Publications by authors named "Chris-Kriton Skylaris"

80 Publications

Energy decomposition analysis method for metallic systems.

Phys Chem Chem Phys 2022 Jan 4. Epub 2022 Jan 4.

School of Chemistry, University of Southampton, Highfield, Southampton, SO17 1BJ, UK.

In this work, we present the first extension of an energy decomposition analysis (EDA) method to metallic systems. We extend the theory of our Hybrid Absolutely Localized Molecular Orbitals (HALMO) EDA to take into account that molecular orbitals in metallic systems are partially occupied, which is done by weighted orthogonalization (WO) of the molecular orbitals using their associated fractional occupancies as weights in the construction of the projection operators. These operators are needed for the self-consistent field for molecular interaction (SCF MI) computation of the polarization-energy contribution to the interaction. The method gives more weight to orbitals that have higher occupancies and treats each fragment as metallic. The resulting HALMO EDA for metallic systems naturally reduces to the insulator version and produces the same results when applied to an insulating system. We present the theory and implementation of our new approach, and we demonstrate it with sample calculations of relevance to industrial materials. This work provides a new EDA paradigm and tool for the study and analysis of interactions in metallic systems within large-scale DFT calculations.
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http://dx.doi.org/10.1039/d1cp05112aDOI Listing
January 2022

Atomistic level characterisation of ssDNA translocation through the proteins CsgG and CsgF for nanopore sequencing.

Comput Struct Biotechnol J 2021 18;19:6417-6430. Epub 2021 Nov 18.

School of Chemistry, University of Southampton, SO17 1BJ, United Kingdom.

Two proteins of the membrane protein complex, CsgG and CsgF, are studied as proteinaceous nanopores for DNA sequencing. It is highly desirable to control the DNA as it moves through the pores, this requires characterisation of DNA translocation and subsequent optimization of the pores. In order to inform protein engineering to improve the pores, we have conducted a series of molecular dynamics simulations to characterise the mechanical strength and conformational dynamics of CsgG and the CsgG-CsgF complex and how these impact ssDNA, water and ion movement. We find that the barrel of CsgG is more susceptible to damage from external electric fields compared to the protein vestibule. Furthermore, the presence of CsgF within the CsgG-CsgF complex enables the complex to withstand higher electric fields. We find that the eyelet loops of CsgG play a key role in both slowing the translocation rate of DNA and modulating the conductance of the pore. CsgF also impacts the DNA translocation rate, but to a lesser degree than CsgG.
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http://dx.doi.org/10.1016/j.csbj.2021.11.014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8649110PMC
November 2021

Massively parallel linear-scaling Hartree-Fock exchange and hybrid exchange-correlation functionals with plane wave basis set accuracy.

J Chem Phys 2021 Dec;155(22):224106

School of Chemistry, Highfield, University of Southampton, Southampton SO17 1BJ, United Kingdom.

We extend our linear-scaling approach for the calculation of Hartree-Fock exchange energy using localized in situ optimized orbitals [Dziedzic et al., J. Chem. Phys. 139, 214103 (2013)] to leverage massive parallelism. Our approach has been implemented in the onetep (Order-N Electronic Total Energy Package) density functional theory framework, which employs a basis of non-orthogonal generalized Wannier functions (NGWFs) to achieve linear scaling with system size while retaining controllable near-complete-basis-set accuracy. For the calculation of Hartree-Fock exchange, we use a resolution-of-identity approach, where an auxiliary basis set of truncated spherical waves is used to fit products of NGWFs. The fact that the electrostatic potential of spherical waves (SWs) is known analytically, combined with the use of a distance-based cutoff for exchange interactions, leads to a calculation cost that scales linearly with the system size. Our new implementation, which we describe in detail, combines distributed memory parallelism (using the message passing interface) with shared memory parallelism (OpenMP threads) to efficiently utilize numbers of central processing unit cores comparable to, or exceeding, the number of atoms in the system. We show how the use of multiple time-memory trade-offs substantially increases performance, enabling our approach to achieve superlinear strong parallel scaling in many cases and excellent, although sublinear, parallel scaling otherwise. We demonstrate that in scenarios with low available memory, which preclude or limit the use of time-memory trade-offs, the performance degradation of our algorithm is graceful. We show that, crucially, linear scaling with system size is maintained in all cases. We demonstrate the practicability of our approach by performing a set of fully converged production calculations with a hybrid functional on large imogolite nanotubes up to over 1400 atoms. We finish with a brief study of how the employed approximations (exchange cutoff and the quality of the SW basis) affect the calculation walltime and the accuracy of the obtained results.
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http://dx.doi.org/10.1063/5.0067781DOI Listing
December 2021

Generation of Quantum Configurational Ensembles Using Approximate Potentials.

