Force field independent metal parameters using a nonbonded dummy model

Assessing Structural Determinants of Zn2+ Binding to Human HV1 via Multiple MD Simulations

Voltage-gated proton channels (H_V1) are essential for various physiological tasks but are strongly inhibited by Zn²⁺ cations. Some determinants of Zn²⁺ binding have been elucidated experimentally and in computational studies. However, the results have always been interpreted under the assumption that Zn²⁺ binds to monomeric H_V1 despite evidence that H_V1 expresses as a dimer and that the dimer has a higher affinity for zinc than the monomer and experimental data that suggest coordination in the dimer interface. The results of former studies are also controversial, e.g., supporting either one single or two binding sites. Some structural determinants of the binding are still elusive. We performed a series of molecular dynamics simulations to address different structures of the human proton channel, the monomer and two plausible dimer conformations, to compare their respective potential to interact with and bind Zn²⁺ via the essential histidines. The series consisted of several copies of the system to generate independent trajectories and increase the significance compared to a single simulation. The amount of time simulated totals 29.9 μs for 126 simulations of systems comprising ∼59,000 to ∼187,000 atoms. Our approach confirms the existence of two binding sites in monomeric and dimeric human H_V1. The dimer interface is more efficient for attracting and binding Zn²⁺ via the essential histidines than the monomer or a dimer with the histidines in the periphery. The higher affinity is due to the residues in the dimer interface that create an attractive electrostatic potential funneling the zinc cations toward the binding sites.

Evidence for an egg-box-like structure in iron(ii)–polygalacturonate hydrogels: a combined EXAFS and molecular dynamics simulation study

The coordination of Fe(ii) with polygalacturonic acid (polyGalA) in Fe(ii)–polyGalA hydrogels exhibits an octahedral geometry that follows the “egg-box model”.

Molecular dynamics simulations of alkaline earth metal ions binding to DNA reveal ion size and hydration effects

Classical molecular dynamics simulations reveal size-dependent trends of alkaline earth metal ions binding to DNA are due to ion size and hydration behavior.

Theory and simulations for RNA folding in mixtures of monovalent and divalent cations

RNA molecules cannot fold in the absence of counterions. Experiments are typically performed in the presence of monovalent and divalent cations. How to treat the impact of a solution containing a mixture of both ion types on RNA folding has remained a challenging problem for decades. By exploiting the large concentration difference between divalent and monovalent ions used in experiments, we develop a theory based on the reference interaction site model (RISM), which allows us to treat divalent cations explicitly while keeping the implicit screening effect due to monovalent ions. Our theory captures both the inner shell and outer shell coordination of divalent cations to phosphate groups, which we demonstrate is crucial for an accurate calculation of RNA folding thermodynamics. The RISM theory for ion-phosphate interactions when combined with simulations based on a transferable coarse-grained model allows us to predict accurately the folding of several RNA molecules in a mixture containing monovalent and divalent ions. The calculated folding free energies and ion-preferential coefficients for RNA molecules (pseudoknots, a fragment of the rRNA, and the aptamer domain of the adenine riboswitch) are in excellent agreement with experiments over a wide range of monovalent and divalent ion concentrations. Because the theory is general, it can be readily used to investigate ion and sequence effects on DNA properties.

Novel phosphorylation-dependent regulation in an unstructured protein

This work explores how phosphorylation of an unstructured protein region in inhibitor-2 (I2) regulates protein phosphatase-1 (PP1) enzyme activity using molecular dynamics (MD). Free I2 is largely unstructured; however, when bound to PP1, three segments adopt a stable structure. In particular, an I2 helix (i-helix) blocks the PP1 active site and inhibits phosphatase activity. I2 phosphorylation in the PP1-I2 complex activates phosphatase activity without I2 dissociation. The I2 Thr74 regulatory phosphorylation site is in an unstructured domain in PP1-I2. PP1-I2 MD demonstrated that I2 phosphorylation promotes early steps of PP1-I2 activation in explicit solvent models. Moreover, phosphorylation-dependent activation occurred in PP1-I2 complexes derived from I2 orthologs with diverse sequences from human, yeast, worm, and protozoa. This system allowed exploration of features of the 73-residue unstructured human I2 domain critical for phosphorylation-dependent activation. These studies revealed that components of I2 unstructured domain are strategically positioned for phosphorylation responsiveness including a transient α-helix. There was no evidence that electrostatic interactions of I2 phosphothreonine74 influenced PP1-I2 activation. Instead, phosphorylation altered the conformation of residues around Thr74. Phosphorylation uncurled the distance between I2 residues Glu71 to Tyr76 to promote PP1-I2 activation, whereas reduced distances reduced activation. This I2 residue Glu71 to Tyr76 distance distribution, independently from Thr74 phosphorylation, controls I2 i-helix displacement from the PP1 active site leading to PP1-I2 activation.

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.

