Benchmarking of copper(II) LFMM parameters for studying amyloid-β peptides

Ligand field molecular mechanics (LFMM) parameters have been benchmarked for copper (II) bound to the amyloid-β1–16 peptide fragment. Several density functional theory (DFT) optimised small test models, representative of different possible copper coordination modes, have been used to test the accuracy of the LFMM copper bond lengths and angles, resulting in errors typically less than 0.1 Å and 5°. Ligand field molecular dynamics (LFMD) simulations have been carried out on the copper bound amyloid-β1–16 peptide and snapshots extracted from the subsequent trajectory. Snapshots have been optimised using DFT and the semi-empirical PM7 method resulting in good agreement against the LFMM calculated geometry. Analysis of substructures within snapshots shows that the larger contribution of geometrical difference, as measured by RMSD, lies within the peptide backbone, arising from differences in DFT and AMBER, and the copper coordination sphere is reproduced well by LFMM. PM7 performs excellently against LFMM with an average RMSD of 0.2 Å over 21 tested snapshots. Further analysis of the LFMD trajectory shows that copper bond lengths and angles have only small deviations from average values, with the exception of a carbonyl moiety from the N-terminus, which can act as a weakly bound fifth ligand

Metal binding to amyloid-β1–42: a ligand field molecular dynamics study

Ligand field molecular mechanics simulation has been used to model the interactions of copper(II) and platinum(II) with the amyloid-β1–42 peptide monomer. Molecular dynamics over several microseconds for both metalated systems are compared to analogous results for the free peptide. Significant differences in structural parameters are observed, both between Cu and Pt bound systems as well as between free and metal-bound peptide. Both metals stabilize the formation of helices in the peptide as well as reducing the content of β secondary structural elements compared to the unbound monomer. This is in agreement with experimental reports of metals reducing β-sheet structures, leading to formation of amorphous aggregates over amyloid fibrils. The shape and size of the peptide structures also undergo noteworthy change, with the free peptide exhibiting globular-like structure, platinum(II) system adopting extended structures, and copper(II) system resulting in a mixture of conformations similar to both of these. Salt bridge networks exhibit major differences: the Asp23-Lys28 salt bridge, known to be important in fibril formation, has a differing distance profile within all three systems studied. Salt bridges in the metal binding region of the peptide are strongly altered; in particular, the Arg5-Asp7 salt bridge, which has an occurrence of 71% in the free peptide, is reduced to zero in the presence of both metals

Molecular dynamics simulations of copper binding to amyloid-β Glu22 mutants

We report microsecond timescale ligand field molecular dynamics simulations of the copper complexes of three known mutants of the amyloid-β peptide, E22G, E22Q and E22K, alongside the naturally occurring sequence. We find that all three mutants lead to formation of less compact structures than the wild-type: E22Q is the most similar to the native peptide, while E22G and especially E22K are markedly different in size, shape and stability. Turn and coil structures dominate all structures studied but subtle differences in helical and β-sheet distribution are noted, especially in the C-terminal region. The origin of these changes is traced to disruption of key salt bridges: in particular, the Asp23-Lys28 bridge that is prevalent in the wild-type is absent in E22G and E22K, while Lys22 in the latter mutant forms a strong association with Asp23. We surmise that the drastically different pattern of salt bridges in the mutants lead to adoption of a different structural ensemble of the peptide backbone, and speculate that this might affect the ability of the mutant peptides to aggregate in the same manner as known for the wild-type

Replica exchange molecular dynamics simulation of the coordination of Pt(ii)-Phenanthroline to amyloid-β†

We report replica exchange molecular dynamics (REMD) simulations of the complex formed between amyloid-β peptides and platinum bound to a phenanthroline ligand, Pt(phen). After construction of an AMBER-style forcefield for the Pt complex, REMD simulation employing temperatures between 270 and 615 K was used to provide thorough sampling of the conformational freedom available to the peptide. We find that the full length peptide Aβ42, in particular, frequently adopts a compact conformation with a large proportion of α- and 3,10-helix content, with smaller amounts of β-strand in the C-terminal region of the peptide. Helical structures are more prevalent than in the metal-free peptide, while turn and strand conformations are markedly less common. Non-covalent interactions, including salt-bridges, hydrogen bonds, and π-stacking between aromatic residues and the phenanthroline ligand, are common, and markedly different from those seen in the amyloid-β peptides alone

Molecular dynamics simulation of aluminum binding to amyloid-β and its effect on peptide structure

Multiple microsecond-length molecular dynamics simulations of complexes of Al(III) with amyloid-β (Aβ) peptides of varying length are reported, employing a non-bonded model of Al-coordination to the peptide, which is modelled using the AMBER ff14SB forcefield. Individual simulations reach equilibrium within 100 to 400 ns, as determined by root mean square deviations, leading to between 2.1 and 2.7 μs of equilibrated data. These reveal a compact set of configurations, with radius of gyration similar to that of the metal free peptide but larger than complexes with Cu, Fe and Zn. Strong coordination through acidic residues Glu3, Asp7 and Glu11 is maintained throughout all trajectories, leading to average coordination numbers of approximately 4 to 5. Helical conformations predominate, particularly in the longer Al-Aβ40 and Al-Aβ42 peptides, while β-strand forms are rare. Binding of the small, highly charged Al(III) ion to acidic residues in the N-terminus strongly disrupts their ability to engage in salt bridges, whereas residues outside the metal binding region engage in salt bridges to similar extent to the metal-free peptide, including the Asp23-Lys28 bridge known to be important for formation of fibrils. High helical content and disruption of salt bridges leads to characteristic tertiary structure, as shown by heat maps of contact between residues as well as representative clusters of trajectories