J Chem Theory Comput 2021 Nov 13;17(11):7021-7042. Epub 2021 Oct 13.

School of Chemistry, University of Southampton, Highfield, Southampton SO17 1BJ, United Kingdom.

Conformational analysis is of paramount importance in drug design: it is crucial to determine pharmacological properties, understand molecular recognition processes, and characterize the conformations of ligands when unbound. Molecular Mechanics (MM) simulation methods, such as Monte Carlo (MC) and molecular dynamics (MD), are usually employed to generate ensembles of structures due to their ability to extensively sample the conformational space of molecules. The accuracy of these MM-based schemes strongly depends on the functional form of the force field (FF) and its parametrization, components that often hinder their performance. High-level methods, such as MD, provide reliable structural information but are still too computationally expensive to allow for extensive sampling. Therefore, to overcome these limitations, we present a multilevel MC method that is capable of generating quantum configurational ensembles while keeping the computational cost at a minimum. We show that FF reparametrization is an efficient route to generate FFs that reproduce QM results more closely, which, in turn, can be used as low-cost models to achieve the gold standard QM accuracy. We demonstrate that the MC acceptance rate is strongly correlated with various phase space overlap measurements and that it constitutes a robust metric to evaluate the similarity between the MM and QM levels of theory. As a more advanced application, we present a self-parametrizing version of the algorithm, which combines sampling and FF parametrization in one scheme, and apply the methodology to generate the QM/MM distribution of a ligand in aqueous solution.
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http://dx.doi.org/10.1021/acs.jctc.1c00532DOI Listing
November 2021

Electrochemistry from first-principles in the grand canonical ensemble.

J Chem Phys 2021 Jul;155(2):024114

School of Chemistry, University of Southampton, Highfield, Southampton SO17 1BJ, United Kingdom.

Progress in electrochemical technologies, such as automotive batteries, supercapacitors, and fuel cells, depends greatly on developing improved charged interfaces between electrodes and electrolytes. The rational development of such interfaces can benefit from the atomistic understanding of the materials involved by first-principles quantum mechanical simulations with Density Functional Theory (DFT). However, such simulations are typically performed on the electrode surface in the absence of its electrolyte environment and at constant charge. We have developed a new hybrid computational method combining DFT and the Poisson-Boltzmann equation (P-BE) capable of simulating experimental electrochemistry under potential control in the presence of a solvent and an electrolyte. The charged electrode is represented quantum-mechanically via linear-scaling DFT, which can model nanoscale systems with thousands of atoms and is neutralized by a counter electrolyte charge via the solution of a modified P-BE. Our approach works with the total free energy of the combined multiscale system in a grand canonical ensemble of electrons subject to a constant electrochemical potential. It is calibrated with respect to the reduction potential of common reference electrodes, such as the standard hydrogen electrode and the Li metal electrode, which is used as a reference electrode in Li-ion batteries. Our new method can be used to predict electrochemical properties under constant potential, and we demonstrate this in exemplar simulations of the differential capacitance of few-layer graphene electrodes and the charging of a graphene electrode coupled to a Li metal electrode at different voltages.
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http://dx.doi.org/10.1063/5.0056514DOI Listing
July 2021

Protein-ligand free energies of binding from full-protein DFT calculations: convergence and choice of exchange-correlation functional.

Phys Chem Chem Phys 2021 Apr;23(15):9381-9393

University of Southampton Faculty of Engineering Science and Mathematics, Chemistry, University Road, Southampton, UK SO17 1BJ, UK.