Structure-Based Virtual Screening Allows the Identification of Efficient Modulators of E-Cadherin-Mediated Cell-Cell Adhesion

Cadherins are a large family of transmembrane calcium-dependent cell adhesion proteins that orchestrate adherens junction formation and are crucially involved in tissue morphogenesis. Due to their important role in cancer development and metastasis, cadherins can be considered attractive targets for drug discovery. A recent crystal structure of the complex of a cadherin extracellular portion and a small molecule inhibitor allowed the identification of a druggable interface, thus providing a viable strategy for the design of cadherin dimerization modulators. Here, we report on a structure-based virtual screening approach that led to the identification of efficient and selective modulators of E-cadherin-mediated cell–cell adhesion. Of all the putative inhibitors that were identified and experimentally tested by cell adhesion assays using human pancreatic tumor BxPC-3 cells expressing both E-cadherin and P-cadherin, two compounds turned out to be effective in inhibiting stable cell–cell adhesion at micromolar concentrations. Moreover, at the same concentrations, one of them also showed anti-invasive properties in cell invasion assays. These results will allow further development of novel and selective cadherin-mediated cell–cell adhesion modulators for the treatment of a variety of cadherin-expressing solid tumors and for improving the efficiency of drug delivery across biological barriers.

GTP Hydrolysis Without an Active Site Base: A Unifying Mechanism for Ras and Related GTPases

GTP hydrolysis is a biologically crucial reaction, being involved in regulating almost all cellular processes. As a result, the enzymes that catalyze this reaction are among the most important drug targets. Despite their vital importance and decades of substantial research effort, the fundamental mechanism of enzyme-catalyzed GTP hydrolysis by GTPases remains highly controversial. Specifically, how do these regulatory proteins hydrolyze GTP without an obvious general base in the active site to activate the water molecule for nucleophilic attack? To answer this question, we perform empirical valence bond simulations of GTPase-catalyzed GTP hydrolysis, comparing solvent- and substrate-assisted pathways in three distinct GTPases, Ras, Rab, and the G_αi subunit of a heterotrimeric G-protein, both in the presence and in the absence of the corresponding GTPase activating proteins. Our results demonstrate that a general base is not needed in the active site, as the preferred mechanism for GTP hydrolysis is a conserved solvent-assisted pathway. This pathway involves the rate-limiting nucleophilic attack of a water molecule, leading to a short-lived intermediate that tautomerizes to form H₂PO₄^- and GDP as the final products. Our fundamental biochemical insight into the enzymatic regulation of GTP hydrolysis not only resolves a decades-old mechanistic controversy but also has high relevance for drug discovery efforts. That is, revisiting the role of oncogenic mutants with respect to our mechanistic findings would pave the way for a new starting point to discover drugs for (so far) "undruggable" GTPases like Ras.

Ab Initio Flexible Force Field for Metal-Organic Frameworks Using Dummy Model Coordination Bonds

We present force fields developed from periodic density functional theory (DFT) calculations that can be used in classical molecular simulations to model M-MOF-74 (M = Co, Fe, Mg, Mn, Ni, Zn) and its extended linker analogs. Our force fields are based on cationic dummy models (CDMs). These dummy models simplify the methodology required to tune the parameters and improve the accuracy of the force fields. We used our force fields to compare mechanical properties across the M-MOF-74 series and determine that increasing the size of the linker decreases the framework rigidity. In addition, we applied our force fields to an extended linker analog of Mg-MOF-74 and characterized the free energy of a previously reported deformation pattern in which the one-dimensional hexagonal channels of the framework become irregular. The free energy profiles confirm that the deformation is adsorbate induced and impossible to access solely by a pressure stimulus. On the basis of our results, we conclude that the force fields presented here and others that may be developed using our methodology are transferable across metal-organic framework series that share a metal center topology. Finally, we believe that these force fields have the potential to be adapted for the study of complex problems in MOF chemistry, including defects and crystal growth, that have thus far been beyond the scope of classical molecular simulations.

Simulations of CYP51A from Aspergillus fumigatus in a model bilayer provide insights into triazole drug resistance

Azole antifungal drugs target CYP51A in Aspergillus fumigatus by binding with the active site of the protein, blocking ergosterol biosynthesis. Resistance to azole antifungal drugs is now common, with a leucine to histidine amino acid substitution at position 98 the most frequent, predominantly conferring resistance to itraconazole, although cross-resistance has been reported in conjunction with other mutations. In this study, we create a homology model of CYP51A using a recently published crystal structure of the paralog protein CYP51B. The derived structures, wild type, and L98H mutant are positioned within a lipid membrane bilayer and subjected to molecular dynamics simulations in order improve the accuracy of both models. The structural analysis from our simulations suggests a decrease in active site surface from the formation of hydrogen bonds between the histidine substitution and neighboring polar side chains, potentially preventing the binding of azole drugs. This study yields a biologically relevant structure and set of dynamics of the A. fumigatus Lanosterol 14 alpha-demethylase enzyme and provides further insight into azole antifungal drug resistance.

