The Fe-MAN Challenge: Ferrates-Microkinetic Assessment of Numerical Quantum Chemistry.

Organometallic species, such as organoferrate ions, are prototypical nucleophiles prone to reacting with a wide range of electrophiles, including proton donors. In solution, the operation of dynamic equilibria and the simultaneous presence of several organometallic species severely complicate the analysis of these fundamentally important reactions. This can be overcome by gas-phase experiments on mass-selected ions, which allow for the determination of the microscopic reactivity of the target species. In this contribution, we focus on the reactivity of a series of trisarylferrate complexes toward 2,2,2-trifluoroethanol and 2,2-difluoroethanol. By means of mass-spectrometric measurements, we determined the experimental bimolecular rate constants kexp of the gas-phase protolysis reactions of the trisarylferrate anions FePh3- and FeMes3- with the aforementioned acids. Based on these experiments, we carried out a dual blind challenge, inviting theoretical groups to submit their best predictions for the activation barriers and/or theoretical rate constants ktheo. This provides a unique opportunity to evaluate different computational protocols under minimal bias and sets the stage for further benchmarking of quantum chemical methods and data-driven approaches in the future.

Exploring the selectivity of cytochrome P450 for enhanced novel anticancer agent synthesis.

Cytochrome P450 monooxygenases are an extensive and unique class of enzymes, which can regio- and stereo-selectively functionalise hydrocarbons by way of oxidation reactions. These enzymes are naturally occurring but have also been extensively applied in a synthesis context, where they are used as efficient biocatalysts. Recently, a biosynthetic pathway where a cytochrome P450 monooxygenase catalyses a critical step of the pathway was uncovered, leading to the production of a number of products that display high antitumour potency. In this work, we use computational techniques to gain insight into the factors that determine the relative yields of the different products. We use conformational search algorithms to understand the substrate stereochemistry. On a machine-learned 3D protein structure, we use molecular docking to obtain a library of favourable poses for substrate-protein interaction. With molecular dynamics, we investigate the most favourable poses for reactivity on a molecular level, allowing us to investigate which protein-substrate interactions favour a given product and thus gain insight into the product selectivity.

Gaseous inhibition of the transsulfuration pathway by cystathionine ß-synthase.

The transsulfuration pathway plays a key role in mammals for maintaining the balance between cysteine and homocysteine, whose concentrations are critical in several biochemical processes. Human cystathionine ß-synthase is a heme-containing, pyridoxal 5'-phosphate (PLP)-dependent enzyme found in this pathway. The heme group does not participate directly in catalysis, but has a regulatory function, whereby CO or NO binding inhibits the PLP-dependent reactions. In this study, we explore the detailed structural changes responsible for inhibition using quantum chemical calculations to validate the experimentally observed bonding patterns associated with heme CO and NO binding and molecular dynamics simulations to explore the medium-range structural changes triggered by gas binding and propagating to the PLP active site, which is more than 20 Å distant from the heme group. Our results support a previously proposed mechanical signaling model, whereby the cysteine decoordination associated with gas ligand binding leads to breaking of a hydrogen bond with an arginine residue on a neighbouring helix. In turn, this leads to a shift in position of the helix, and hence also of the PLP cofactor, ultimately disrupting a key hydrogen bond that stabilizes the PLP in its catalytically active form.

On the origin of cooperativity effects in the formation of self-assembled molecular networks at the liquid/solid interface.

In this work we investigate the behaviour of molecules at the nanoscale using scanning tunnelling microscopy in order to explore the origin of the cooperativity in the formation of self-assembled molecular networks (SAMNs) at the liquid/solid interface. By studying concentration dependence of alkoxylated dimethylbenzene, a molecular analogue to 5-alkoxylated isophthalic derivatives, but without hydrogen bonding moieties, we show that the cooperativity effect can be experimentally evaluated even for low-interacting systems and that the cooperativity in SAMN formation is its fundamental trait. We conclude that cooperativity must be a local effect and use the nearest-neighbor Ising model to reproduce the coverage vs. concentration curves. The Ising model offers a direct link between statistical thermodynamics and experimental parameters, making it a valuable tool for assessing the thermodynamics of SAMN formation.

Highly Ordered Co-Assembly of Bisurea Functionalized Molecular Switches at the Solid-Liquid Interface.