The accurate prediction of protein-ligand binding free energies with tractable computational methods has the potential to revolutionize drug discovery. Modeling the protein-ligand interaction at a quantum mechanical level, instead of relying on empirical classical-mechanics methods, is an important step toward this goal. In this study, we explore the QM-PBSA method to calculate the free energies of binding of seven ligands to the T4-lysozyme L99A/M102Q mutant using linear-scaling density functional theory on the whole protein-ligand complex. By leveraging modern high-performance computing we perform over 2900 full-protein (2600 atoms) DFT calculations providing new insights into the convergence, precision and reproducibility of the QM-PBSA method. We find that even at moderate sampling over 50 snapshots, the convergence of QM-PBSA is similar to traditional MM-PBSA and that the DFT-based energy evaluations are very reproducible. We show that in the QM-PBSA framework, the physically-motivated GGA exchange-correlation functional PBE outperforms the more modern, dispersion-including non-local and meta-GGA-nonlocal functionals VV10 and B97M-rV. Different empirical dispersion corrections perform similarly well but the three-body dispersion term, as included in Grimme's D3 dispersion, is significant and improves results slightly. Inclusion of an entropy correction term sampled over less than 25 snapshots is detrimental while an entropy correction sampled over the same 50 or 100 snapshots as the enthalpies improves the accuracy of the QM-PBSA method. As full-protein DFT calculations can now be performed on modest computational resources our study demonstrates that they can be a useful addition to the toolbox of free energy calculations.
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http://dx.doi.org/10.1039/d1cp00206fDOI Listing
April 2021

Analysis of DNA interactions and GC content with energy decomposition in large-scale quantum mechanical calculations.

Phys Chem Chem Phys 2021 Apr 6;23(14):8891-8899. Epub 2021 Apr 6.

School of Chemistry, University of Southampton, Highfield, Southampton SO17 1BJ, UK.

GC content is a contributing factor to the stability of nucleic acids due to hydrogen bonding. More hydrogen bonding generally results in greater stability. Empirical evidence, however, has suggested that the GC content of a nucleic acid is a poor predictor of its stability, implying that there are sequence-dependent interactions besides what its GC content indicates. To examine how much such sequence-dependent interactions affect the interaction energies of double-stranded DNA (dsDNA) molecules, dsDNA molecules of different sequences are generated and examined in silico for variabilities in the interaction energies within each group of dsDNA molecules of the same GC content. Since the amount of hydrogen bonding depends on the GC content, holding the GC content fixed when examining the differences in interaction energies allows sequence-dependent interactions to be isolated. The nature of sequence-dependent interactions is then dissected using energy decomposition analysis (EDA). By using EDA, the components of the interactions that depend on the neighboring base pairs help explain some of the variability in the interaction energies of the dsDNA molecules despite having the same GC content. This work provides a new paradigm and tool for the study and analysis of the distributions of interaction components in dsDNA with the same GC content using EDA within large-scale quantum chemistry calculations.
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http://dx.doi.org/10.1039/d0cp06630cDOI Listing
April 2021

ParaMol: A Package for Automatic Parameterization of Molecular Mechanics Force Fields.

J Chem Inf Model 2021 04 22;61(4):2026-2047. Epub 2021 Mar 22.

School of Chemistry, University of Southampton, Highfield, Southampton SO17 1BJ, United Kingdom.

The ensemble of structures generated by molecular mechanics (MM) simulations is determined by the functional form of the force field employed and its parameterization. For a given functional form, the quality of the parameterization is crucial and will determine how accurately we can compute observable properties from simulations. While accurate force field parameterizations are available for biomolecules, such as proteins or DNA, the parameterization of new molecules, such as drug candidates, is particularly challenging as these may involve functional groups and interactions for which accurate parameters may not be available. Here, in an effort to address this problem, we present ParaMol, a Python package that has a special focus on the parameterization of bonded and nonbonded terms of druglike molecules by fitting to data. We demonstrate the software by deriving bonded terms' parameters of three widely known drug molecules, aspirin, caffeine, and a norfloxacin analogue, for which we show that, within the constraints of the functional form, the methodologies implemented in ParaMol are able to derive near-ideal parameters. Additionally, we illustrate the best practices to follow when employing specific parameterization routes. We also determine the sensitivity of different fitting data sets, such as relaxed dihedral scans and configurational ensembles, to the parameterization procedure, and discuss the features of the various weighting methods available to weight configurations. Owing to ParaMol's capabilities, we propose that this software can be introduced as a routine step in the protocol normally employed to parameterize druglike molecules for MM simulations.
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http://dx.doi.org/10.1021/acs.jcim.0c01444DOI Listing
April 2021

Translocation of flexible and tensioned ssDNA through designed hydrophobic nanopores with two constrictions.

