Migration of para-Nitrophenyl Groups in Methyl Pyranosides: Configuration and Conformation Determine the Kinetics.

para-Nitrophenyl (PNP) ethers of glycosides are important building blocks en route to functional carbohydrates. They are stable in neutral media, however, under basic conditions such as during the Zemplén deacylation of sugars, aryl migration is frequently observed. We have employed a library of O-PNP-substituted methyl glycosides of the manno-, galacto-, gluco- and altro-series to study the kinetics of aryl migration in MeOH/sodium methoxide using NMR spectroscopy revealing that migration between cis-oriented OH groups is faster than between trans-oriented ones.

Advancing Optoglycomics: Two Orthogonal Azobenzene Glycoside Antennas in One Glycocluster-Synthesis, Switching Cycles, Kinetics and Molecular Dynamics.

Carbohydrate recognition is essential for numerous biological processes and is governed by various factors within the supramolecular environment of the cell. Photoswitchable glycoconjugates have proven as valuable tools for the investigation and modulation of carbohydrate recognition as they allow to control the relative orientation of sugar ligands by light. In order to advance the possibilities of such an "optoglycomics" approach for the glycosciences, we have synthesized a biantennary glycocluster in which two glycoazobenzene antennas are conjugated to the 3- and 6-position of a scaffold glycoside.

On the brink of self-hydration: the water heptadecamer.

For pure, neutral, isolated molecular clusters, (HO) marks the transition from structures with all water molecules on the cluster surface to water self-hydration, , cluster structures around one central water molecule. Getting this right with water model potentials turns out to be challenging. Even the best water potentials currently available, which reproduce collective properties very well, still deliver contradicting results for (HO), when different low-energy isomers from global structure optimizations are examined.

Comparison of Implicit and Explicit Solvent Approaches in Ab Initio Evaluation of Thermochemistry in Solution: Application in Studying Boron Isotope Fractionation in Water.

Evaluation of thermochemistry in solution plays a key role in numerous fields. For this task, the solvent effects are commonly included in theoretical computations based on either implicit or explicit solvent approaches. In the present study, we evaluate and compare the performance of some of the most widely applied methods based on these two approaches.

Dependence of Vaporization Enthalpy on Molecular Surfaces and Temperature: Thermodynamically Effective Molecular Surfaces.

Approximation of molecular surfaces is of central importance in numerous scientific fields. In this study we theoretically derive a physical model to relate phase-change thermodynamics to molecular surfaces. The model allows accurately predicting vaporization enthalpy of compounds for a wide temperature range without requiring any empirical parameter.

Graph-based Automated Macro-Molecule Assembly.

We present a general molecular framework assembly algorithm that takes a largely arbitrary molecular fragment database and a user-supplied target template graph as input. Automatic assembly of molecular fragments from the database, following a prescribed, user-supplied set of connection rules, then turns the template graph into an actual, chemically reasonable molecular framework. Assembly capabilities of our algorithm are tested by producing several abstract, closed-loop shapes.

Implicitly perturbed Hamiltonian as a class of versatile and general-purpose molecular representations for machine learning.

Unraveling challenging problems by machine learning has recently become a hot topic in many scientific disciplines. For developing rigorous machine-learning models to study problems of interest in molecular sciences, translating molecular structures to quantitative representations as suitable machine-learning inputs play a central role. Many different molecular representations and the state-of-the-art ones, although efficient in studying numerous molecular features, still are suboptimal in many challenging cases, as discussed in the context of the present research.

Improved prediction of solvation free energies by machine-learning polarizable continuum solvation model.

Theoretical estimation of solvation free energy by continuum solvation models, as a standard approach in computational chemistry, is extensively applied by a broad range of scientific disciplines. Nevertheless, the current widely accepted solvation models are either inaccurate in reproducing experimentally determined solvation free energies or require a number of macroscopic observables which are not always readily available. In the present study, we develop and introduce the Machine-Learning Polarizable Continuum solvation Model (ML-PCM) for a substantial improvement of the predictability of solvation free energy.

Globally optimal catalytic fields for a Diels-Alder reaction.

In a previous paper [M. Dittner and B. Hartke, J.

Exploring self-organization of molecular tether molecules on a gold surface by global structure optimization.

We employ nondeterministic global cluster structure optimization, based on the evolutionary algorithms paradigm, to model the self-assembly of complex molecules on a surface. As a real-life application example directly related to many recent experiments, we use this approach for the assembly of triazatriangulene "platform" molecules on the Au(111) surface. Without additional restrictions like spatial discretizations, coarse-graining or precalculated adsorption poses, and despite the proof-of-principle character of this study, we achieve satisfactory qualitative agreement with several experimental observations and can provide answers to questions that experiments on these species had left open so far.

Axitinib: A Photoswitchable Approved Tyrosine Kinase Inhibitor.

The goal of photopharmacology is to develop photoswitchable enzyme modulators as tunable (pro-)drugs that can be spatially and temporally controlled by light. In this context, the tyrosine kinase inhibitor axitinib, which contains a photosensitive stilbene-like moiety that allows for E/Z isomerization, is of interest. Axitinib is an approved drug that targets the vascular endothelial growth factor receptor 2 (VEGFR2) and is licensed for second-line therapy of renal cell carcinoma.

Globally Optimal Catalytic Fields - Inverse Design of Abstract Embeddings for Maximum Reaction Rate Acceleration.

