On the Validation of Protein Force Fields Based on Structural Criteria.

Molecular dynamics simulations depend critically on the quality of the force field used to describe the interatomic interactions and the extent to which it has been validated for use in a specific application. Using a curated test set of 52 high-resolution structures, 39 derived from X-ray diffraction and 13 solved using NMR, we consider the extent to which different parameter sets of the GROMOS protein force field can be distinguished based on comparing a range of structural criteria, including the number of backbone hydrogen bonds, the number of native hydrogen bonds, polar and nonpolar solvent-accessible surface area, radius of gyration, the prevalence of secondary structure elements, J-coupling constants, nuclear Overhauser effect (NOE) intensities, positional root-mean-square deviations (RMSD), and the distribution of backbone ϕ and ψ dihedral angles. It is shown that while statistically significant differences between the average values of individual metrics could be detected, these were in general small. Furthermore, improvements in agreement in one metric were often offset by loss of agreement in another. The work establishes a framework and test set against which protein force fields can be validated. It also highlights the danger of inferring the relative quality of a given force field based on a small range of structural properties or small number of proteins.

Permeability of Dermatological Solutes through the Short Periodicity Phase of Human Stratum Corneum Lipid Bilayers.

Determining the permeability of drug-like solutes through the densely packed and heterogeneous stratum corneum lipid layer presents a significant challenge. In this study, we employed umbrella sampling with a periodic weighing function applied to the center of mass of the lipid bilayers. Precise umbrella sampling was conducted with an interframe distance of 0.5 Å, spanning from the bilayer center to the water phase, and each frame was simulated for at least 20 ns. Autocorrelation functions, potential of mean force (PMF), and diffusivity profiles were analyzed for six solutes (testosterone, benzene, caffeine, ethanol, mannitol, and histidine). The results revealed that autocorrelations were dependent solely on the medium, whether water or lipid phase. Diffusivity and PMF profiles along the reaction coordinate were influenced by the hydrophilicity of the solute rather than its size. For hydrophobic solutes, the PMF curves exhibited a minimum at the bilayer center, while for hydrophilic solutes, the PMFs peaked at the bilayer center and lipid tails (where the lipid tails are not interacting with the cholesterol). Diffusivity curves were low at the bilayer center and water phase, with peaks observed at the headgroup or the boundary between fatty acid and cholesterol (1 nm from the bilayer center). The quantitative findings presented in this work hold significance for pharmacists and drug designers.

Development of a model for granule-bound starch synthase I activity using free-energy calculations.

Starch is a branched polymer of glucose with two components, both of which have (1 â†’ 4)-α linear links and (1 â†’ 6)-α branch points: amylopectin, of high molecular weight with many short branches, and amylose, of lower molecular weight and only a few long-chain branches. Granule-bound starch synthase I (GBSSI) is one of the main enzymes controlling amylose synthesis and chain-length distribution. As production of different GBSSI mutants is time-consuming and laborious, molecular dynamics (MD) simulations are used here to predict the binding of different GBSSI mutants to a representative amylose fragment. The simulations were atomistic, with explicit solvent and docking, a method successfully used to understand the binding of wild-type GBSSI to amylose fragments. The binding of GBSSI to G5 (a pentasaccharide amylose fragment) is combined with free-energy calculations employing a thermodynamic integration method to predict the effects of mutations on enzyme activity. Ten GBSSI mutants with different enzyme activities were analyzed to find the structural and energy changes among different single amino-acid mutants and their possible relationship to starch characteristics. Comparing the structural changes and the relative binding free energy of G5 to the wild type GBSSI and GBSSI mutants, it was found that mutants with negative binding energy (lower than -2.0 kcal/mol) are more likely to have higher enzyme activity and amylose content compared to the wild type. This theoretical paper used simulations and robust free energy calculations to interpret in planta data with potential predictions as to what mutants might be generated to give desired properties. This study can be used to help develop grains with improved functional properties.

Probing Disaccharide Binding to Triplatin as Models for Tumor Cell Heparan Sulfate (GAG) Interactions.