Nanoscale 2021 Jan;13(3):1673-1679

School of Chemistry, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, UK.

Protein-inspired nanopores with hydrophobic constriction regions have previously been shown to offer some promise for DNA sequencing. Here we explore a series of pores with two hydrophobic constrictions. The impact of nanopore radius, the nature of residues that define the constriction region and the flexibility of the ssDNA is explored. Our results show that aromatic residues slow down DNA translocation, and in the case of short DNA strands, they cause deviations from a linear DNA conformation. When DNA is under tension, translocation is once again slower when aromatic residues are present in the constriction. However, the lack of flexibility in the DNA backbone provides a narrower window of opportunity for the DNA bases to be retained inside the pore via interaction with the aromatic residues, compared to more flexible strands. Consequently, there is more variability in translocation rates for strands under tension. DNA entry into the pores is correlated to pore width, but no such correlation between width and translocation rate is observed.
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http://dx.doi.org/10.1039/d0nr04890aDOI Listing
January 2021

Strain effects in core-shell PtCo nanoparticles: a comparison of experimental observations and computational modelling.

Phys Chem Chem Phys 2020 Nov 27;22(42):24784-24795. Epub 2020 Oct 27.

Department of Chemistry, University of Southampton, Southampton, UK.

Strain in Pt nanoalloys induced by the secondary metal has long been suggested as a major contributor to the modification of catalytic properties. Here, we investigate strain in PtCo nanoparticles using a combination of computational modelling and microscopy experiments. We have used a combination of molecular dynamics (MD) and large-scale density functional theory (DFT) for our models, alongside experimental work using annular dark field scanning transmission electron microscopy (ADF-STEM). We have performed extensive validation of the interatomic potential against DFT using a PtCo nanoparticle. Modelling gives access to 3 dimensional structures that can be compared to the 2D ADF-STEM images, which we use to build an understanding of nanoparticle structure and composition. Strain has been measured for PtCo and pure Pt nanoparticles, with MD annealed models compared to ADF-STEM images. Our analysis was performed on a layer by layer basis, where distinct trends between the Pt and PtCo alloy nanoparticles are observed. To our knowledge, we show for the first time a way in which detailed atomistic simulations can be used to augment and help interpret the results of ADF-STEM strain mapping experiments, which will enhance their use in characterisation towards the development of improved catalysts.
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http://dx.doi.org/10.1039/d0cp04318dDOI Listing
November 2020

Electronic structure calculations in electrolyte solutions: Methods for neutralization of extended charged interfaces.

J Chem Phys 2020 Sep;153(12):124101

School of Chemistry, University of Southampton, Highfield, Southampton SO17 1BJ, United Kingdom.

Density functional theory (DFT) is often used for simulating extended materials such as infinite crystals or surfaces, under periodic boundary conditions (PBCs). In such calculations, when the simulation cell has non-zero charge, electrical neutrality has to be imposed, and this is often done via a uniform background charge of opposite sign ("jellium"). This artificial neutralization does not occur in reality, where a different mechanism is followed as in the example of a charged electrode in electrolyte solution, where the surrounding electrolyte screens the local charge at the interface. The neutralizing effect of the surrounding electrolyte can be incorporated within a hybrid quantum-continuum model based on a modified Poisson-Boltzmann equation, where the concentrations of electrolyte ions are modified to achieve electroneutrality. Among the infinite possible ways of modifying the electrolyte charge, we propose here a physically optimal solution, which minimizes the deviation of concentrations of electrolyte ions from those in open boundary conditions (OBCs). This principle of correspondence of PBCs with OBCs leads to the correct concentration profiles of electrolyte ions, and electroneutrality within the simulation cell and in the bulk electrolyte is maintained simultaneously, as observed in experiments. This approach, which we call the Neutralization by Electrolyte Concentration Shift (NECS), is implemented in our electrolyte model in the Order-N Electronic Total Energy Package (ONETEP) linear-scaling DFT code, which makes use of a bespoke highly parallel Poisson-Boltzmann solver, DL_MG. We further propose another neutralization scheme ("accessible jellium"), which is a simplification of NECS. We demonstrate and compare the different neutralization schemes on several examples.
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http://dx.doi.org/10.1063/5.0021210DOI Listing
September 2020

The ONETEP linear-scaling density functional theory program.