Early stages of phase selection in MOF formation observed in molecular Monte Carlo simulations

Metal–organic frameworks (MOF) comprising metal nodes bridged by organic linkers show great promise because of their guest-specific gas sorption, separation, drug-delivery, and catalytic properties. The selection of metal node, organic linker, and synthesis conditions in principle offers engineered control over both structure and function. For MOFs to realise their potential and to become more than just promising materials, a degree of predictability in the synthesis and a better understanding of the self-assembly or initial growth processes is of paramount importance. Using cobalt succinate, a MOF that exhibits a variety of phases depending on synthesis temperature and ligand to metal ratio, as proof of concept, we present a molecular Monte Carlo approach that allows us to simulate the early stage of MOF assembly. We introduce a new Contact Cluster Monte Carlo (CCMC) algorithm which uses a system of overlapping “virtual sites” to represent the coordination environment of the cobalt and both metal–metal and metal–ligand associations. Our simulations capture the experimentally observed synthesis phase distinction in cobalt succinate at 348 K. To the best of our knowledge this is the first case in which the formation of different MOF phases as a function of composition is captured by unbiased molecular simulations. The CCMC algorithm is equally applicable to any system in which short-range attractive interactions are a dominant feature, including hydrogen-bonding networks, metal–ligand coordination networks, or the assembly of particles with “sticky” patches, such as colloidal systems or the formation of protein complexes.

Clusters produced in simulations of MOF assembly at metal : ligand ratios of (a) 5 : 1 and (b) 1 : 1 with identical interaction potentials.

Cryptic genetic variation shapes the adaptive evolutionary potential of enzymes

Genetic variation among orthologous proteins can cause cryptic phenotypic properties that only manifest in changing environments. Such variation may impact the evolvability of proteins, but the underlying molecular basis remains unclear. Here, we performed comparative directed evolution of four orthologous metallo-β-lactamases toward a new function and found that different starting genotypes evolved to distinct evolutionary outcomes. Despite a low initial fitness, one ortholog reached a significantly higher fitness plateau than its counterparts, via increasing catalytic activity. By contrast, the ortholog with the highest initial activity evolved to a less-optimal and phenotypically distinct outcome through changes in expression, oligomerization and activity. We show how cryptic molecular properties and conformational variation of active site residues in the initial genotypes cause epistasis, that could lead to distinct evolutionary outcomes. Our work highlights the importance of understanding the molecular details that connect genetic variation to protein function to improve the prediction of protein evolution.

Oxidase or peptidase? A computational insight into a putative aflatoxin oxidase from Armillariella tabescens

Aflatoxin oxidase (AFO), an enzyme isolated from Armillariella tabescens, has been reported to degrade aflatoxin B1 (AFB1). However, recent studies reported sequence and structure similarities with the dipeptidyl peptidase III (DPP III) family of enzymes and confirmed peptidase activity toward DPP III substrates. In light of these investigations, an extensive computational study was performed in order to improve understanding of the AFO functions. Steered MD simulations revealed long-range domain motions described as protein opening, characteristic for DPPs III and necessary for substrate binding. Newly identified open and partially open forms of the enzyme closely resemble those of the human DPP III orthologue. Docking of a synthetic DPP III substrate Arg₂ -2-naphthylamide revealed a binding mode similar to the one found in crystal structures of human DPP III complexes with peptides with the S1 and S2 subsites' amino acid residues conserved. On the other hand, no energetically favorable AFB1 binding mode was detected, suggesting that aflatoxins are not good substrates of AFO. High plasticity of the zinc ion coordination sphere within the active site, consistent with that of up to date studied DPPs III, was observed as well. A detailed electrostatic analysis of the active site revealed a predominance of negatively charged regions, unsuitable for the binding of the neutral AFB1. The present study is in line with the most recent experimental study on this enzyme, both suggesting that AFO is a typical member of the DPP III family.

Structural consequence of the most frequently recurring cancer-associated substitution in DNA polymerase ε

The most frequently recurring cancer-associated DNA polymerase ε (Pol ε) mutation is a P286R substitution in the exonuclease domain. While originally proposed to increase genome instability by disrupting exonucleolytic proofreading, the P286R variant was later found to be significantly more pathogenic than Pol ε proofreading deficiency per se. The mechanisms underlying its stronger impact remained unclear. Here we report the crystal structure of the yeast orthologue, Pol ε−P301R, complexed with DNA and an incoming dNTP. Structural changes in the protein are confined to the exonuclease domain, with R301 pointing towards the exonuclease site. Molecular dynamics simulations suggest that R301 interferes with DNA binding to the exonuclease site, an outcome not observed with the exonuclease-inactive Pol ε−D290A,E292A variant lacking the catalytic residues. These results reveal a distinct mechanism of exonuclease inactivation by the P301R substitution and a likely basis for its dramatically higher mutagenic and tumorigenic effects.

Mutations in the human POLE gene are associated with tumours with high mutational loads. Here the authors provide a structural rationale for the mutagenic activity of the cancer-associated DNA polymerase ε P286R variant.

Assessing the Performance of the Nonbonded Mg2+ Models in a Two-Metal-Dependent Ribonuclease

Magnesium ions (Mg²⁺), abundant in living cells, are essential for biomolecular structure, dynamics, and function. The biological importance of Mg²⁺ has motivated continuous development and improvement of various Mg²⁺ models for molecular dynamics (MD) simulations during the last decades. There are four types of nonbonded Mg²⁺ models: the point charge models based on a 12-6 or 12-6-4 type Lennard-Jones (LJ) potential, and the multisite models based on a 12-6 or 12-6-4 LJ potential. Here, we systematically assessed the performance of these four types of nonbonded Mg²⁺ models (21 models in total) in terms of maintaining a challenging intermediate state configuration captured in the structure of a prototypical two-metal-ion RNase H complex with an RNA/DNA hybrid. Our data demonstrate that the 12-6-4 multisite models, which account for charge-induced dipole interactions, perform the best in reproducing all the unique coordination modes in this intermediate state and maintaining the correct carboxylate denticity. Our benchmark work provides a useful guideline for MD simulations and structural refinement of Mg²⁺-containing biomolecular systems.

