A facile one step route that introduces functionality to polymer powders for laser sintering.

Laser Sintering (LS) is a type of Additive Manufacturing (AM) exploiting laser processing of polymeric particles to produce 3D objects. Because of its ease of processability and thermo-physical properties, polyamide-12 (PA-12) represents ~95% of the polymeric materials used in LS. This constrains the functionality of the items produced, including limited available colours. Moreover, PA-12 objects tend to biofoul in wet environments. Therefore, a key challenge is to develop an inexpensive route to introduce desirable functionality to PA-12. We report a facile, clean, and scalable approach to modification of PA-12, exploiting supercritical carbon dioxide (scCO2) and free radical polymerizations to yield functionalised PA-12 materials. These can be easily printed using commercial apparatus. We demonstrate the potential by creating coloured PA-12 materials and show that the same approach can be utilized to create anti-biofouling objects. Our approach to functionalise materials could open significant new applications for AM.

Theoretical analysis of divalent cation effects on aptamer recognition of neurotransmitter targets.

Aptamer-based sensing of small molecules such as dopamine and serotonin in the brain, requires characterization of the specific aptamer sequences in solutions mimicking the in vivo environment with physiological ionic concentrations. In particular, divalent cations (Mg2+ and Ca2+) present in brain fluid, have been shown to affect the conformational dynamics of aptamers upon target recognition. Thus, for biosensors that transduce aptamer structure switching as the signal response, it is critical to interrogate the influence of divalent cations on each unique aptamer sequence. Herein, we demonstrate the potential of molecular dynamics (MD) simulations to predict the behaviour of dopamine and serotonin aptamers on sensor surfaces. The simulations enable molecular-level visualization of aptamer conformational changes that, in some cases, are significantly influenced by divalent cations. The correlations of theoretical simulations with experimental findings validate the potential for MD simulations to predict aptamer-specific behaviors on biosensors.

QuantumScents: Quantum-Mechanical Properties for 3.5k Olfactory Molecules.

Quantitative structure-odor relationships are critically important for studies related to the function of olfaction. Current literature data sets contain expert-labeled molecules but lack feature data. This paper introduces QuantumScents, a quantum mechanics augmented derivative of the Leffingwell data set. QuantumScents contains 3.5k structurally and chemically diverse molecules ranging from 2 to 30 heavy atoms (CNOS) and their corresponding 3D coordinates, total PBE0 energy, molecular dipole moment, and per-atom Hirshfeld charges, dipoles, and ratios. The authors demonstrate that Hirshfeld charges and ratios contain sufficient information to perform molecular classification by training a Message Passing Neural Network with chemprop (Heid, E.; et al. ChemRxiv, 2023, DOI: 10.26434/chemrxiv-2023-3zcfl) to predict scent labels. The QuantumScents data set is freely available on Zenodo along with the authors' code, example models, and data set generation workflow (https://zenodo.org/doi/10.5281/zenodo.8239853).

SARS-CoV2 billion-compound docking.

This dataset contains ligand conformations and docking scores for 1.4 billion molecules docked against 6 structural targets from SARS-CoV2, representing 5 unique proteins: MPro, NSP15, PLPro, RDRP, and the Spike protein. Docking was carried out using the AutoDock-GPU platform on the Summit supercomputer and Google Cloud. The docking procedure employed the Solis Wets search method to generate 20 independent ligand binding poses per compound. Each compound geometry was scored using the AutoDock free energy estimate, and rescored using RFScore v3 and DUD-E machine-learned rescoring models. Input protein structures are included, suitable for use by AutoDock-GPU and other docking programs. As the result of an exceptionally large docking campaign, this dataset represents a valuable resource for discovering trends across small molecule and protein binding sites, training AI models, and comparing to inhibitor compounds targeting SARS-CoV-2. The work also gives an example of how to organize and process data from ultra-large docking screens.

Cysteine-Selective Modification of Peptides and Proteins via Desulfurative C-C Bond Formation.