J Chem Phys 2020 May;152(17):174111

Chemistry and Chemical Biology, University of California Merced, Merced, California 95343, USA.

We present an overview of the onetep program for linear-scaling density functional theory (DFT) calculations with large basis set (plane-wave) accuracy on parallel computers. The DFT energy is computed from the density matrix, which is constructed from spatially localized orbitals we call Non-orthogonal Generalized Wannier Functions (NGWFs), expressed in terms of periodic sinc (psinc) functions. During the calculation, both the density matrix and the NGWFs are optimized with localization constraints. By taking advantage of localization, onetep is able to perform calculations including thousands of atoms with computational effort, which scales linearly with the number or atoms. The code has a large and diverse range of capabilities, explored in this paper, including different boundary conditions, various exchange-correlation functionals (with and without exact exchange), finite electronic temperature methods for metallic systems, methods for strongly correlated systems, molecular dynamics, vibrational calculations, time-dependent DFT, electronic transport, core loss spectroscopy, implicit solvation, quantum mechanical (QM)/molecular mechanical and QM-in-QM embedding, density of states calculations, distributed multipole analysis, and methods for partitioning charges and interactions between fragments. Calculations with onetep provide unique insights into large and complex systems that require an accurate atomic-level description, ranging from biomolecular to chemical, to materials, and to physical problems, as we show with a small selection of illustrative examples. onetep has always aimed to be at the cutting edge of method and software developments, and it serves as a platform for developing new methods of electronic structure simulation. We therefore conclude by describing some of the challenges and directions for its future developments and applications.
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http://dx.doi.org/10.1063/5.0004445DOI Listing
May 2020

The Role of Electrostatics in Enzymes: Do Biomolecular Force Fields Reflect Protein Electric Fields?

J Chem Inf Model 2020 06 13;60(6):3131-3144. Epub 2020 May 13.

School of Chemistry, University of Southampton, Highfield Campus, Southampton, SO17 1BJ, United Kingdom.

Preorganization of large, directionally oriented, electric fields inside protein active sites has been proposed as a crucial contributor to catalytic mechanism in many enzymes, and it may be efficiently investigated at the atomistic level with molecular dynamics simulations. Here, we evaluate the ability of the AMOEBA polarizable force field, as well as the additive Amber ff14SB and Charmm C36m models, to describe the electric fields present inside the active site of the peptidyl-prolyl isomerase cyclophilin A. We compare the molecular mechanical electric fields to those calculated with a fully first-principles quantum mechanical (QM) representation of the protein, solvent, and ions, and find that AMOEBA consistently shows far greater correlation with the QM electric fields than either of the additive force fields tested. Catalytically relevant fields calculated with AMOEBA were typically smaller than those observed with additive potentials, but were generally consistent with an electrostatically driven mechanism for catalysis. Our results highlight the accuracy and the potential advantages of using polarizable force fields in systems where accurate electrostatics may be crucial for providing mechanistic insights.
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http://dx.doi.org/10.1021/acs.jcim.0c00217DOI Listing
June 2020

Erratum: "Achieving plane wave accuracy in linear-scaling density functional theory applied to periodic systems: A case study on crystalline silicon" [J. Chem. Phys. 127, 164712 (2007)].

J Chem Phys 2020 Mar;152(11):119901

Department of Materials and Department of Physics, Imperial College London, London SW7 2AZ, United Kingdom.

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http://dx.doi.org/10.1063/5.0005883DOI Listing
March 2020

Corrigendum: Using ONETEP for accurate and efficient O(N) density functional calculations (2005 J. Phys.: Condens. Matter 17 5757).