Single-Ion Thermodynamics from First Principles: Calculation of the Absolute Hydration Free Energy and Single-Electrode Potential of Aqueous Li+ Using ab Initio Quantum Mechanical/Molecular Mechanical Molecular Dynamics Simulations

A recently proposed thermodynamic integration (TI) approach formulated in the framework of quantum mechanical/molecular mechanical molecular dynamics (QM/MM MD) simulations is applied to study the structure, dynamics, and absolute intrinsic hydration free energy Δ_s G_M⁺,wat^◦ of the Li⁺ ion at a correlated ab initio level of theory. Based on the results, standard values (298.15 K, ideal gas at 1 bar, ideal solute at 1 molal) for the absolute intrinsic hydration free energy [Formula: see text] of the proton, the surface electric potential jump χ_wat^◦ upon entering bulk water, and the absolute single-electrode potential [Formula: see text] of the reference hydrogen electrode are calculated to be -1099.9 ± 4.2 kJ·mol^-1, 0.13 ± 0.08 V, and 4.28 ± 0.04 V, respectively, in excellent agreement with the standard values recommended by Hünenberger and Reif on the basis of an extensive evaluation of the available experimental data (-1100 ± 5 kJ·mol^-1, 0.13 ± 0.10 V, and 4.28 ± 0.13 V). The simulation results for Li⁺ are also compared to those for Na⁺ and K⁺ from a previous study in terms of relative hydration free energies ΔΔ_s G_M⁺,wat^◦ and relative electrode potentials [Formula: see text]. The calculated values are found to agree extremely well with the experimental differences in standard conventional hydration free energies ΔΔ_s G_M⁺,wat^• and redox potentials [Formula: see text]. The level of agreement between simulation and experiment, which is quantitative within error bars, underlines the substantial accuracy improvement achieved by applying a highly demanding QM/MM approach at the resolution-of-identity second-order Møller-Plesset perturbation (RIMP2) level over calculations relying on purely molecular mechanical or density functional theory (DFT) descriptions. A detailed analysis of the structural and dynamical properties of the Li⁺ hydrate indicates that a correct description of the solvation structure and dynamics is achieved as well at this level of theory. Consideration of the QM/MM potential-energy components also shows that the partitioning into QM and MM zones does not induce any significant energetic artifact for the system considered.

Exploring the applicability of density functional tight binding to transition metal ions. Parameterization for nickel with the spin-polarized DFTB3 model

In this work, we explore the applicability and limitations of the current third order density functional tight binding (DFTB3) formalism for treating transition metal ions using nickel as an example. To be consistent with recent parameterization of DFTB3 for copper, the parametrization for nickel is conducted in a spin-polarized formulation and with orbital-resolved Hubbard parameters and their charge derivatives. The performance of the current parameter set is evaluated based on structural and energetic properties of a set of nickel-containing compounds that involve biologically relevant ligands. Qualitatively similar to findings in previous studies of copper complexes, the DFTB3 results are more reliable for nickel complexes with neutral ligands than for charged ligands; nevertheless, encouraging agreement is noted in comparison to the reference method, B3LYP/aug-cc-pVTZ, especially for structural properties, including cases that exhibit Jahn-Teller distortions; the structures also compare favorably to available X-ray data in the Cambridge Crystallographic Database for a number of nickel-containing compounds. As to limitations, we find it is necessary to use different d shell Hubbard charge derivatives for Ni(I) and Ni(II), due to the distinct electronic configurations for the nickel ion in the respective complexes, and substantial errors are observed for ligand binding energies, especially for charged ligands, d orbital splitting energies and splitting between singlet and triplet spin states for Ni(II) compounds. These observations highlight that future improvement in intra-d correlation and ligand polarization is required to enable the application of the DFTB3 model to complex transition metal ions. © 2018 Wiley Periodicals, Inc.

Empirical Valence Bond Simulations Suggest a Direct Hydride Transfer Mechanism for Human Diamine Oxidase

Diamine oxidase (DAO) is an enzyme involved in the regulation of cell proliferation and the immune response. This enzyme performs oxidative deamination in the catabolism of biogenic amines, including, among others, histamine, putrescine, spermidine, and spermine. The mechanistic details underlying the reductive half-reaction of the DAO-catalyzed oxidative deamination which leads to the reduced enzyme cofactor and the aldehyde product are, however, still under debate. The catalytic mechanism was proposed to involve a prototropic shift from the substrate-Schiff base to the product-Schiff base, which includes the rate-limiting cleavage of the Cα-H bond by the conserved catalytic aspartate. Our detailed mechanistic study, performed using a combined quantum chemical cluster approach with empirical valence bond simulations, suggests that the rate-limiting cleavage of the Cα-H bond involves direct hydride transfer to the topaquinone cofactor-a mechanism that does not involve the formation of a Schiff base. Additional investigation of the D373E and D373N variants supported the hypothesis that the conserved catalytic aspartate is indeed essential for the reaction; however, it does not appear to serve as the catalytic base, as previously suggested. Rather, the electrostatic contributions of the most significant residues (including D373), together with the proximity of the Cu2+ cation to the reaction site, lower the activation barrier to drive the chemical reaction.