In this study, we have used [1H, 15N] NMR spectroscopy to investigate the interactions of the trinuclear platinum anticancer drug triplatin (1) (1,0,1/t,t,t or BBR3464) with site-specific sulfated and carboxylated disaccharides. Specifically, the disaccharides GlcNS(6S)-GlcA (I) and GlcNS(6S)-IdoA(2S) (II) are useful models of longer-chain glycosaminoglycans (GAGs) such as heparan sulfate (HS). For both the reactions of 15N-1 with I and II, equilibrium conditions were achieved more slowly (65 h) compared to the reaction with the monosaccharide GlcNS(6S) (9 h). The data suggest both carboxylate and sulfate binding of disaccharide I to the Pt with the sulfato species accounting for <1% of the total species at equilibrium. The rate constant for sulfate displacement of the aqua ligand (kL2) is 4 times higher than the analogous rate constant for carboxylate displacement (kL1). There are marked differences in the equilibrium concentrations of the chlorido, aqua, and carboxy-bound species for reactions with the two disaccharides, notably a significantly higher concentration of carboxylate-bound species for II, where sulfate-bound species were barely detectable. The trend mirrors that reported for the corresponding dinuclear platinum complex 1,1/t,t, where the rate constant for sulfate displacement of the aqua ligand was 3 times higher than that for acetate. Also similar to what we observed for the reactions of 1,1/t,t with the simple anions, aquation of the sulfato group is rapid, and the rate constant k-L2 is 3 orders of magnitude higher than that for displacement of the carboxylate (k-L1). Molecular dynamics calculations suggest that extra hydrogen-bonding interactions with the more sulfated disaccharide II may prevent or diminish sulfate binding of the triplatin moiety. The overall results suggest that Pt-O donor interactions should be considered in any full description of platinum complex cellular chemistry.

Understanding the Binding of Starch Fragments to Granule-Bound Starch Synthase.

Granule-bound starch synthase (GBSS) plays a major role, that of chain elongation, in the biosynthesis of amylose, a starch component with mostly (1 → 4)-α connected long chains of glucose with a few (1 → 6)-α branch points. Chain-length distributions (CLDs) of amylose affect functional properties, which can be controlled by changing appropriate residues on granule-bound starch synthase (GBSS). Knowing the binding of GBSS and amylose at a molecular level can help better determine the key amino acids on GBSS that affect CLDs of amylose for subsequent use in molecular engineering. Atomistic molecular dynamics simulations with explicit solvent and docking approaches were used in this study to build a model of the binding between rice GBSS and amylose. Amylose fragments containing 3-12 linearly linked glucose units were built to represent the starch fragments. The stability of the complexes, interactions between GBSS and sugars, and difference in structure/conformation of bound and free starch fragments were analyzed. The study found that starch/amylose fragments with 5 or 6 glucose units were suitable for modeling starch binding to GBSS. The removal of an interdomain disulfide on GBSS was found to affect both GBSS and starch stability. Key residues that could affect the binding ability were also indicated. This model can help rationalize the design of mutants and suggest ways to make single-point mutations, which could be used to develop plants producing starches with improved functional properties.

MyD88 TIR domain higher-order assembly interactions revealed by microcrystal electron diffraction and serial femtosecond crystallography.

MyD88 and MAL are Toll-like receptor (TLR) adaptors that signal to induce pro-inflammatory cytokine production. We previously observed that the TIR domain of MAL (MALTIR) forms filaments in vitro and induces formation of crystalline higher-order assemblies of the MyD88 TIR domain (MyD88TIR). These crystals are too small for conventional X-ray crystallography, but are ideally suited to structure determination by microcrystal electron diffraction (MicroED) and serial femtosecond crystallography (SFX). Here, we present MicroED and SFX structures of the MyD88TIR assembly, which reveal a two-stranded higher-order assembly arrangement of TIR domains analogous to that seen previously for MALTIR. We demonstrate via mutagenesis that the MyD88TIR assembly interfaces are critical for TLR4 signaling in vivo, and we show that MAL promotes unidirectional assembly of MyD88TIR. Collectively, our studies provide structural and mechanistic insight into TLR signal transduction and allow a direct comparison of the MicroED and SFX techniques.