J Phys Condens Matter 2020 Mar 18. Epub 2020 Mar 18.

Department of Physics, University of Cambridge, Cambridge, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.

N/A.
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http://dx.doi.org/10.1088/1361-648X/ab80f5DOI Listing
March 2020

Corrigendum: Density kernel optimization in the ONETEP code (2008 J. Phys.: Condens. Matter 20 294207).

J Phys Condens Matter 2020 Mar 18. Epub 2020 Mar 18.

Department of Physics, University of Cambridge, Cambridge, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.

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http://dx.doi.org/10.1088/1361-648X/ab80f7DOI Listing
March 2020

Corrigendum: Recent progress in linear-scaling density functional calculations with plane waves and pseudopotentials: the ONETEP code (2008 J. Phys.: Condens. Matter 20 064209).

J Phys Condens Matter 2020 Mar 18. Epub 2020 Mar 18.

Department of Physics, University of Cambridge, Cambridge, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND.

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http://dx.doi.org/10.1088/1361-648X/ab80f6DOI Listing
March 2020

Reconciling Work Functions and Adsorption Enthalpies for Implicit Solvent Models: A Pt (111)/Water Interface Case Study.

J Chem Theory Comput 2020 Apr 27;16(4):2703-2715. Epub 2020 Mar 27.

School of Chemistry, University of Southampton, Southampton SO17 1BJ, U.K.

Implicit solvent models are a computationally efficient method of representing solid/liquid interfaces prevalent in electrocatalysis, energy storage, and materials science. However, electronic structure changes induced at the metallic surface by the dielectric continuum are not fully understood. To address this, we perform DFT calculations for the Pt(111)/water interface, in order to compare Poisson-Boltzmann continuum solvation methods with molecular dynamics (AIMD) simulations of explicit solvent. We show that the implicit solvent cavity can be parametrized in terms of the electric dipole moment change at the equilibrated explicit Pt/water interface to obtain the potential of zero charge (PZC). We also compare the accuracy of aqueous enthalpies of adsorption of phenol on Pt(111) using geometry and charge density based dielectric cavitation methods. The ability to parametrize the cavity according to individual atoms, as afforded in the geometry based approach, is key to obtaining accurate enthalpy changes of adsorption under aqueous conditions. We also show that the electronic structure changes induced by explicit solvent and our proposed implicit solvent parametrization scheme yield comparable density difference profiles and d-band projected density of states. We therefore demonstrate the capability of implicit solvent approaches to capture both the energetics of adsorption processes and the main electronic effects of aqueous solvent on the metallic surface. This work therefore provides a scheme for computationally efficient simulations of interfacial processes for applications in areas such as heterogeneous catalysis and electrochemistry.
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http://dx.doi.org/10.1021/acs.jctc.0c00034DOI Listing
April 2020

Mechanism of Os-Catalyzed Oxidative Cyclization of 1,5-Dienes.

J Org Chem 2019 12 13;84(23):15173-15183. Epub 2019 Nov 13.

Department of Chemistry , University of Southampton , Southampton , Hampshire SO17 1BJ , U.K.

The oxidative cyclization of 1,5-dienes by metal-oxo species is a powerful method for stereocontrolled synthesis of tetrahydrofuran diols (THF-diols), structural motifs present in many bioactive natural products. Oxidative cyclization of (2,6)-octa-2,6-diene catalyzed by OsO/NMO has been studied using density functional theory (DFT) calculations (M06-2X/aug-cc-pVDZ/Hay-Wadt VDZ (n+1) ECP), highlighting the remarkable effect of acid on the fate of the first intermediate, an Os(VI) dioxoglycolate. A strong acid promotes cyclization of the Os(VI) dioxoglycolate, or its NMO complex, through protonation of an oxo ligand to give more electrophilic species. By contrast, in the absence of acid, reoxidation may occur to afford the Os(VIII) trioxoglycolate, which is shown to favor conventional "second cycle" dihydroxylation reactivity rather than cyclization. The results of the calculations are consistent with experimental results for reactions of OsO/NMO with 1,5-dienes with acid (oxidative cyclization) and without acid (second cycle osmylation/dihydroxylation). Detailed evaluation of potential catalytic cycles supports oxidation of the cyclized Os(IV) THF-diolate intermediate to the corresponding Os(VI) species followed by slow hydrolysis and, finally, regeneration of OsO.
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http://dx.doi.org/10.1021/acs.joc.9b02174DOI Listing
December 2019

Modification of O and CO binding on Pt nanoparticles due to electronic and structural effects of titania supports.