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

Unexpected Diffusion Anisotropy of Carbon Dioxide in the Metal-Organic Framework Zn2(dobpdc)

Metal-organic frameworks are promising materials for energy-efficient gas separations, but little is known about the diffusion of adsorbates in materials featuring one-dimensional porosity at the nanoscale. An understanding of the interplay between framework structure and gas diffusion is crucial for the practical application of these materials as adsorbents or in mixed-matrix membranes, since the rate of gas diffusion within the adsorbent pores impacts the required size (and therefore cost) of the adsorbent column or membrane. Here, we investigate the diffusion of CO2 within the pores of Zn2(dobpdc) (dobpdc4- = 4,4'-dioxidobiphenyl-3,3'-dicarboxylate) using pulsed field gradient (PFG) nuclear magnetic resonance (NMR) spectroscopy and molecular dynamics (MD) simulations. The residual chemical shift anisotropy for pore-confined CO2 allows PFG NMR measurements of self-diffusion in different crystallographic directions, and our analysis of the entire NMR line shape as a function of the applied field gradient provides a precise determination of the self-diffusion coefficients. In addition to observing CO2 diffusion through the channels parallel to the crystallographic c axis (self-diffusion coefficient D∥ = (5.8 ± 0.1) × 10-9 m2 s-1 at a pressure of 625 mbar CO2), we unexpectedly find that CO2 is also able to diffuse between the hexagonal channels in the crystallographic ab plane (D⊥ = (1.9 ± 0.2) × 10-10 m2 s-1), despite the walls of these channels appearing impermeable by single-crystal X-ray crystallography and flexible lattice MD simulations. Observation of such unexpected diffusion in the ab plane suggests the presence of defects that enable effective multidimensional CO2 transport in a metal-organic framework with nominally one-dimensional porosity.

Challenges and advances in the computational modeling of biological phosphate hydrolysis

Phosphate ester hydrolysis is fundamental to many life processes, and has been the topic of substantial experimental and computational research effort. However, even the simplest of phosphate esters can be hydrolyzed through multiple possible pathways that can be difficult to distinguish between, either experimentally, or computationally. Therefore, the mechanisms of both the enzymatic and non-enzymatic reactions have been historically controversial. In the present contribution, we highlight a number of technical issues involved in reliably modeling these computationally challenging reactions, as well as proposing potential solutions. We also showcase examples of our own work in this area, discussing both the non-enzymatic reaction in aqueous solution, as well as insights obtained from the computational modeling of organophosphate hydrolysis and catalytic promiscuity amongst enzymes that catalyze phosphoryl transfer.

Structural Insights into the Osteopontin-Aptamer Complex by Molecular Dynamics Simulations

Osteopontin is an intrinsically disordered protein involved in tissue remodeling. As a biomarker for pathological hypertrophy and fibrosis, the protein is targeted by an RNA aptamer. In this work, we model the interactions between osteopontin and its aptamer, including mono- (Na⁺) and divalent (Mg²⁺) cations. The molecular dynamics simulations suggest that the presence of divalent cations forces the N-terminus of osteopontin to bind the shell of divalent cations adsorbed over the surface of its RNA aptamer, the latter exposing a high negative charge density. The osteopontin plasticity as a function of the local concentration of Mg is discussed in the frame of the proposed strategies for osteopontin targeting as biomarker and in theranostic.

Computer simulations of the catalytic mechanism of wild-type and mutant β-phosphoglucomutase

β-Phosphoglucomutase (β-PGM) has served as an important model system for understanding biological phosphoryl transfer.

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.

Similar Active Sites and Mechanisms Do Not Lead to Cross-Promiscuity in Organophosphate Hydrolysis: Implications for Biotherapeutic Engineering

Organophosphate hydrolases are proficient catalysts of the breakdown of neurotoxic organophosphates and have great potential as both biotherapeutics for treating acute organophosphate toxicity and as bioremediation agents. However, proficient organophosphatases such as serum paraoxonase 1 (PON1) and the organophosphate-hydrolyzing lactonase SsoPox are unable to hydrolyze bulkyorganophosphates with challenging leaving groups such as diisopropyl fluorophosphate (DFP) or venomous agent X, creating a major challenge for enzyme design. Curiously, despite their mutually exclusive substrate specificities, PON1 and diisopropyl fluorophosphatase (DFPase) have essentially identical active sites and tertiary structures. In the present work, we use empirical valence bond simulations to probe the catalytic mechanism of DFPase as well as temperature, pH, and mutational effects, demonstrating that DFPase and PON1 also likely utilize identical catalytic mechanisms to hydrolyze their respective substrates. However, detailed examination of both static structures and dynamical simulations demonstrates subtle but significant differences in the electrostatic properties and solvent penetration of the two active sites and, most critically, the role of residues that make no direct contact with either substrate in acting as "specificity switches" between the two enzymes. Specifically, we demonstrate that key residues that are structurally and functionally critical for the paraoxonase activity of PON1 prevent it from being able to hydrolyze DFP with its fluoride leaving group. These insights expand our understanding of the drivers of the evolution of divergent substrate specificity in enzymes with identical active sites and guide the future design of organophosphate hydrolases that hydrolyze compounds with challenging leaving groups.