The site-selective modification of peptides and proteins facilitates the preparation of targeted therapeutic agents and tools to interrogate biochemical pathways. Among the numerous bioconjugation techniques developed to install groups of interest, those that generate C(sp3 )-C(sp3 ) bonds are significantly underrepresented despite affording proteolytically stable, biogenic linkages. Herein, a visible-light-mediated reaction is described that enables the site-selective modification of peptides and proteins via desulfurative C(sp3 )-C(sp3 ) bond formation. The reaction is rapid and high yielding in peptide systems, with comparable translation to proteins. Using this chemistry, a range of moieties is installed into model systems and an effective PTM-mimic is successfully integrated into a recombinantly expressed histone.

Free Energies of Hydrated Halide Anions: High Through-Put Computations on Clusters to Treat Rough Energy-Landscapes.

With a longer-term goal of addressing the comparative behavior of the aqueous halides F-, Cl-, Br-, and I- on the basis of quasi-chemical theory (QCT), here we study structures and free energies of hydration clusters for those anions. We confirm that energetically optimal (H2O)nX clusters, with X = Cl-, Br-, and I-, exhibit surface hydration structures. Computed free energies, based on optimized surface hydration structures utilizing a harmonic approximation, typically (but not always) disagree with experimental free energies. To remedy the harmonic approximation, we utilize single-point electronic structure calculations on cluster geometries sampled from an AIMD (ab initio molecular dynamics) simulation stream. This rough-landscape procedure is broadly satisfactory and suggests unfavorable ligand crowding as the physical effect addressed. Nevertheless, this procedure can break down when n≳4, with the characteristic discrepancy resulting from a relaxed definition of clustering in the identification of (H2O)nX clusters, including ramified structures natural in physical cluster theories. With ramified structures, the central equation for the present rough-landscape approach can acquire some inconsistency. Extension of these physical cluster theories in the direction of QCT should remedy that issue, and should be the next step in this research direction.

Molecular basis for higher affinity of SARS-CoV-2 spike RBD for human ACE2 receptor.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has caused substantially more infections, deaths, and economic disruptions than the 2002-2003 SARS-CoV. The key to understanding SARS-CoV-2's higher infectivity lies partly in its host receptor recognition mechanism. Experiments show that the human angiotensin converting enzyme 2 (ACE2) protein, which serves as the primary receptor for both CoVs, binds to the receptor binding domain (RBD) of CoV-2's spike protein stronger than SARS-CoV's spike RBD. The molecular basis for this difference in binding affinity, however, remains unexplained from X-ray structures. To go beyond insights gained from X-ray structures and investigate the role of thermal fluctuations in structure, we employ all-atom molecular dynamics simulations. Microseconds-long simulations reveal that while CoV and CoV-2 spike-ACE2 interfaces have similar conformational binding modes, CoV-2 spike interacts with ACE2 via a larger combinatorics of polar contacts, and on average, makes 45% more polar contacts. Correlation analysis and thermodynamic calculations indicate that these differences in the density and dynamics of polar contacts arise from differences in spatial arrangements of interfacial residues, and dynamical coupling between interfacial and non-interfacial residues. These results recommend that ongoing efforts to design spike-ACE2 peptide blockers will benefit from incorporating dynamical information as well as allosteric coupling effects.

Near-Ultraviolet Circular Dichroism and Two-Dimensional Spectroscopy of Polypeptides.

A fully quantitative theory of the relationship between protein conformation and optical spectroscopy would facilitate deeper insights into biophysical and simulation studies of protein dynamics and folding. In contrast to intense bands in the far-ultraviolet, near-UV bands are much weaker and have been challenging to compute theoretically. We report some advances in the accuracy of calculations in the near-UV, which were realised through the consideration of the vibrational structure of the electronic transitions of aromatic side chains.

Supercomputing Pipelines Search for Therapeutics Against COVID-19.