The search for, and understanding of, good catalysts for chemical reactions is a central issue for chemists. Here, we present first steps toward developing a general computational framework to better support this task. This framework combines efficient, unbiased global optimization techniques with an abstract representation of the catalytic environment, to shrink the search space.

Resonance dynamics of DCO (X̃A) simulated with the dynamically pruned discrete variable representation (DP-DVR).

Selected resonance states of the deuterated formyl radical in the electronic ground state X̃A are computed using our recently introduced dynamically pruned discrete variable representation [H. R. Larsson, B.

Cluster structures influenced by interaction with a surface.

Clusters on surfaces are vitally important for nanotechnological applications. Clearly, cluster-surface interactions heavily influence the preferred cluster structures, compared to clusters in vacuum. Nevertheless, systematic explorations and an in-depth understanding of these interactions and how they determine the cluster structures are still lacking.

Simulations of optically switchable molecular machines for particle transport.

A promising application for design and deployment of molecular machines is nanoscale transport, driven by artificial cilia. In this contribution, we present several further steps toward this goal, beyond our first-generation artificial cilium (Raeker et al., J.

Ultrafast dynamics of UV-excited trans- and cis-ferulic acid in aqueous solutions.

The ultrafast UV-induced processes of the neutral, anionic and dianionic forms of trans- and cis-ferulic acid (FA) in aqueous solution were studied by static and femtosecond time-resolved emission and absorption spectroscopy combined with quantum chemical calculations. In all cases, initial excitation populates the first ππ* state. For the dianionic cis-isomer cFA, electronic deactivation takes place with a time constant of only 1.

Full-Dimensional Excited-State Intramolecular Proton Transfer Dynamics of Salicylic Acid.

Salicylic acid (SAc) and its excited-state intramolecular proton transfer (ESIPT) capabilities have been studied both experimentally and theoretically by static calculations. However, to our knowledge, no radiationless pathway has been proposed so far. Instead, excited-state deactivation was only investigated via fluorescence.

Cheap but accurate calculation of chemical reaction rate constants from ab initio data, via system-specific, black-box force fields.

Building on the recently published quantum-mechanically derived force field (QMDFF) and its empirical valence bond extension, EVB-QMDFF, it is now possible to generate a reliable potential energy surface for any given elementary reaction step in an essentially black box manner. This requires a limited and pre-defined set of reference data near the reaction path and generates an accurate approximation of the reference potential energy surface, on and off the reaction path. This intermediate representation can be used to generate reaction rate data, with far better accuracy and reliability than with traditional approaches based on transition state theory (TST) or variational extensions thereof (VTST), even if those include sophisticated tunneling corrections.

Error-Safe, Portable, and Efficient Evolutionary Algorithms Implementation with High Scalability.

We present an efficient massively parallel implementation of genetic algorithms for chemical and materials science problems, solely based on Java virtual machine (JVM) technologies and standard networking protocols. The lack of complicated dependencies allows for a highly portable solution exploiting strongly heterogeneous components within a single computational context. At runtime, our implementation is almost completely immune to hardware failure, and additional computational resources can be added or subtracted dynamically, if needed.

reaxFF Reactive Force Field for Disulfide Mechanochemistry, Fitted to Multireference ab Initio Data.

Mechanochemistry, in particular in the form of single-molecule atomic force microscopy experiments, is difficult to model theoretically, for two reasons: Covalent bond breaking is not captured accurately by single-determinant, single-reference quantum chemistry methods, and experimental times of milliseconds or longer are hard to simulate with any approach. Reactive force fields have the potential to alleviate both problems, as demonstrated in this work: Using nondeterministic global parameter optimization by evolutionary algorithms, we have fitted a reaxFF force field to high-level multireference ab initio data for disulfides. The resulting force field can be used to reliably model large, multifunctional mechanochemistry units with disulfide bonds as designed breaking points.

Efficient global optimization of reactive force-field parameters.

Reactive force fields make low-cost simulations of chemical reactions possible. However, optimizing them for a given chemical system is difficult and time-consuming. We present a high-performance implementation of global force-field parameter optimization, which delivers parameter sets of the same quality with much less effort and in far less time than before, and also offers excellent parallel scaling.

Reactive force fields made simple.

Generating a reactive force field for a given chemical reaction is turned from a many-months project for experts into a task of a few hours for a non-specialist, by joining the newly developed quantum-mechanically derived force field (QMDFF) and Warshel's time-tested empirical valence bond (EVB) idea. Three first example applications demonstrate that this works not just for simple atom exchange but also for more complicated reactions.

Observable-targeting global cluster structure optimization.

Traditionally, global cluster structure optimization is done by minimizing energy. As an alternative, we propose minimizing the difference between actual experimental observables and their simulated counterparts. To validate and explain this approach, test cases for small clusters are shown.

Pinpointing mechanochemical bond rupture by embedding the mechanophore into a macrocycle.

Mechanophores contain a mechanically labile bond that can be broken by an external mechanical force. Quantitative measurement and control of the applied force is possible through atomic force microscopy (AFM). A macrocycle was synthesized that contains both the mechanophore and an aliphatic chain that acts as a "safety line" upon bond breaking.

A graph-based short-cut to low-energy structures.

A new graph-based move class for global optimization of cluster structures is presented. Its performance and efficiency is analyzed for water clusters (H2O)n, n = 24, 61. This analysis indicates superior basin exploitation capabilities of the new move class for large clusters, compared to traditional moves.