On the Dynamical Behavior of the Cysteine Dioxygenase-l-Cysteine Complex in the Presence of Free Dioxygen and l-Cysteine

In this work, viable models of cysteine dioxygenase (CDO) and its complex with l-cysteine dianion were built for the first time, under strict adherence to the crystal structure from X-ray diffraction studies, for all atom molecular dynamics (MD). Based on the CHARMM36 FF, the active site, featuring an octahedral dummy Fe(II) model, allowed us observing water exchange, which would have escaped attention with the more popular bonded models. Free dioxygen (O₂ ) and l-cysteine, added at the active site, could be observed being expelled toward the solvating medium under Random Accelerated Molecular Dynamics (RAMD) along major and minor pathways. Correspondingly, free dioxygen (O₂ ), added to the solvating medium, could be observed to follow the same above pathways in getting to the active site under unbiased MD. For the bulky l-cysteine, 600 ns of trajectory were insufficient for protein penetration, and the molecule was stuck at the protein borders. These models pave the way to free energy studies of ligand associations, devised to better clarify how this cardinal enzyme behaves in human metabolism.

Extending the Nonbonded Cationic Dummy Model to Account for Ion-Induced Dipole Interactions

Modeling metalloproteins often requires classical molecular dynamics (MD) simulations in order to capture their relevant motions, which in turn necessitates reliable descriptions of the metal centers involved. One of the most successful approaches to date is provided by the "cationic dummy model", where the positive charge of the metal ion is transferred toward dummy particles that are bonded to the central metal ion in a predefined coordination geometry. While this approach allows for ligand exchange, and captures the correct electrostatics as demonstrated for different divalent metal ions, current dummy models neglect ion-induced dipole interactions. In the present work, we resolve this weakness by taking advantage of the recently introduced 12-6-4 type Lennard-Jones potential to include ion-induced dipole interactions. We revise our previous dummy model for Mg²⁺ and demonstrate that the resulting model can simultaneously reproduce the experimental solvation free energy and metal-ligand distances without the need for artificial restraints or bonds. As ion-induced dipole interactions become particularly important for highly charged metal ions, we develop dummy models for the biologically relevant ions Al³⁺, Fe³⁺, and Cr³⁺. Finally, the effectiveness of our new models is demonstrated in MD simulations of several diverse (and highly challenging to simulate) metalloproteins.

Prediction of the interaction of metallic moieties with proteins: An update for protein-ligand docking techniques

In this article, we present a new approach to expand the range of application of protein-ligand docking methods in the prediction of the interaction of coordination complexes (i.e., metallodrugs, natural and artificial cofactors, etc.) with proteins. To do so, we assume that, from a pure computational point of view, hydrogen bond functions could be an adequate model for the coordination bonds as both share directionality and polarity aspects. In this model, docking of metalloligands can be performed without using any geometrical constraints or energy restraints. The hard work consists in generating the convenient atom types and scoring functions. To test this approach, we applied our model to 39 high-quality X-ray structures with transition and main group metal complexes bound via a unique coordination bond to a protein. This concept was implemented in the protein-ligand docking program GOLD. The results are in very good agreement with the experimental structures: the percentage for which the RMSD of the simulated pose is smaller than the X-ray spectra resolution is 92.3% and the mean value of RMSD is < 1.0 Å. Such results also show the viability of the method to predict metal complexes-proteins interactions when the X-ray structure is not available. This work could be the first step for novel applicability of docking techniques in medicinal and bioinorganic chemistry and appears generalizable enough to be implemented in most protein-ligand docking programs nowadays available. © 2017 Wiley Periodicals, Inc.

Molecular simulations of self-assembly processes in metal-organic frameworks: Model dependence

Molecular simulation is a powerful tool for investigating microscopic behavior in various chemical systems, where the use of suitable models is critical to successfully reproduce the structural and dynamic properties of the real systems of interest. In this context, molecular dynamics simulation studies of self-assembly processes in metal-organic frameworks (MOFs), a well-known class of porous materials with interesting chemical and physical properties, are relatively challenging, where a reasonably accurate representation of metal-ligand interactions is anticipated to play an important role. In the current study, we both investigate the performance of some existing models and introduce and test new models to help explore the self-assembly in an archetypal Zn-carboxylate MOF system. To this end, the behavior of six different Zn-ion models, three solvent models, and two ligand models was examined and validated against key experimental structural parameters. To explore longer time scale ordering events during MOF self-assembly via explicit solvent simulations, it is necessary to identify a suitable combination of simplified model components representing metal ions, organic ligands, and solvent molecules. It was observed that an extended cationic dummy atom (ECDA) Zn-ion model combined with an all-atom carboxylate ligand model and a simple dipolar solvent model can reproduce characteristic experimental structures for the archetypal MOF system. The successful use of these models in extensive sets of molecular simulations, which provide key insights into the self-assembly mechanism of this archetypal MOF system occurring during the early stages of this process, has been very recently reported.