Platinum complexes act as shielding agents against virus infection.

We determine that the substitution-inert polynuclear platinum complex (PPC) TriplatinNC is an antiviral agent and protects cells from enterovirus 71 and human metapneumovirus infection. This protection occurs through the formation of adducts with cell-surface glycosaminoglycans. Our detailed mechanistic investigation demonstrates that TriplatinNC blocks viral entry by shielding cells from virus attack, opening new directions for metalloshielding antiviral drug development.

SARM1 is a metabolic sensor activated by an increased NMN/NAD+ ratio to trigger axon degeneration.

Axon degeneration is a central pathological feature of many neurodegenerative diseases. Sterile alpha and Toll/interleukin-1 receptor motif-containing 1 (SARM1) is a nicotinamide adenine dinucleotide (NAD+)-cleaving enzyme whose activation triggers axon destruction. Loss of the biosynthetic enzyme NMNAT2, which converts nicotinamide mononucleotide (NMN) to NAD+, activates SARM1 via an unknown mechanism. Using structural, biochemical, biophysical, and cellular assays, we demonstrate that SARM1 is activated by an increase in the ratio of NMN to NAD+ and show that both metabolites compete for binding to the auto-inhibitory N-terminal armadillo repeat (ARM) domain of SARM1. We report structures of the SARM1 ARM domain bound to NMN and of the homo-octameric SARM1 complex in the absence of ligands. We show that NMN influences the structure of SARM1 and demonstrate via mutagenesis that NMN binding is required for injury-induced SARM1 activation and axon destruction. Hence, SARM1 is a metabolic sensor responding to an increased NMN/NAD+ ratio by cleaving residual NAD+, thereby inducing feedforward metabolic catastrophe and axonal demise.

Bisubstrate Ether-Linked Uridine-Peptide Conjugates as O-GlcNAc Transferase Inhibitors.

The O-linked ß-N-acetylglucosamine (O-GlcNAc) transferase (OGT) is a master regulator of installing O-GlcNAc onto serine or threonine residues on a multitude of target proteins. Numerous nuclear and cytosolic proteins of varying functional classes, including translational factors, transcription factors, signaling proteins, and kinases are OGT substrates. Aberrant O-GlcNAcylation of proteins is implicated in signaling in metabolic diseases such as diabetes and cancer. Selective and potent OGT inhibitors are valuable tools to study the role of OGT in modulating a wide range of effects on cellular functions. We report linear bisubstrate ether-linked uridine-peptide conjugates as OGT inhibitors with micromolar affinity. In vitro evaluation of the compounds revealed the importance of donor substrate, linker and acceptor substrate in the rational design of bisubstrate analogue inhibitors. Molecular dynamics simulations shed light on the binding of this novel class of inhibitors and rationalized the effect of amino acid truncation of acceptor peptide on OGT inhibition.

Simplified Novel Muraymycin Analogues; using a Serine Template Strategy for Linking Key Pharmacophores.

The present status of antibiotic research requires the urgent invention of novel agents that act on multidrug-resistant bacteria. The World Health Organization has classified antibiotic-resistant bacteria into critical, high and medium priority according to the urgency of need for new antibiotics. Naturally occurring uridine-derived "nucleoside antibiotics" have shown promising activity against numerous priority resistant organisms by inhibiting the transmembrane protein MraY (translocase I), which is yet to be explored in a clinical context. The catalytic activity of MraY is an essential process for bacterial cell viability and growth including that of priority organisms. Muraymycins are one subclass of naturally occurring MraY inhibitors. Despite having potent antibiotic properties, the structural complexity of muraymycins advocates for simplified analogues as potential lead structures. Herein, we report a systematic structure-activity relationship (SAR) study of serine template-linked, simplified muraymycin-type analogues. This preliminary SAR lead study of serine template analogues successfully revealed that the complex structure of naturally occurring muraymycins could be easily simplified to afford bioactive scaffolds against resistant priority organisms. This study will pave the way for the development of novel antibacterial lead compounds based on a simplified serine template.