The urgent search for drugs to combat SARS-CoV-2 has included the use of supercomputers. The use of general-purpose graphical processing units (GPUs), massive parallelism, and new software for high-performance computing (HPC) has allowed researchers to search the vast chemical space of potential drugs faster than ever before. We developed a new drug discovery pipeline using the Summit supercomputer at Oak Ridge National Laboratory to help pioneer this effort, with new platforms that incorporate GPU-accelerated simulation and allow for the virtual screening of billions of potential drug compounds in days compared to weeks or months for their ability to inhibit SARS-COV-2 proteins. This effort will accelerate the process of developing drugs to combat the current COVID-19 pandemic and other diseases.

Protein Conformational States-A First Principles Bayesian Method.

Automated identification of protein conformational states from simulation of an ensemble of structures is a hard problem because it requires teaching a computer to recognize shapes. We adapt the naïve Bayes classifier from the machine learning community for use on atom-to-atom pairwise contacts. The result is an unsupervised learning algorithm that samples a 'distribution' over potential classification schemes. We apply the classifier to a series of test structures and one real protein, showing that it identifies the conformational transition with >95% accuracy in most cases. A nontrivial feature of our adaptation is a new connection to information entropy that allows us to vary the level of structural detail without spoiling the categorization. This is confirmed by comparing results as the number of atoms and time-samples are varied over 1.5 orders of magnitude. Further, the method's derivation from Bayesian analysis on the set of inter-atomic contacts makes it easy to understand and extend to more complex cases.

Force Fields for Macromolecular Assemblies Containing Diketopyrrolopyrrole and Thiophene.

Utilizing a force-matching procedure, we parametrize new force fields systematically for large conjugated systems. We model both conjugated polymers and molecular crystals that contain diketopyrrolopyrrole, thiophene, and thieno[3,2-b]thiophene units. These systems have recently been found to have low band gaps, which exhibit high efficiency for photovoltaic devices. The equilibrium structures, forces, and energies of the building block chromophores, diketopyrrolopyrrole, thiophene, and thieno[3,2-b]thiophene computed using our parameters are comparable to those computed using the reference electronic structure method. We assess the suitability of this new force field for electronic property calculations by comparing the electronic excitation properties computed along classical and ab initio molecular dynamics trajectories. For both trajectories, we find similar distributions of TDDFT-calculated excitation energies and oscillator strengths for the building block chromophore diketopyrrolopyrrole-thieno[3,2-b]thiophene. The structural, dynamic, and electronic properties of the macromolecular assemblies built upon these chromophores are characterized. For both polymers and molecular crystals, pronounced peaks around 0° or 180° are observed for the torsions between chromophores under ambient conditions. The high planarity in these systems can promote local ordering and π-π stacking, thereby potentially facilitating charge transport across these materials. For the model conducting polymers, we found that the fluctuations in the density of states per chain per monomer is negligibly small and does not vary significantly with chains comprising 20-40 monomers. Analysis of the electron-hole distributions and the transition density matrices indicates that the delocalized length is approximately 4-6 monomers, which is in good agreement with other theoretical and experimental studies of different conducting polymers. For the molecular crystals, our investigation of the characteristic time scale of the fluctuation in the excitonic couplings shows that a low-frequency vibration below 100 cm-1 is observed for the nearest neighbors. These observations are in line with previous studies on other molecular crystals, in which low-frequency vibrations are believed to be responsible for the large modulation of the excitonic coupling. Thus, our approach and the new force fields provide a direct route for studying the structure-property relations and the molecular level origins of the high efficiency of these classes of materials.

Dewar Benzenoids Discovered In Carbon Nanobelts.

The synthesis of cyclacene nanobelts remains an elusive goal dating back over 60 years. These molecules represent the last unsynthesized building block of carbon nanotubes and may be useful both as seed molecules for the preparation of structurally well-defined carbon nanotubes and for understanding the behavior and formation of zigzag nanotubes more broadly. Here we report the discovery that isomers containing two Dewar benzenoid rings are the preferred form for several sizes of cyclacene. The predicted lower polyradical character and higher singlet-triplet stability that these isomers possess compared with their pure benzenoid counterparts suggest that they may be more stable synthetic targets than the structures that have previously been identified. Our findings should facilitate the exploration of new routes to cyclacene synthesis through Dewar benzene chemistry.