Distinct Protein Hydration Water Species Defined by Spatially Resolved Spectra of Intermolecular Vibrations

In this molecular dynamics simulation study, we analyze intermolecular vibrations in the hydration shell of a solvated enyzme, the membrane type 1–matrix metalloproteinase, with high spatial resolution. Our approach allows us to characterize vibrational signatures of the local hydrogen bond network, the translational mobility of water molecules, as well as the molecular entropy, in specific local environments. Our study demonstrates the heterogeneity of water properties within the hydration shell of a complex biomolecule. We define a classification scheme based on the vibrational density of states that allows us to distinguish separate classes of hydration water species and facilitates the description of hydration water properties at distinct hydration sites. The results demonstrate that no single characteristic of the protein surface is sufficient to determine the properties of nearby water. The protein surface geometry, quantified here by the number of protein atoms in the vicinity of a hydration water molecule, as well as the chemical nature of a solvated protein functional group, influences dynamic and thermodynamic properties of solvating water molecules.

Free-Energy Calculations of Ionic Hydration Consistent with the Experimental Hydration Free Energy of the Proton

Computational free-energy correction strategies and the choice of experimental proton hydration free energy, ΔG_s^*(H⁺), are analyzed to investigate the apparent controversy in experimental thermodynamics of ionic hydration. Without corrections, the hydration free-energy (ΔG_hyd) calculations match experiments with ΔG_s^*(H⁺) = -1064 kJ/mol as reference. Using the Galvani surface potential the resulting (real) ΔG_hyd are consistent with ΔG_s^*(H⁺) = -1098 kJ/mol. When applying, in an ad hoc manner, the discrete solvent correction, ΔG_hyd matching the "consensus" ΔG_s^*(H⁺) of -1112 kJ/mol are obtained. This analysis rationalizes reports on ΔG_hyd calculations for ions using different experimental references. For neutral amino acid side chains ΔG_hyd are independent of the water model, whereas there are large differences in ΔG_hyd due to the water model for charged species, suggesting that long-range ordering of water around ions yields an important contribution to the ΔG_hyd. These differences are reduced significantly when applying consistent corrections, but to obtain the most accurate results it is recommended to use the water model belonging to the force field.

Development of a multisite model for Ni(II) ion in solution from thermodynamic and kinetic data

Force-field parameters are developed for a multisite model of Ni(II) ions to be used in molecular dynamics simulations combined to enhanced sampling methods. The performances of two charge-partitioning schemes are validated by taking into account structural, thermodynamic, and kinetic observables. One of the two models, featuring partial charges on the dummy atoms only, matches both Ni(II) free energy of solvation and water exchange rates. Such model is particularly suited to study complexation events at a fully dynamic description. © 2017 Wiley Periodicals, Inc.

The Influence of Intrinsic Framework Flexibility on Adsorption in Nanoporous Materials

For applications of metal–organic frameworks (MOFs) such as gas storage and separation, flexibility is often seen as a parameter that can tune material performance. In this work we aim to determine the optimal flexibility for the shape selective separation of similarly sized molecules (e.g., Xe/Kr mixtures). To obtain systematic insight into how the flexibility impacts this type of separation, we develop a simple analytical model that predicts a material’s Henry regime adsorption and selectivity as a function of flexibility. We elucidate the complex dependence of selectivity on a framework’s intrinsic flexibility whereby performance is either improved or reduced with increasing flexibility, depending on the material’s pore size characteristics. However, the selectivity of a material with the pore size and chemistry that already maximizes selectivity in the rigid approximation is continuously diminished with increasing flexibility, demonstrating that the globally optimal separation exists within an entirely rigid pore. Molecular simulations show that our simple model predicts performance trends that are observed when screening the adsorption behavior of flexible MOFs. These flexible simulations provide better agreement with experimental adsorption data in a high-performance material that is not captured when modeling this framework as rigid, an approximation typically made in high-throughput screening studies. We conclude that, for shape selective adsorption applications, the globally optimal material will have the optimal pore size/chemistry and minimal intrinsic flexibility even though other nonoptimal materials’ selectivity can actually be improved by flexibility. Equally important, we find that flexible simulations can be critical for correctly modeling adsorption in these types of systems.

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.

Active Site Hydrophobicity and the Convergent Evolution of Paraoxonase Activity in Structurally Divergent Enzymes: The Case of Serum Paraoxonase 1

Serum paraoxonase 1 (PON1) is a native lactonase capable of promiscuously hydrolyzing a broad range of substrates, including organophosphates, esters, and carbonates. Structurally, PON1 is a six-bladed β-propeller with a flexible loop (residues 70–81) covering the active site. This loop contains a functionally critical Tyr at position 71. We have performed detailed experimental and computational analyses of the role of selected Y71 variants in the active site stability and catalytic activity in order to probe the role of Y71 in PON1’s lactonase and organophosphatase activities. We demonstrate that the impact of Y71 substitutions on PON1’s lactonase activity is minimal, whereas the k_cat for the paraoxonase activity is negatively perturbed by up to 100-fold, suggesting greater mutational robustness of the native activity. Additionally, while these substitutions modulate PON1’s active site shape, volume, and loop flexibility, their largest effect is in altering the solvent accessibility of the active site by expanding the active site volume, allowing additional water molecules to enter. This effect is markedly more pronounced in the organophosphatase activity than the lactonase activity. Finally, a detailed comparison of PON1 to other organophosphatases demonstrates that either a similar “gating loop” or a highly buried solvent-excluding active site is a common feature of these enzymes. We therefore posit that modulating the active site hydrophobicity is a key element in facilitating the evolution of organophosphatase activity. This provides a concrete feature that can be utilized in the rational design of next-generation organophosphate hydrolases that are capable of selecting a specific reaction from a pool of viable substrates.