Crystal Structures of Protein-Bound Cyclic Peptides.

Cyclization is an important post-translational modification of peptides and proteins that confers key advantages such as protection from proteolytic degradation, altered solubility, membrane permeability, bioavailability, and especially restricted conformational freedom in water that allows the peptide backbone to adopt the major secondary structure elements found in proteins. Non-ribosomal synthesis in bacteria, fungi, and plants or synthetic chemistry can introduce unnatural amino acids and non-peptidic constraints that modify peptide backbones and side chains to fine-tune cyclic peptide structure. Structures can be potentially altered further upon binding to a protein in biological environments. Here we analyze three-dimensional crystal structures for 211 bioactive cyclic peptides bound to 65 different proteins. The protein-bound cyclic peptides were examined for similarities and differences in bonding modes, for main-chain and side-chain structure, and for the importance of polarity, hydrogen bonds, hydrophobic effects, and water molecules in interactions with proteins. Many protein-bound cyclic peptides show backbone structures like those (strands, sheets, turns, helices, loops, or distorted variations) found at protein-protein binding interfaces. However, the notion of macrocycles simply as privileged scaffolds that primarily project side-chain substituents for complementary interactions with proteins is dispelled here. Unlike small-molecule drugs, the cyclic peptides do not rely mainly upon hydrophobic and van der Waals interactions for protein binding; they also use their main chain and side chains to form polar contacts and hydrogen bonds with proteins. Compared to small-molecule ligands, cyclic peptides can bind across larger, polar, and water-exposed protein surface areas, making many more contacts that can increase affinity, selectivity, biological activity, and ligand-receptor residence time. Cyclic peptides have a greater capacity than small-molecule drugs to modulate protein-protein interfaces that involve large, shallow, dynamic, polar, and water-exposed protein surfaces.

Automated Topology Builder Version 3.0: Prediction of Solvation Free Enthalpies in Water and Hexane.

The ability of atomic interaction parameters generated using the Automated Topology Builder and Repository version 3.0 (ATB3.0) to predict experimental hydration free enthalpies (Δ Gwater) and solvation free enthalpies in the apolar solvent hexane (Δ Ghexane) is presented. For a validation set of 685 molecules the average unsigned error (AUE) between Δ Gwater values calculated using the ATB3.0 and experiment is 3.8 kJ·mol-1. The slope of the line of best fit is 1.00, the intercept -1.0 kJ·mol-1, and the R2 0.90. For the more restricted set of 239 molecules used to validate OPLS3 ( J. Chem. Theory Comput. 2016 , 12 , 281 - 296 , DOI: 10.1021/acs.jctc.5b00864 ) the AUE using the ATB3.0 is just 2.7 kJ·mol-1 and the R2 0.93. A roadmap for further improvement of the ATB parameters is presented together with a discussion of the challenges of validating force fields against the available experimental data.

Predicting the Prevalence of Alternative Warfarin Tautomers in Solution.

Warfarin, a widely used oral anticoagulant, is prescribed as a racemic mixture. Each enantiomer of neutral Warfarin can exist in 20 possible tautomeric states leading to complex pharmacokinetics and uncertainty as to the relevant species under different conditions. Here, the ability of alternative computational approaches to predict the preferred tautomeric form(s) of neutral Warfarin in different solvents is examined. It is shown that varying the method used to estimate the heat of formation in vacuum (direct or via homodesmic reactions), whether entropic corrections were included, and the method used to estimate the free enthalpy of solvation (i.e., PCM, COSMO, or SMD implicit models or explicit solvent) lead to large differences in the predicted rank and relative populations of the tautomers. In this case, only a combination of the enthalpy of formation using homodesmic reactions and explicit solvent to estimate the free enthalpy of solvation yielded results compatible with the available experimental data. The work also suggests that a small but significant subset of the possible Warfarin tautomers are likely to be physiologically relevant.

