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Dive into the research topics where Daniel J. Cole is active.

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Featured researches published by Daniel J. Cole.


Journal of Chemical Physics | 2007

Development of a classical force field for the oxidized Si surface: application to hydrophilic wafer bonding.

Daniel J. Cole; M. C. Payne; Gábor Csányi; S. Mark Spearing; Lucio Colombi Ciacchi

We have developed a classical two- and three-body interaction potential to simulate the hydroxylated, natively oxidized Si surface in contact with water solutions, based on the combination and extension of the Stillinger-Weber potential and of a potential originally developed to simulate SiO(2) polymorphs. The potential parameters are chosen to reproduce the structure, charge distribution, tensile surface stress, and interactions with single water molecules of a natively oxidized Si surface model previously obtained by means of accurate density functional theory simulations. We have applied the potential to the case of hydrophilic silicon wafer bonding at room temperature, revealing maximum room temperature work of adhesion values for natively oxidized and amorphous silica surfaces of 97 and 90 mJm(2), respectively, at a water adsorption coverage of approximately 1 ML. The difference arises from the stronger interaction of the natively oxidized surface with liquid water, resulting in a higher heat of immersion (203 vs 166 mJm(2)), and may be explained in terms of the more pronounced water structuring close to the surface in alternating layers of larger and smaller densities with respect to the liquid bulk. The computed force-displacement bonding curves may be a useful input for cohesive zone models where both the topographic details of the surfaces and the dependence of the attractive force on the initial surface separation and wetting can be taken into account.


Journal of Physical Chemistry Letters | 2013

Toward Ab Initio Optical Spectroscopy of the Fenna–Matthews–Olson Complex

Daniel J. Cole; Alex W. Chin; Nicholas Hine; Peter D. Haynes; M. C. Payne

We present progress toward a first-principles parametrization of the Hamiltonian of the Fenna-Matthews-Olson pigment-protein complex, a molecule that has become key to understanding the role of quantum dynamics in photosynthetic exciton energy transfer. To this end, we have performed fully quantum mechanical calculations on each of the seven bacteriochlorophyll pigments that make up the complex, including a significant proportion of their protein environment (more than 2000 atoms), using linear-scaling density functional theory exploiting a recent development for the computation of excited states. Local pigment transition energies and interpigment coupling between optical transitions have been calculated and are in good agreement with the literature consensus. Comparisons between simulated and experimental optical spectra point toward future work that may help to elucidate important design principles in these nanoscale devices.


Journal of Physical Chemistry Letters | 2014

Large-scale density functional theory transition state searching in enzymes

Greg Lever; Daniel J. Cole; Richard Lonsdale; Kara E. Ranaghan; David J. Wales; Adrian J. Mulholland; Chris-Kriton Skylaris; M. C. Payne

Linear-scaling quantum mechanical density functional theory calculations have been applied to study the rearrangement of chorismate to prephenate in large-scale models of the Bacillus subtilis chorismate mutase enzyme. By treating up to 2000 atoms at a consistent quantum mechanical level of theory, we obtain an unbiased, almost parameter-free description of the transition state geometry and energetics. The activation energy barrier is calculated to be lowered by 10.5 kcal mol(-1) in the enzyme, compared with the equivalent reaction in water, which is in good agreement with experiment. Natural bond orbital analysis identifies a number of active site residues that are important for transition state stabilization in chorismate mutase. This benchmark study demonstrates that linear-scaling density functional theory techniques are capable of simulating entire enzymes at the ab initio quantum mechanical level of accuracy.


EPL | 2010

Protein-protein interactions from linear-scaling first-principles quantum-mechanical calculations

Daniel J. Cole; Chris-Kriton Skylaris; Eeson Rajendra; Ashok R. Venkitaraman; M. C. Payne

A modification of the MM-PBSA technique for calculating binding affinities of biomolecular complexes is presented. Classical molecular dynamics is used to explore the motion of the extended interface between two peptides derived from the BRC4 repeat of BRCA2 and the eukaryotic recombinase RAD51. The resulting trajectory is sampled using the linear-scaling density functional theory code, onetep, to determine from first principles, and with high computational efficiency, the relative free energies of binding of the ~2800 atom receptor-ligand complexes. This new method provides the basis for computational interrogation of protein-protein and protein-ligand interactions within fields ranging from chemical biological studies to small-molecule binding behaviour, with both unprecedented chemical accuracy and affordable computational expense.