J Chem Phys 2019 Sep;151(11):114702

Department of Chemistry, University of Southampton, Southampton, United Kingdom.

Metal oxide supports often play an active part in heterogeneous catalysis by moderating both the structure and the electronic properties of the metallic catalyst particle. In order to provide some fundamental understanding on these effects, we present here a density functional theory (DFT) investigation of the binding of O and CO on Pt nanoparticles supported on titania (anatase) surfaces. These systems are complex, and in order to develop realistic models, here, we needed to perform DFT calculations with up to ∼1000 atoms. By performing full geometry relaxations at each stage, we avoid any effects of "frozen geometry" approximations. In terms of the interaction of the Pt nanoparticles with the support, we find that the surface deformation of the anatase support contributes greatly to the adsorption of each nanoparticle, especially for the anatase (001) facet. We attempt to separate geometric and electronic effects and find a larger contribution to ligand binding energy arising from the former. Overall, we show an average weakening (compared to the isolated nanoparticle) of ∼0.1 eV across atop, bridge and hollow binding sites on supported Pt for O and CO, and a preservation of site preference. Stronger effects are seen for O on Pt, which is heavily deformed by anatase supports. In order to rationalize our results and examine methods for faster characterization of metal catalysts, we make use of electronic descriptors, including the d-band center and an electronic density based descriptor. We expect that the approach followed in this study could be applied to study other supported metal catalysts.
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http://dx.doi.org/10.1063/1.5120571DOI Listing
September 2019

Machine-Learned Fragment-Based Energies for Crystal Structure Prediction.

J Chem Theory Comput 2019 Apr 13;15(4):2743-2758. Epub 2019 Mar 13.

School of Chemistry , University of Southampton , Highfield, Southampton , SO17 1BJ , United Kingdom.

Crystal structure prediction involves a search of a complex configurational space for local minima corresponding to stable crystal structures, which can be performed efficiently using atom-atom force fields for the assessment of intermolecular interactions. However, for challenging systems, the limitations in the accuracy of force fields prevent a reliable assessment of the relative thermodynamic stability of potential structures, while the cost of fully quantum mechanical approaches can limit applications of the methods. We present a method to rapidly improve force field lattice energies by correcting two-body interactions with a higher level of theory in a fragment-based approach and predicting these corrections with machine learning. Corrected lattice energies with commonly used density functionals and second order perturbation theory (MP2) all significantly improve the ranking of experimentally known polymorphs where the rigid molecule model is applicable. The relative lattice energies of known polymorphs are also found to systematically improve with the fragment corrections. Predicting two-body interactions with atom-centered symmetry functions in a Gaussian process is found to give highly accurate results using as little as 10-20% of the data for training, reducing the cost of the energy correction by up to an order of magnitude. The machine learning approach opens up the possibility of more widespread use of fragment-based methods in crystal structure prediction, whose increased accuracy at a low computational cost will benefit applications in areas such as polymorph screening and computer-guided materials discovery.
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http://dx.doi.org/10.1021/acs.jctc.9b00038DOI Listing
April 2019

Mutually polarizable QM/MM model with in situ optimized localized basis functions.

J Chem Phys 2019 Feb;150(7):074103

School of Chemistry, University of Southampton, Highfield, Southampton SO17 1BJ, United Kingdom.