Immobilization of stimulus-responsive systems on solid surfaces is beneficial for controlled signal transmission and adaptive behavior while allowing the characterization of the functional interface with high sensitivity and high spatial resolution. Positioning of the stimuli-responsive units with nanometer-scale precision across the adaptive surface remains one of the bottlenecks in the extraction of cooperative function. Nanoscale organization, cooperativity, and amplification remain key challenges in bridging the molecular and the macroscopic worlds. Here we report on the design, synthesis, and scanning tunneling microscopy (STM) characterization of overcrowded alkene photoswitches merged in self-assembled networks physisorbed at the solid-liquid interface. A detailed anchoring strategy that ensures appropriate orientation of the switches with respect to the solid surface through the use of bis-urea groups is presented. We implement a co-assembly strategy that enables the merging of the photoswitches within physisorbed monolayers of structurally similar 'spacer' molecules. The self-assembly of the individual components and the co-assemblies was examined in detail using (sub)molecular resolution STM which confirms the robust immobilization and controlled orientation of the photoswitches within the spacer monolayers. The experimental STM data is supported by detailed molecular mechanics (MM) simulations. Different designs of the switches and the spacers were investigated which allowed us to formulate guidelines that enable the precise organization of the photoswitches in crystalline physisorbed self-assembled molecular networks.

Exploration of biochemical reactivity with a QM/MM growing string method.

In this work, we have implemented the single-ended growing string method using a hybrid internal/Cartesian coordinate scheme within our in-house QM/MM package, QoMMMa, representing the first implementation of the growing string method in the QM/MM framework. The goal of the implementation was to facilitate generation of QM/MM reaction pathways with minimal user input, and also to improve the quality of the pathways generated as compared to the widely used adiabatic mapping approach. We have validated the algorithm against a reaction which has been studied extensively in previous computational investigations - the Claisen rearrangement catalysed by chorismate mutase. The nature of the transition state and the height of the barrier was predicted well using our algorithm, where more than 88% of the pathways generated were deemed to be of production quality. Directly compared to using adiabatic mapping, we found that while our QM/MM single-ended growing string method is slightly less efficient, it readily produces reaction pathways with fewer discontinuites and thus minimises the need for involved remapping of unsatisfactory energy profiles.

Machine Learning Representations of the Three Lowest Adiabatic Electronic Potential Energy Surfaces for the ArH2+ Reactive System.

In this work, we present Gaussian process regression machine learning representations of the three lowest coupled 2A' adiabatic electronic potential energy surfaces of the ArH2+ reactive system in full dimensionality. Additionally, the nonadiabatic coupling matrix elements were calculated. These adiabatic potentials and their nonadiabatic couplings are necessary ingredients in the theoretical investigation of the nonadiabatic reaction dynamics of the Ar + H2+ → ArH+ + H and Ar+ + H2 → ArH+ + H reactions, as well as the competing charge transfer process, Ar + H2+↔ Ar+ + H2. Accurate ab initio electronic structure calculations (ic-MRCI+Q/aug-cc-pVQZ), whereby the effect of spin-orbit coupling in Ar+ has been accounted for through the state interaction method, serve as input for the machine learning training process. The potential energy surfaces are fitted with high accuracies, with root-mean-square errors on the order of 10-7 eV for the three surfaces, which meet the requirements for chemical dynamics at low temperature. It was found that quite a large number of training points (of the order of 5000 ab initio points) are needed in order to achieve these accuracies due to the complex topography of these electronic surfaces.

Molecular structure of soluble vimentin tetramers.

Intermediate filaments (IFs) are essential constituents of the metazoan cytoskeleton. A vast family of cytoplasmic IF proteins are capable of self-assembly from soluble tetrameric species into typical 10-12 nm wide filaments. The primary structure of these proteins includes the signature central 'rod' domain of ~ 300 residues which forms a dimeric α-helical coiled coil composed of three segments (coil1A, coil1B and coil2) interconnected by non-helical, flexible linkers (L1 and L12). The rod is flanked by flexible terminal head and tail domains. At present, the molecular architecture of mature IFs is only poorly known, limiting our capacity to rationalize the effect of numerous disease-related mutations found in IF proteins. Here we addressed the molecular structure of soluble vimentin tetramers which are formed by two antiparallel, staggered dimers with coil1B domains aligned (A11 tetramers). By examining a series of progressive truncations, we show that the presence of the coil1A domain is essential for the tetramer formation. In addition, we employed a novel chemical cross-linking pipeline including isotope labelling to identify intra- and interdimeric cross-links within the tetramer. We conclude that the tetramer is synergistically stabilized by the interactions of the aligned coil1B domains, the interactions between coil1A and the N-terminal portion of coil2, and the electrostatic attraction between the oppositely charged head and rod domains. Our cross-linking data indicate that, starting with a straight A11 tetramer, flexibility of linkers L1 and L12 enables 'backfolding' of both the coil1A and coil2 domains onto the tetrameric core formed by the coil1B domains. Through additional small-angle X-ray scattering experiments we show that the elongated A11 tetramers dominate in low ionic strength solutions, while there is also a significant structural flexibility especially in the terminal domains.

