Toward an extreme-scale electronic structure system.

Electronic structure calculations have the potential to predict key matter transformations for applications of strategic technological importance, from drug discovery to material science and catalysis. However, a predictive physicochemical characterization of these processes often requires accurate quantum chemical modeling of complex molecular systems with hundreds to thousands of atoms. Due to the computationally demanding nature of electronic structure calculations and the complexity of modern high-performance computing hardware, quantum chemistry software has historically failed to operate at such large molecular scales with accuracy and speed that are useful in practice.

Negating coordinative cysteine and methionine residues during metathesis of unprotected peptides.

Ru-Alkylidene catalysed olefin metathesis generates metabolically stable cystine bridge peptidomimetics with defined geometry. Deleterious coordinative bonding to the catalyst by sulfur-containing functionality found in cysteine and methionine residues can be negated by and reversible oxidation of thiol and thioether functionality, as disulfides and S-oxides respectively, to facilitate high yielding ring-closing and cross metathesis of bioorthogonally protected peptides.

Appropriate clusterset selection for the prediction of thermodynamic properties of liquid water with QCE theory.

Evident in many physical and chemical phenomena, thermodynamics is the study of how energy is stored, transformed and transferred in a molecule or material. However, prediction of these properties with simulation techniques is a non-trivial task as several factors such as composition and intermolecular interactions come into play. While molecular dynamics and molecular dynamics are the most common techniques for the prediction of thermodynamic properties, there exists many shortcomings associated with their use.

Structural elucidation of polydopamine facilitated by ionic liquid solvation.

Minimal understanding of the formation mechanism and structure of polydopamine (pDA) and its natural analogue, eumelanin, impedes the practical application of these versatile polymers and limits our knowledge of the origin of melanoma. The lack of conclusive structural evidence stems from the insolubility of these materials, which has spawned significantly diverse suggestions of pDA's structure in the literature. We discovered that pDA is soluble in certain ionic liquids.

Accurate Prediction of Three-Body Intermolecular Interactions via Electron Deformation Density-Based Machine Learning.

This work extends the electron deformation density-based descriptor, originally developed in the electron deformation density-based interaction energy machine learning (EDDIE-ML) algorithm to predict dimer interaction energies, to the prediction of three-body interactions in trimers. Using a sequential learning process to select the training data, the resulting Gaussian process regression (GPR) model predicts the three-body interaction energy within 0.2 kcal mol of the SRS-MP2/cc-pVTZ reference values for the 3B69 and S22-3 trimer data sets.