Effect of Binding on Enantioselectivity of Epoxide Hydrolase.

Molecular dynamics simulations and free energy calculations have been used to investigate the effect of ligand binding on the enantioselectivity of an epoxide hydrolase (EH) from Aspergillus niger. Despite sharing a common mechanism, a wide range of alternative mechanisms have been proposed to explain the origin of enantiomeric selectivity in EHs. By comparing the interactions of ( R)- and ( S)-glycidyl phenyl ether (GPE) with both the wild type (WT, E = 3) and a mutant showing enhanced enantioselectivity to GPE (LW202, E = 193), we have examined whether enantioselectivity is due to differences in the binding pose, the affinity for the ( R)- or ( S)- enantiomers, or a kinetic effect. The two enantiomers were easily accommodated within the binding pockets of the WT enzyme and LW202. Free energy calculations suggested that neither enzyme had a preference for a given enantiomer. The two substrates sampled a wide variety of conformations in the simulations with the sterically hindered and unhindered carbon atoms of the GPE epoxide ring both coming in close proximity to the nucleophilic aspartic acid residue. This suggests that alternative pathways could lead to the formation of a ( S)- and ( R)-diol product. Together, the calculations suggest that the enantioselectivity is due to kinetic rather than thermodynamic effects and that the assumption that one substrate results in one product when interpreting the available experimental data and deriving E-values may be inappropriate in the case of EHs.

Learning epistatic interactions from sequence-activity data to predict enantioselectivity.

Enzymes with a high selectivity are desirable for improving economics of chemical synthesis of enantiopure compounds. To improve enzyme selectivity mutations are often introduced near the catalytic active site. In this compact environment epistatic interactions between residues, where contributions to selectivity are non-additive, play a significant role in determining the degree of selectivity. Using support vector machine regression models we map mutations to the experimentally characterised enantioselectivities for a set of 136 variants of the epoxide hydrolase from the fungus Aspergillus niger (AnEH). We investigate whether the influence a mutation has on enzyme selectivity can be accurately predicted through linear models, and whether prediction accuracy can be improved using higher-order counterparts. Comparing linear and polynomial degree = 2 models, mean Pearson coefficients (r) from [Formula: see text]-fold cross-validation increase from 0.84 to 0.91 respectively. Equivalent models tested on interaction-minimised sequences achieve values of [Formula: see text] and [Formula: see text]. As expected, testing on a simulated control data set with no interactions results in no significant improvements from higher-order models. Additional experimentally derived AnEH mutants are tested with linear and polynomial degree = 2 models, with values increasing from [Formula: see text] to [Formula: see text] respectively. The study demonstrates that linear models perform well, however the representation of epistatic interactions in predictive models improves identification of selectivity-enhancing mutations. The improvement is attributed to higher-order kernel functions that represent epistatic interactions between residues.

Optimization of Empirical Force Fields by Parameter Space Mapping: A Single-Step Perturbation Approach.

A general method for parametrizing atomic interaction functions is presented. The method is based on an analysis of surfaces corresponding to the difference between calculated and target data as a function of alternative combinations of parameters (parameter space mapping). The consideration of surfaces in parameter space as opposed to local values or gradients leads to a better understanding of the relationships between the parameters being optimized and a given set of target data. This in turn enables for a range of target data from multiple molecules to be combined in a robust manner and for the optimal region of parameter space to be trivially identified. The effectiveness of the approach is illustrated by using the method to refine the chlorine 6-12 Lennard-Jones parameters against experimental solvation free enthalpies in water and hexane as well as the density and heat of vaporization of the liquid at atmospheric pressure for a set of 10 aromatic-chloro compounds simultaneously. Single-step perturbation is used to efficiently calculate solvation free enthalpies for a wide range of parameter combinations. The capacity of this approach to parametrize accurate and transferrable force fields is discussed.

Elucidating the Spatial Arrangement of Emitter Molecules in Organic Light-Emitting Diode Films.