An automated method for graph-based chemical space exploration and transition state finding.

Algorithms that automatically explore the chemical space have been limited to chemical systems with a low number of atoms due to expensive involved quantum calculations and the large amount of possible reaction pathways. The method described here presents a novel solution to the problem of chemical exploration by generating reaction networks with heuristics based on chemical theory. First, a second version of the reaction network is determined through molecular graph transformations acting upon functional groups of the reacting. Only transformations that break two chemical bonds and form two new ones are considered, leading to a significant performance enhancement compared to previously presented algorithm. Second, energy barriers for this reaction network are estimated through quantum chemical calculations by a growing string method, which can also identify non-octet species missed during the previous step and further define the reaction network. The proposed algorithm has been successfully applied to five different chemical reactions, in all cases identifying the most important reaction pathways.

Stability profile of vimentin rod domain.

Intermediate filaments (IFs) form an essential part of the metazoan cytoskeleton. Despite a long history of research, a proper understanding of their molecular architecture and assembly process is still lacking. IFs self-assemble from elongated dimers, which are defined by their central "rod" domain. This domain forms an α-helical coiled coil consisting of three segments called coil1A, coil1B, and coil2. It has been hypothesized that the structural plasticity of the dimer, including the unraveling of some coiled-coil regions, is essential for the assembly process. To systematically explore this possibility, we have studied six 50-residue fragments covering the entire rod domain of human vimentin, a model IF protein. After creating in silico models of these fragments, their evaluation using molecular dynamics was performed. Large differences were seen across the six fragments with respect to their structural variability during a 100 ns simulation. Next, the fragments were prepared recombinantly, whereby their correct dimerization was promoted by adding short N- or C-terminal capping motifs. The capped fragments were subjected to circular dichroism measurements at varying temperatures. The obtained melting temperatures reveal the relative stabilities of individual fragments, which correlate well with in silico results. We show that the least stable regions of vimentin rod are coil1A and the first third of coil2, while the structures of coil1B and the rest of coil2 are significantly more robust. These observations are in line with the data obtained using other experimental approaches, and contribute to a better understanding of the molecular mechanisms driving IF assembly.

Microscopic Reactivity of Phenylferrate Ions toward Organyl Halides.

Despite its practical importance, organoiron chemistry remains poorly understood due to its mechanistic complexity. Here, we focus on the oxidative addition of organyl halides to phenylferrate anions in the gas phase. By mass-selecting individual phenylferrate anions, we can determine the effect of the oxidation state, the ligation, and the nuclearity of the iron complex on its reactions with a series of organyl halides RX. We find that Ph2 Fe(I)- and other low-valent ferrates are more reactive than Ph3 Fe(II)- ; Ph4 Fe(III)- is inert. The coordination of a PPh3 ligand or the presence of a second iron center lower the reactivity. Besides direct cross-coupling reactions resulting in the formation of RPh, we also observe the abstraction of halogen atoms. This reaction channel shows the readiness of organoiron species to undergo radical-type processes. Complementary DFT calculations afford further insight and rationalize the high reactivity of the Ph2 Fe(I)- complex by the exothermicity of the oxidative addition and the low barriers associated with this reaction step. At the same time, they point to the importance of changes of the spin state in the reactions of Ph3 Fe(II)- .

The Mechanism of Biochemical NO-Sensing: Insights from Computational Chemistry.

The binding of small gas molecules such as NO and CO plays a major role in the signaling routes of the human body. The sole NO-receptor in humans is soluble guanylyl cyclase (sGC) - a histidine-ligated heme protein, which, upon NO binding, activates a downstream signaling cascade. Impairment of NO-signaling is linked, among others, to cardiovascular and inflammatory diseases. In the present work, we use a combination of theoretical tools such as MD simulations, high-level quantum chemical calculations and hybrid QM/MM methods to address various aspects of NO binding and to elucidate the most likely reaction paths and the potential intermediates of the reaction. As a model system, the H-NOX protein from Shewanella oneidensis (So H-NOX) homologous to the NO-binding domain of sGC is used. The signaling route is predicted to involve NO binding to form a six-coordinate intermediate heme-NO complex, followed by relatively facile His decoordination yielding a five-coordinate adduct with NO on the distal side with possible isomerization to the proximal side through binding of a second NO and release of the first one. MD simulations show that the His sidechain can quite easily rotate outward into solvent, with this motion being accompanied in our simulations by shifts in helix positions that are consistent with this decoordination leading to significant conformational change in the protein.