We extend our recently developed quantum-mechanical/molecular mechanics (QM/MM) approach [Dziedzic et al., J. Chem. Phys. 145, 124106 (2016)] to enable in situ optimization of the localized orbitals. The quantum subsystem is described with onetep linear-scaling density functional theory and the classical subsystem - with the AMOEBA polarizable force field. The two subsystems interact via multipolar electrostatics and are fully mutually polarizable. A total energy minimization scheme is employed for the Hamiltonian of the coupled QM/MM system. We demonstrate that, compared to simpler models using fixed basis sets, the additional flexibility offered by in situ optimized basis functions improves the accuracy of the QM/MM interface, but also poses new challenges, making the QM subsystem more prone to overpolarization and unphysical charge transfer due to increased charge penetration. We show how these issues can be efficiently solved by replacing the classical repulsive van der Waals term for QM/MM interactions with an interaction of the electronic density with a fixed, repulsive MM potential that mimics Pauli repulsion, together with a modest increase in the damping of QM/MM polarization. We validate our method, with particular attention paid to the hydrogen bond, in tests on water-ion pairs, the water dimer, first solvation shells of neutral and charged species, and solute-solvent interaction energies. As a proof of principle, we determine suitable repulsive potential parameters for water, K, and Cl. The mechanisms we employed to counteract the unphysical overpolarization of the QM subsystem are demonstrated to be adequate, and our approach is robust. We find that the inclusion of explicit polarization in the MM part of QM/MM improves agreement with fully QM calculations. Our model permits the use of minimal size QM regions and, remarkably, yields good energetics across the well-balanced QM/MM interface.
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http://dx.doi.org/10.1063/1.5080384DOI Listing
February 2019

Surface reconstruction amendment to the intrinsic sampling method.

J Chem Phys 2018 Dec;149(23):234705

University of Southampton, Southampton SO17 1BJ, United Kingdom.

The intrinsic sampling method (ISM) is a powerful tool that allows the exploration of interfacial properties from molecular simulations by fitting a function that represents the local boundary between two phases. However, owing to the non-physical nature of an "intrinsic" surface, there remains an ambiguity surrounding the comparison of theoretical properties with the physical world. It is therefore important that the ISM remains internally consistent when reproducing simulated properties which match experiments, such as the surface tension or interfacial density distribution. We show that the current ISM procedure causes an over-fitting of the surface to molecules in the interface region, leading to a biased distribution of curvature at these molecular coordinates. We assert that this biased distribution is a cause of the disparity between predicted interfacial densities upon convolution to a laboratory frame, an artefact which has been known to exist since the development of the ISM. We present an improvement to the fitting procedure of the ISM in an attempt to alleviate the ambiguity surrounding the true nature of an intrinsic surface. Our "surface reconstruction" method is able to amend the shape of the interface so as to reproduce the global curvature distribution at all sampled molecular coordinates. We present the effects that this method has on the ISM predicted structure of a simulated Lennard-Jones fluid air-liquid interface. Additionally, we report an unexpected relationship between surface thermodynamic predictions of our reconstructed ISM surfaces and those of extended capillary wave theory, which is of current interest.
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http://dx.doi.org/10.1063/1.5055241DOI Listing
December 2018

Surfactant Proteins A and D: Trimerized Innate Immunity Proteins with an Affinity for Viral Fusion Proteins.

J Innate Immun 2019 5;11(1):13-28. Epub 2018 Oct 5.

Child Health, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton, United

Innate recognition of viruses is an essential part of the immune response to viral pathogens. This is integral to the maintenance of healthy lungs, which are free from infection and efficient at gaseous exchange. An important component of innate immunity for identifying viruses is the family of C-type collagen-containing lectins, also known as collectins. These secreted, soluble proteins are pattern recognition receptors (PRRs) which recognise pathogen-associated molecular patterns (PAMPs), including viral glycoproteins. These innate immune proteins are composed of trimerized units which oligomerise into higher-order structures and facilitate the clearance of viral pathogens through multiple mechanisms. Similarly, many viral surface proteins form trimeric configurations, despite not showing primary protein sequence similarities across the virus classes and families to which they belong. In this review, we discuss the role of the lung collectins, i.e., surfactant proteins A and D (SP-A and SP-D) in viral recognition. We focus particularly on the structural similarity and complementarity of these trimeric collectins with the trimeric viral fusion proteins with which, we hypothesise, they have elegantly co-evolved. Recombinant versions of these innate immune proteins may have therapeutic potential in a range of infectious and inflammatory lung diseases including anti-viral therapeutics.
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http://dx.doi.org/10.1159/000492974DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6738215PMC
February 2020
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