Journal of Physical Chemistry C | 2008

Stress-Driven Oxidation Chemistry of Wet Silicon Surfaces

Lucio Colombi Ciacchi; Daniel J. Cole; M. C. Payne; Peter Gumbsch

The formation of a hydroxylated native oxide layer on Si(001) under wet conditions is studied by means of first principles molecular dynamics simulations. Water molecules are found to adsorb and dissociate on the oxidized surface leading to rupture of Si−O bonds and producing reactive sites for attack by dissolved dioxygen or hydrogen peroxide molecules. Tensile strain is found to enhance the driving force for the dissociative adsorption of water, suggesting that similar reactions could be responsible for environmentally driven subcritical crack propagation in silicon.


PLOS Computational Biology | 2011

Interrogation of the Protein-Protein Interactions between Human BRCA2 BRC Repeats and RAD51 Reveals Atomistic Determinants of Affinity

Daniel J. Cole; Eeson Rajendra; Meredith Roberts-Thomson; Bryn Hardwick; Grahame J. McKenzie; M. C. Payne; Ashok R. Venkitaraman; Chris-Kriton Skylaris

The breast cancer suppressor BRCA2 controls the recombinase RAD51 in the reactions that mediate homologous DNA recombination, an essential cellular process required for the error-free repair of DNA double-stranded breaks. The primary mode of interaction between BRCA2 and RAD51 is through the BRC repeats, which are ∼35 residue peptide motifs that interact directly with RAD51 in vitro. Human BRCA2, like its mammalian orthologues, contains 8 BRC repeats whose sequence and spacing are evolutionarily conserved. Despite their sequence conservation, there is evidence that the different human BRC repeats have distinct capacities to bind RAD51. A previously published crystal structure reports the structural basis of the interaction between human BRC4 and the catalytic core domain of RAD51. However, no structural information is available regarding the binding of the remaining seven BRC repeats to RAD51, nor is it known why the BRC repeats show marked variation in binding affinity to RAD51 despite only subtle sequence variation. To address these issues, we have performed fluorescence polarisation assays to indirectly measure relative binding affinity, and applied computational simulations to interrogate the behaviour of the eight human BRC-RAD51 complexes, as well as a suite of BRC cancer-associated mutations. Our computational approaches encompass a range of techniques designed to link sequence variation with binding free energy. They include MM-PBSA and thermodynamic integration, which are based on classical force fields, and a recently developed approach to computing binding free energies from large-scale quantum mechanical first principles calculations with the linear-scaling density functional code onetep. Our findings not only reveal how sequence variation in the BRC repeats directly affects affinity with RAD51 and provide significant new insights into the control of RAD51 by human BRCA2, but also exemplify a palette of computational and experimental tools for the analysis of protein-protein interactions for chemical biology and molecular therapeutics.


Journal of Chemical Theory and Computation | 2016

Biomolecular Force Field Parameterization via Atoms-in-Molecule Electron Density Partitioning

Daniel J. Cole; Jonah Z. Vilseck; Julian Tirado-Rives; M. C. Payne; William L. Jorgensen

Molecular mechanics force fields, which are commonly used in biomolecular modeling and computer-aided drug design, typically treat nonbonded interactions using a limited library of empirical parameters that are developed for small molecules. This approach does not account for polarization in larger molecules or proteins, and the parametrization process is labor-intensive. Using linear-scaling density functional theory and atoms-in-molecule electron density partitioning, environment-specific charges and Lennard-Jones parameters are derived directly from quantum mechanical calculations for use in biomolecular modeling of organic and biomolecular systems. The proposed methods significantly reduce the number of empirical parameters needed to construct molecular mechanics force fields, naturally include polarization effects in charge and Lennard-Jones parameters, and scale well to systems comprised of thousands of atoms, including proteins. The feasibility and benefits of this approach are demonstrated by computing free energies of hydration, properties of pure liquids, and the relative binding free energies of indole and benzofuran to the L99A mutant of T4 lysozyme.