Distinguishing epimers through raman optical activity

The Raman optical activity spectra of the epimers β-d-glucose and β-d-galactose, two monosaccharides of biological importance, have been calculated using molecular dynamics combined with a quantum mechanics/molecular mechanics approach. Good agreement between theoretical and experimental spectra is observed for both monosaccharides. Full band assignments have been carried out, which has not previously been possible for carbohydrate epimers. For the regions where the spectral features are opposite in sign, the differences in the vibrational modes have been noted and ascribed to the band sign changes

The Raman optical activity of β-D-xylose: where experiment and theory meet

Besides its applications in bioenergy and biosynthesis, β-D-xylose is a very simple monosaccharide that exhibits relatively high rigidity. As such, it provides the best basis to study the impact of different solvation shell radii on the computation of its Raman optical activity (ROA) spectrum. Indeed, this chiroptical spectroscopic technique provides exquisite sensitivity to stereochemistry, and benefits much from theoretical support for interpretation. Our simulation approach combines density functional theory (DFT) and molecular dynamics (MD) in order to efficiently account for the crucial hydration effects in the simulation of carbohydrates and their spectroscopic response predictions. Excellent agreement between the simulated spectrum and the experiment was obtained with a solvation radius of 10 Å. Vibrational bands have been resolved from the computed ROA data, and compared with previous results on different monosaccharides in order to identify specific structure–spectrum relationships and to investigate the effect of the solvation environment on the conformational dynamics of small sugars. From the comparison with ROA analytical results, a shortcoming of the classical force field used for the MD simulations has been identified and overcome, again highlighting the complementary role of experiment and theory in the structural characterisation of complex biomolecules. Indeed, due to unphysical puckering, a spurious ring conformation initially led to erroneous conformer ratios, which are used as weights for the averaging of the spectral average, and only by removing this contribution was near perfect comparison between theory and experiment achieved

Calculation of Raman optical activity spectra for vibrational analysis

By looking back on the history of Raman Optical Activity (ROA), the present article shows that the success of this analytical technique was for a long time hindered, paradoxically, by the deep level of detail and wealth of structural information it can provide. Basic principles of the underlying theory are discussed, to illustrate the technique's sensitivity due to its physical origins in the delicate response of molecular vibrations to electromagnetic properties. Following a short review of significant advances in the application of ROA by UK researchers, we dedicate two extensive sections to the technical and theoretical difficulties that were overcome to eventually provide predictive power to computational simulations in terms of ROA spectral calculation. In the last sections, we focus on a new modelling strategy that has been successful in coping with the dramatic impact of solvent effects on ROA analyses. This work emphasises the role of complementarity between experiment and theory for analysing the conformations and dynamics of biomolecules, so providing new perspectives for methodological improvements and molecular modelling development. For the latter, an example of a next-generation force-field for more accurate simulations and analysis of molecular behaviour is presented. By improving the accuracy of computational modelling, the analytical capabilities of ROA spectroscopy will be further developed so generating new insights into the complex behaviour of molecules

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Towards improved quantitative analysis using surface-enhanced Raman scattering incorporating internal isotope labelling

Raman spectroscopy has attracted considerable interest during the past two decades as a vibrational technique used for the molecular characterisation of different molecules. Whilst the Raman effect is known to be generally weak, it is also known that this can be greatly improved using surface-enhanced Raman scattering (SERS). Indeed, in recent years, the power of SERS for rapid identification and quantification of target analytes in a wide range of applications has been repeatedly demonstrated in multiple studies. Moreover, the application of SERS in combination with an isotopically labelled compound (ILC), as an internal standard, has also very recently shown promising results for quantitative SERS measurements, by improving both its accuracy and precision. This is due to the 12 C and 13 C or 1 H and 2 H (D) having similar physicochemical properties. The use of these internal standards results in the reduction of any influences due to the number of nanoparticles within the analysis zone and fluctuations in laser fluence. Thus, in this study we have employed SERS for quantitative detection of tryptophan (Trp) and caffeine. These have been chosen because Trp is readily available as the deuterated form and caffeine is available in both 12 C and 13 C. Quantum chemical calculations based on density functional theory (DFT) have been utilized to determine the vibrational characteristics of the target analytes. For SERS analysis incorporating isotopologues of tryptophan three independent experiments were conducted with three different batches of nanoparticles over a 12 month period; our results show that the use of this internal standard improves quantification of this target molecule. In particular for the independent test sets (i.e., samples not used in quantitative partial least squares regression (PLSR) model construction) we observed improvements in the linearity for test set predictions, as well as lower errors in test set pred