Adsorbate-induced lattice deformation in IRMOF-74 series

IRMOF-74 analogues are among the most widely studied metal-organic frameworks (MOFs) for adsorption applications because of their one-dimensional channels and high metal density. Most studies involving the IRMOF-74 series assume that the crystal lattice is rigid. This assumption guides the interpretation of experimental data, as changes in the crystal symmetry have so far been ignored as a possibility in the literature. Here, we report a deformation pattern, induced by the adsorption of argon, for IRMOF-74-V. This work has two main implications. First, we use molecular simulations to demonstrate that the IRMOF-74 series undergoes a deformation that is similar to the mechanism behind breathing MOFs, but is unique because the deformation pattern extends beyond a single unit cell of the original structure. Second, we provide an alternative interpretation of experimental small-angle X-ray scattering profiles of these systems, which changes how we view the fundamentals of adsorption in this MOF series.

Development of Site-Specific Mg(2+)-RNA Force Field Parameters: A Dream or Reality? Guidelines from Combined Molecular Dynamics and Quantum Mechanics Simulations

The vital contribution of Mg²⁺ ions to RNA biology is challenging to dissect at the experimental level. This calls for the integrative support of atomistic simulations, which at the classical level are plagued by limited accuracy. Indeed, force fields intrinsically neglect nontrivial electronic effects that Mg²⁺ exerts on its surrounding ligands in varying RNA coordination environments. Here, we present a combined computational study based on classical molecular dynamics (MD) and Density Functional Theory (DFT) calculations, aimed at characterizing (i) the performance of five Mg²⁺ force field (FF) models in RNA systems and (ii) how charge transfer and polarization affect the binding of Mg²⁺ ions in different coordination motifs. As a result, a total of ∼2.5 μs MD simulations (100/200 ns for each run) for two prototypical Mg²⁺-dependent ribozymes showed remarkable differences in terms of populations of inner-sphere coordination site types. Most importantly, complementary DFT calculations unveiled that differences in charge transfer and polarization among recurrent Mg²⁺-RNA coordination motifs are surprisingly small. In particular, the charge of the Mg²⁺ ions substantially remains constant through different coordination sites, suggesting that the common philosophy of developing site-specific Mg²⁺ ion parameters is not in line with the physical origin of the Mg²⁺-RNA MD simulations inaccuracies. Overall, this study constitutes a guideline for an adept use of current Mg²⁺ models and provides novel insights for the rational development of next-generation Mg²⁺ FFs to be employed for atomistic simulations of RNA.

Characterization of Mn(II) ion binding to the amyloid-β peptide in Alzheimer's disease

Growing evidence links neurodegenerative diseases to metal exposure. Aberrant metal ion concentrations have been noted in Alzheimer's disease (AD) brains, yet the role of metals in AD pathogenesis remains unresolved. A major factor in AD pathogenesis is considered to be aggregation of and amyloid formation by amyloid-β (Aβ) peptides. Previous studies have shown that Aβ displays specific binding to Cu(II) and Zn(II) ions, and such binding has been shown to modulate Aβ aggregation. Here, we use nuclear magnetic resonance (NMR) spectroscopy to show that Mn(II) ions also bind to the N-terminal part of the Aβ(1-40) peptide, with a weak binding affinity in the milli- to micromolar range. Circular dichroism (CD) spectroscopy, solid state atomic force microscopy (AFM), fluorescence spectroscopy, and molecular modeling suggest that the weak binding of Mn(II) to Aβ may not have a large effect on the peptide's aggregation into amyloid fibrils. However, identification of an additional metal ion displaying Aβ binding reveals more complex AD metal chemistry than has been previously considered in the literature.

Probing the mechanisms for the selectivity and promiscuity of methyl parathion hydrolase

Diverse organophosphate hydrolases have convergently evolved the ability to hydrolyse man-made organophosphates. Thus, these enzymes are attractive model systems for studying the factors shaping enzyme functional evolution. Methyl parathion hydrolase (MPH) is an enzyme from the metallo-β-lactamase superfamily, which hydrolyses a wide range of organophosphate, aryl ester and lactone substrates. In addition, MPH demonstrates metal-ion-dependent selectivity patterns. The origins of this remain unclear, but are linked to open questions about the more general role of metal ions in functional evolution and divergence within enzyme superfamilies. Here, we present detailed mechanistic studies of the paraoxonase and arylesterase activities of MPH complexed with five different transition metal ions, and demonstrate that the hydrolysis reactions proceed via similar pathways and transition states. However, while it is possible to discern a clear structural origin for the selectivity between different substrates, the selectivity between different metal ions appears to lie instead in the distinct electrostatic properties of the metal ions themselves, which causes subtle changes in transition state geometries and metal-metal distances at the transition state rather than significant structural changes in the active site. While subtle, these differences can be significant for shaping the metal-ion-dependent activity patterns observed for this enzyme.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'.