Journal of Chemical Theory and Computation | 2014

Enhanced Monte Carlo Sampling through Replica Exchange with Solute Tempering

Daniel J. Cole; Julian Tirado-Rives; William L. Jorgensen

With a view to improving the consistency of free energy perturbation calculations in Monte Carlo simulations of protein–ligand complexes, we have implemented the replica exchange with solute tempering (REST) method in the MCPRO software. By augmenting the standard REST approach with regular attempted jumps in selected dihedral angles, our combined method facilitates sampling of ligand binding modes that are separated by high free energy barriers and ensures that computed free energy changes are considerably less dependent on the starting conditions and the chosen mutation pathway than those calculated with standard Monte Carlo sampling. We have applied the enhanced sampling method to the calculation of the activities of seven non-nucleoside inhibitors of HIV-1 reverse transcriptase, and its Tyr181Cys variant, and have shown that a range of binding orientations is possible depending on the nature of the ligand and the presence of mutations at the binding site.


Journal of Computational Chemistry | 2013

Natural Bond Orbital Analysis in the ONETEP Code: Applications to Large Protein Systems

Louis P. Lee; Daniel J. Cole; M. C. Payne; Chris-Kriton Skylaris

First principles electronic structure calculations are typically performed in terms of molecular orbitals (or bands), providing a straightforward theoretical avenue for approximations of increasing sophistication, but do not usually provide any qualitative chemical information about the system. We can derive such information via post‐processing using natural bond orbital (NBO) analysis, which produces a chemical picture of bonding in terms of localized Lewis‐type bond and lone pair orbitals that we can use to understand molecular structure and interactions. We present NBO analysis of large‐scale calculations with the ONETEP linear‐scaling density functional theory package, which we have interfaced with the NBO 5 analysis program. In ONETEP calculations involving thousands of atoms, one is typically interested in particular regions of a nanosystem whilst accounting for long‐range electronic effects from the entire system. We show that by transforming the Non‐orthogonal Generalized Wannier Functions of ONETEP to natural atomic orbitals, NBO analysis can be performed within a localized region in such a way that ensures the results are identical to an analysis on the full system. We demonstrate the capabilities of this approach by performing illustrative studies of large proteins—namely, investigating changes in charge transfer between the heme group of myoglobin and its ligands with increasing system size and between a protein and its explicit solvent, estimating the contribution of electronic delocalization to the stabilization of hydrogen bonds in the binding pocket of a drug‐receptor complex, and observing, in situ, the n → π* hyperconjugative interactions between carbonyl groups that stabilize protein backbones.


Journal of Chemical Theory and Computation | 2013

Polarized protein-specific charges from atoms-in-molecule electron density partitioning

Louis P. Lee; Daniel J. Cole; Chris-Kriton Skylaris; William L. Jorgensen; M. C. Payne

Atomic partial charges for use in traditional force fields for biomolecular simulation are often fit to the electrostatic potentials of small molecules and, hence, neglect large-scale electronic polarization. On the other hand, recent advances in atoms-in-molecule charge derivation schemes show promise for use in flexible force fields but are limited in size by the underlying quantum mechanical calculation of the electron density. Here, we implement the density derived electrostatic and chemical charges method in the linear-scaling density functional theory code ONETEP. Our implementation allows the straightforward derivation of partial atomic charges for systems comprising thousands of atoms, including entire proteins. We demonstrate that the derived charges are chemically intuitive, reproduce ab initio electrostatic potentials of proteins and are transferable between closely related systems. Simulated NMR data derived from molecular dynamics of three proteins using force fields based on the ONETEP charges are in good agreement with experiment.

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M. C. Payne

University of Cambridge

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Alex W. Chin

University of Cambridge

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