amino acids. Comparison of individual interaction components revealed that while there are significant charge-penetration and charge-transfer effects in Ca complexes, these effects can be captured by the van der Waals (vdW) term in the AMOEBA force field. The electrostatic interaction in Mg complexes is well described by AMOEBA since the charge penetration is small, but the distance-dependent polarization energy is problematic. Many-body effects were shown to be important for protein-ion binding. In the absence of many-body effects, highly charged binding pockets will be over-stabilized, and the pockets will always favor Mg and thus lose selectivity. Therefore, many-body effects must be incorporated in the force field in order to predict the structure and energetics of metalloproteins. Also, the many-body effects of charge transfer in Ca complexes were found to be non-negligible. The absorption of charge-transfer energy into the additive vdW term was a main source of error for the AMOEBA many-body interaction energies.

Computer simulations of alkali-acetate solutions: Accuracy of the forcefields in difference concentrations

When proteins are solvated in electrolyte solutions that contain alkali ions, the ions interact mostly with carboxylates on the protein surface. Correctly accounting for alkali-carboxylate interactions is thus important for realistic simulations of proteins. Acetates are the simplest carboxylates that are amphipathic, and experimental data for alkali acetate solutions are available and can be compared with observables obtained from simulations. We carried out molecular dynamics simulations of alkali acetate solutions using polarizable and non-polarizable forcefields and examined the ion-acetate interactions. In particular, activity coefficients and association constants were studied in a range of concentrations (0.03, 0.1, and 1M). In addition, quantum-mechanics (QM) based energy decomposition analysis was performed in order to estimate the contribution of polarization, electrostatics, dispersion, and QM (non-classical) effects on the cation-acetate and cation-water interactions. Simulations of Li-acetate solutions in general overestimated the binding of Li⁺ and acetates. In lower concentrations, the activity coefficients of alkali-acetate solutions were too high, which is suggested to be due to the simulation protocol and not the forcefields. Energy decomposition analysis suggested that improvement of the forcefield parameters to enable accurate simulations of Li-acetate solutions can be achieved but may require the use of a polarizable forcefield. Importantly, simulations with some ion parameters could not reproduce the correct ion-oxygen distances, which calls for caution in the choice of ion parameters when protein simulations are performed in electrolyte solutions.

Membrane-Ion Interactions

Biomembranes assemble and operate at the interface with electrolyte solutions. Interactions between ions in solutions and the lipid affect the membrane structure, dynamics and electrostatic potential. In this article, I review some of the experimental and computational methods that are used to study membrane–ions interactions. Experimental methods that account for membrane–ion interactions directly and indirectly are presented first. Then, studies in which molecular dynamics simulations were used to gain an understanding of membrane–ion interactions are surveyed. Finally, the current view on membrane–ion interactions and their significance is briefly discussed.