Divide and Conquer. Pocket-Opening Mixed-Solvent Simulations in the Perspective of Docking Virtual Screening Applications for Drug Discovery.

The existence of a druggable binding pocket is a prerequisite for computational drug-target interaction studies including virtual screening. Retrospective studies have shown that extended sampling methods like Markov State Modeling and mixed-solvent simulations can identify cryptic pockets relevant for drug discovery. Here, we apply a combination of mixed-solvent molecular dynamics (MD) and time-structure independent component analysis (TICA) to four retrospective case studies: NPC2, the CECR2 bromodomain, TEM-1, and MCL-1. We compare previous experimental and computational findings to our results. It is shown that the successful identification of cryptic pockets depends on the system and the cosolvent probes. We used alternative TICA internal features such as the unbiased backbone coordinates or backbone dihedrals versus biased interatomic distances. We found that in the case of NPC2, TEM-1, and MCL-1, the use of unbiased features is able to identify cryptic pockets, although in the case of the CECR2 bromodomain, more specific features are required to properly capture a pocket opening. In the perspective of virtual screening applications, it is shown how docking studies with the parent ligands depend critically on the conformational state of the targets.

Pd-Catalyzed Ring Restructuring of Oxazolidines with Alkenes Leading to Fused Polycyclic Indolizines.

A palladium-catalyzed reaction of N-propargyl oxazolidines with alkenes for the synthesis of indolizidines has been developed. Through a sequential 6-exo-dig cyclization/proton transfer/[3+2] cycloaddition/cycloreversion/aromatization process, a series of fused polycyclic indolizines are obtained in moderate to good yields with high functional group tolerance. Experimental and theoretical studies suggest that the [3+2] cycloaddition/cycloreversion of the oxazolidine ring probably involves C-C and C-O bond cleavage, providing a new ring restructuring approach for the synthesis of heterocycles.

Effect of solvent motions on the dynamics of the Diels-Alder reaction.

How solvent motions affect the dynamics of chemical reactions in which the solute undergoes a substantial shape change is a fundamental but elusive issue. This work utilizes reactive simulation and Grote-Hynes theory to explore the effect of solvent motions on the dynamics of the Diels-Alder reaction (in the reverse direction, this reaction involves very substantial solute expansion) in aprotic solvents. The results reveal that the solvent environment is not sufficiently constraining to influence transition state passage dynamics, with the calculated transmission coefficients being close to unity. Even when solvent motions are suppressed or artificially slowed down, the solvent only affects the reaction dynamics in the transition state region to a very small extent. The only notable effect of solvent occurs far from the transition state region and corresponds to caging of the reactants within the reactant well.

Computational Analysis of a Prebiotic Amino Acid Synthesis with Reference to Extant Codon-Amino Acid Relationships.

Novel density functional theory calculations are presented regarding a mechanism for prebiotic amino acid synthesis from alpha-keto acids that was suggested to happen via catalysis by dinucleotide species. Our results were analysed with comparison to the original hypothesis (Copley et al., PNAS, 2005, 102, 4442-4447). It was shown that the keto acid-dinucleotide hypothesis for possible prebiotic amino acid synthesis was plausible based on an initial computational analysis, and details of the structures for the intermediates and transition states showed that there was wide scope for interactions between the keto acid and dinucleotide moieties that could affect the free energy profiles and lead to the required proto-metabolic selectivity.

On the Use of Normalized Metrics for Density Sensitivity Analysis in DFT.

In the past years, there has been a discussion about how the errors in density functional theory might be related to errors in the self-consistent densities obtained from different density functional approximations. This, in turn, brings up the discussion about the different ways in which we can measure such errors and develop metrics that assess the sensitivity of calculated energies to changes in the density. It is important to realize that there cannot be a unique metric in order to look at this density sensitivity, simultaneously needing size-extensive and size-intensive metrics. In this study, we report two metrics that are widely applicable to any density functional approximation. We also show how they can be used to classify different chemical systems of interest with respect to their sensitivity to small variations in the density.