Hydration and Dispersion Forces in Hydroxypropylcellulose Phase Behavior.

Many-body polarization and hydration forces can strongly affect the equilibrium structure and energetics of mixed phases. Accurately reproducing both forces presents a challenge to force field models because it requires balancing hydrogen bonding at short range with many-body orientational order and dispersive attraction at long range. This work reports the first comparison of experimental measurements of the pressure-area isotherm for hydroxypropylcellulose (HPC) against molecular dynamics results with four different force field models-united-atom, all-atom (OPLS and CHARMM), and Drude oscillator models. All force fields exhibit the experimentally determined, exponentially shaped repulsive force at short range. Above a critical temperature of about 40 °C and a lattice spacing of around 14 Å, HPC experiments show a reversible, heat-induced polymer aggregation into an ordered phase driven by loss of water. The nonpolarizable force fields do not display the critical point and instead show biphasic behavior at all temperatures tested. This indicates net attractive forces at intermediate lattice spacings. In contrast, the Drude polarizable force field shows positive osmotic pressure and a single, homogeneous phase over all temperatures and spacings tested. Analysis of structural data from our simulations provides several clues to help interpret these findings. Although all force fields show similar water-water hydrogen bond numbers in the mixed phase, the polarizable model predicts that water-HPC hydrogen bonds are much more favorable than HPC-HPC hydrogen bonds when polymers are dispersed. At high density, water is driven out and replaced by HPC-HPC hydrogen bonds. The polarizable force field shows that both effects have a stronger dependence on polymer density than any of the nonpolarizable models. Our observations support the conclusion that hydration forces are coupled to the polymer coordination number by local, structural waters and that long-range dispersive attraction is overestimated by pairwise additive models.

Ultrafast photodissociation dynamics of 1,4-diiodobenzene.

The photodissociation dynamics of 1,4-diiodobenzene is investigated using ultrafast time-resolved photoelectron spectroscopy. Following excitation by laser pulses at 271 nm, the excited-state dynamics is probed by resonance-enhanced multiphoton ionization with 405 nm probe pulses. A progression of Rydberg states, which come into resonance sequentially, provide a fingerprint of the dissociation dynamics of the molecule. The initial excitation decays with a lifetime of 33 ± 4 fs, in good agreement with a previous study. The spectrum is interpreted by reference to ab initio calculations at the CASPT2(18,14) level, including spin-orbit coupling. We propose that both the 5B1 and 6B1 states are excited initially, and based on the calculations, we identify diabatic spin-orbit coupled states corresponding to the main dissociation pathways.

Accelerating QM/MM Free Energy Computations via Intramolecular Force Matching.

The calculation of free energy differences between levels of theory has numerous potential pitfalls. Chief among them is the lack of overlap, i.e., ensembles generated at one level of theory (e.g., "low") not being good approximations of ensembles at the other (e.g., "high"). Numerous strategies have been devised to mitigate this issue. However, the most straightforward approach is to ensure that the "low" level ensemble more closely resembles that of the "high". Ideally, this is done without increasing computational cost. Herein, we demonstrate that by reparametrizing classical intramolecular potentials to reproduce high level forces (i.e., force matching) configurational overlap between a "low" (i.e., classical) and "high" (i.e., quantum) level can be significantly improved. This procedure is validated on two test cases and results in vastly improved convergence of free energy simulations.

Extension of Kirkwood-Buff theory to the canonical ensemble.

Kirkwood-Buff (KB) integrals are notoriously difficult to converge from a canonical simulation because they require estimating the grand-canonical radial distribution. The same essential difficulty is encountered when attempting to estimate the direct correlation function of Ornstein-Zernike theory by inverting the pair correlation functions. We present a new theory that applies to the entire, finite, simulation volume, so that no cutoff issues arise at all. The theory gives the direct correlation function for closed systems, while smoothness of the direct correlation function in reciprocal space allows calculating canonical KB integrals via a well-posed extrapolation to the origin. The present analysis method represents an improvement over previous work because it makes use of the entire simulation volume and its convergence can be accelerated using known properties of the direct correlation function. Using known interaction energy functions can make this extrapolation near perfect accuracy in the low-density case. Because finite size effects are stronger in the canonical than in the grand-canonical ensemble, we state ensemble correction formulas for the chemical potential and the KB coefficients. The new theory is illustrated with both analytical and simulation results on the 1D Ising model and a supercritical Lennard-Jones fluid. For the latter, the finite-size corrections are shown to be small.