The effect of varying the emitter concentration on the structural properties of an archetypal phosphorescent blend consisting of 4,4'-bis(N-carbazolyl)biphenyl and tris(2-phenylpyridyl)iridium(III) has been investigated using non-equilibrium molecular dynamics (MD) simulations that mimic the process of vacuum deposition. By comparison with reflectometry measurements, we show that the simulations provide an accurate model of the average density of such films. The emitter molecules were found not to be evenly distributed throughout film, but rather they can form networks that provide charge and/or energy migration pathways, even at emitter concentrations as low as ≈5 weight percent. At slightly higher concentrations, percolated networks form that span the entire system. While such networks would give improved charge transport, they could also lead to more non-radiative pathways for the emissive state and a resultant loss of efficiency.

Molecular dynamics simulations reveal structural insights into inhibitor binding modes and functionality in human Group IIA phospholipase A2.

Human Group IIA phospholipase A2 (hGIIA) promotes inflammation in immune-mediated pathologies by regulating the arachidonic acid pathway through both catalysis-dependent and -independent mechanisms. The hGIIA crystal structure, both alone and inhibitor-bound, together with structures of closely related snake-venom-derived secreted phospholipase enzymes has been well described. However, differentiation of biological and nonbiological contacts and the relevance of structures determined from snake venom enzymes to human enzymes are not clear. We employed molecular dynamics (MD) and docking approaches to understand the binding of inhibitors that selectively or nonselectively block the catalysis-independent mechanism of hGIIA. Our results indicate that hGIIA behaves as a monomer in the solution environment rather than a dimer arrangement that is in the asymmetric unit of some crystal structures. The binding mode of a nonselective inhibitor, KH064, was validated by a combination of the experimental electron density and MD simulations. The binding mode of the selective pentapeptide inhibitor FLSYK to hGIIA was stipulated to be different to that of the snake venom phospholipases A2 of Daboia russelli pulchella (svPLA2 ). Our data suggest that the application of MD approaches to crystal structure data is beneficial in evaluating the robustness of conclusions drawn based on crystal structure data alone. Proteins 2017; 85:827-842. © 2016 Wiley Periodicals, Inc.

Binding of Starch Fragments to the Starch Branching Enzyme: Implications for Developing Slower-Digesting Starch.

Molecular weight distributions of starch branches affect functional properties, which can be controlled by engineering starch branching enzymes (SBEs). Molecular dynamics and docking approaches are used to examine interactions between SBE and starch fragments. In the native protein, three residues formed stable interactions with starch fragments in the central binding region; these residues may play key roles in substrate recognition. Fragments containing 5-12 glucose units interacted more tightly with SBE than smaller fragments, suggesting a minimal functional fragment size of 5, agreeing with experiment. Effects of three different point mutations on interactions with maltopentaose in the central binding region correlated well with experiment. Simulations indicate that SBE may template formation of the crystalline lamellae characteristic of native starch, consistent with the observation that crystalline lamellae formed by starch in a plant, are not necessarily the state of lowest free energy. The methodology will help develop starches with optimized functional properties.

The characterization of modified starch branching enzymes: toward the control of starch chain-length distributions.

Starch is a complex branched glucose polymer whose branch molecular weight distribution (the chain-length distribution, CLD) influences nutritionally important properties such as digestion rate. Chain-stopping in starch biosynthesis is by starch branching enzyme (SBE). Site-directed mutagenesis was used to modify SBEIIa from Zea mays (mSBEIIa) to produce mutants, each differing in a single conserved amino-acid residue. Products at different times from in vitro branching were debranched and the time evolution of the CLD measured by size-exclusion chromatography. The results confirm that Tyr352, Glu513, and Ser349 are important for mSBEIIa activity while Arg456 is important for determining the position at which the linear glucan is cut. The mutant mSBEIIa enzymes have different activities and suggest the length of the transferred chain can be varied by mutation. The work shows analysis of the molecular weight distribution can yield information regarding the enzyme branching sites useful for development of plants yielding starch with improved functionality.