Insertion of Dengue E into lipid bilayers studied by neutron reflectivity and molecular dynamics simulations.

The envelope (E) protein of Dengue virus rearranges to a trimeric hairpin to mediate fusion of the viral and target membranes, which is essential for infectivity. Insertion of E into the target membrane serves to anchor E and possibly also to disrupt local order within the membrane. Both aspects are likely to be affected by the depth of insertion, orientation of the trimer with respect to the membrane normal, and the interactions that form between trimer and membrane. In the present work, we resolved the depth of insertion, the tilt angle, and the fundamental interactions for the soluble portion of Dengue E trimers (sE) associated with planar lipid bilayer membranes of various combinations of 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC), 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-rac-glycerol (POPG), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE), and cholesterol (CHOL) by neutron reflectivity (NR) and by molecular dynamics (MD) simulations. The results show that the tip of E containing the fusion loop (FL) is located at the interface of the headgroups and acyl chains of the outer leaflet of the lipid bilayers, in good agreement with prior predictions. The results also indicate that E tilts with respect to the membrane normal upon insertion, promoted by either the anionic lipid POPG or CHOL. The simulations show that tilting of the protein correlates with hydrogen bond formation between lysines and arginines located on the sides of the trimer close to the tip (K246, K247, and R73) and nearby lipid headgroups. These hydrogen bonds provide a major contribution to the membrane anchoring and may help to destabilize the target membrane.

Coherent ultrafast lattice-directed reaction dynamics of triiodide anion photodissociation.

Solid-state reactions are influenced by the spatial arrangement of the reactants and the electrostatic environment of the lattice, which may enable lattice-directed chemical dynamics. Unlike the caging imposed by an inert matrix, an active lattice participates in the reaction, however, little evidence of such lattice participation has been gathered on ultrafast timescales due to the irreversibility of solid-state chemical systems. Here, by lowering the temperature to 80 K, we have been able to study the dissociative photochemistry of the triiodide anion (I3-) in single-crystal tetra-n-butylammonium triiodide using broadband transient absorption spectroscopy. We identified the coherently formed tetraiodide radical anion (I4•-) as a reaction intermediate. Its delayed appearance after that of the primary photoproduct, diiodide radical I2•-, indicates that I4•- was formed via a secondary reaction between a dissociated iodine radical (I•) and an adjacent I3-. This chemistry occurs as a result of the intermolecular interaction determined by the crystalline arrangement and is in stark contrast with previous solution studies.

Einstein-Podolsky-Rosen paradox implies a minimum achievable temperature.

This work examines the thermodynamic consequences of the repeated partial projection model for coupling a quantum system to an arbitrary series of environments under feedback control. This paper provides observational definitions of heat and work that can be realized in current laboratory setups. In contrast to other definitions, it uses only properties of the environment and the measurement outcomes, avoiding references to the "measurement" of the central system's state in any basis. These definitions are consistent with the usual laws of thermodynamics at all temperatures, while never requiring complete projective measurement of the entire system. It is shown that the back action of measurement must be counted as work rather than heat to satisfy the second law. Comparisons are made to quantum jump (unravelling) and transition-probability based definitions, many of which appear as particular limits of the present model. These limits show that our total entropy production is a lower bound on traditional definitions of heat that trace out the measurement device. Examining the master equation approximation to the process at finite measurement rates, we show that most interactions with the environment make the system unable to reach absolute zero. We give an explicit formula for the minimum temperature achievable in repeatedly measured quantum systems. The phenomenon of minimum temperature offers an explanation of recent experiments aimed at testing fluctuation theorems in the quantum realm and places a fundamental purity limit on quantum computers.