Domain Analysis and Motif Matcher (DAMM): A Program to Predict Selectivity Determinants in Monosiga brevicollis PDZ Domains Using Human PDZ Data

Choanoflagellates are single-celled eukaryotes with complex signaling pathways. They are considered the closest non-metazoan ancestors to mammals and other metazoans and form multicellular-like states called rosettes. The choanoflagellate Monosiga brevicollis contains over 150 PDZ domains, an important peptide-binding domain in all three domains of life (Archaea, Bacteria, and Eukarya). Therefore, an understanding of PDZ domain signaling pathways in choanoflagellates may provide insight into the origins of multicellularity. PDZ domains recognize the C-terminus of target proteins and regulate signaling and trafficking pathways, as well as cellular adhesion. Here, we developed a computational software suite, Domain Analysis and Motif Matcher (DAMM), that analyzes peptide-binding cleft sequence identity as compared with human PDZ domains and that can be used in combination with literature searches of known human PDZ-interacting sequences to predict target specificity in choanoflagellate PDZ domains. We used this program, protein biochemistry, fluorescence polarization, and structural analyses to characterize the specificity of A9UPE9_MONBE, a M. brevicollis PDZ domain-containing protein with no homology to any metazoan protein, finding that its PDZ domain is most similar to those of the DLG family. We then identified two endogenous sequences that bind A9UPE9 PDZ with <100 μM affinity, a value commonly considered the threshold for cellular PDZ–peptide interactions. Taken together, this approach can be used to predict cellular targets of previously uncharacterized PDZ domains in choanoflagellates and other organisms. Our data contribute to investigations into choanoflagellate signaling and how it informs metazoan evolution.     

Fitting quantum machine learning potentials to experimental free energy data: predicting tautomer ratios in solution

The computation of tautomer ratios of druglike molecules is enormously important in computer-aided drug discovery, as over a quarter of all approved drugs can populate multiple tautomeric species in solution. Unfortunately, accurate calculations of aqueous tautomer ratios—the degree to which these species must be penalized in order to correctly account for tautomers in modeling binding for computer-aided drug discovery—is surprisingly difficult. While quantum chemical approaches to computing aqueous tautomer ratios using continuum solvent models and rigid-rotor harmonic-oscillator thermochemistry are currently state of the art, these methods are still surprisingly inaccurate despite their enormous computational expense. Here, we show that a major source of this inaccuracy lies in the breakdown of the standard approach to accounting for quantum chemical thermochemistry using rigid rotor harmonic oscillator (RRHO) approximations, which are frustrated by the complex conformational landscape introduced by the migration of double bonds, creation of stereocenters, and introduction of multiple conformations separated by low energetic barriers induced by migration of a single proton. Using quantum machine learning (QML) methods that allow us to compute potential energies with quantum chemical accuracy at a fraction of the cost, we show how rigorous relative alchemical free energy calculations can be used to compute tautomer ratios in vacuum free from the limitations introduced by RRHO approximations. Furthermore, since the parameters of QML methods are tunable, we show how we can train these models to correct limitations in the underlying learned quantum chemical potential energy surface using free energies, enabling these methods to learn to generalize tautomer free energies across a broader range of predictions.

We show how alchemical free energies can be calculated with QML potentials to identify deficiencies in RRHO approximations for computing tautomeric free energies, and how these potentials can be learned from experiment to improve prediction accuracy.     

Toeplitz Operators on the Fock Space

We study Toeplitz operators on the Fock space with positive measures as symbols. Main results include characterizations of Fock–Carleson measures, bounded Toeplitz operators, compact Toeplitz operators, and Toeplitz operators in the Schatten p-classes.     

Projected index computed tomography

Projected index computed tomography (PICT) is a new imaging technique that provides a computed reconstruction of the index of refraction of a sample. PICT makes use of data from standard optical coherence tomography images taken from several view angles to determine a mapping of the refractive indices of the sample. A rectilinear propagation model is assumed, so the data are understood to be related to the line integral of the refractive index in the beam paths. These data thus provide a set of angular projections of the sample. The spatial distribution of the index of the object may then be reconstructed by use of standard filtered backprojection techniques. The resultant PICT images are free of the spatial distortion that is inherent in standard optical cross-sectional images and correspond well to the manufactured dimensions of specific samples.     

Deconvolution filtering: Temporal smoothing revisited

Inferences made from analysis of BOLD data regarding neural processes are potentially confounded by multiple competing sources: cardiac and respiratory signals, thermal effects, scanner drift, and motion-induced signal intensity changes. To address this problem, we propose deconvolution filtering, a process of systematically deconvolving and reconvolving the BOLD signal via the hemodynamic response function such that the resultant signal is composed of maximally likely neural and neurovascular signals. To test the validity of this approach, we compared the accuracy of BOLD signal variants (i.e., unfiltered, deconvolution filtered, band-pass filtered, and optimized band-pass filtered BOLD signals) in identifying useful properties of highly confounded, simulated BOLD data: (1) reconstructing the true, unconfounded BOLD signal, (2) correlation with the true, unconfounded BOLD signal, and (3) reconstructing the true functional connectivity of a three-node neural system. We also tested this approach by detecting task activation in BOLD data recorded from healthy adolescent girls (control) during an emotion processing task.     

Antifreeze Protein‐Induced Selective Crystallization of a New Thermodynamically and Kinetically Less Preferred Molecular Crystal

The formation of a new, dihydrate crystalline form of 5‐methyluridine (m⁵U) was selectively induced by a protein additive, antifreeze protein (AFP) in a highly efficient manner (in 10^?6 molar scale, whereas known kinetic additives need 0.1 molar scale). The hemihydrate form (form I, the only previously known crystalline form of m⁵U) and the dihydrate form of m⁵U (form II) obtained herein were characterized using X‐ray crystallography and differential scanning calorimetry (DSC). Compared to form I, remarkably, form II is thermodynamically and kinetically less preferred. The presence of AFP can selectively inhibit the appearance of form I and hence allows the growth of form II, the pure form of which cannot grow directly from m⁵U supersaturated solutions under the same conditions. An explanation supported by both experimental and theoretical results is provided for the AFP‐induced selection process. Implications on AFP‐induced ice shape changes are also discussed. Control of crystallization from supersaturated solutions is of great interest in both fundamental research and practical applications in fields like chemistry, pharmacology and materials science. These findings suggest that crystallization processes with AFPs could be valuable for selective growth of hydrates and polymorphs of important pharmaceutical compounds.     

Unexpectedly similar charge transfer rates through benzo-annulated bicyclo[2.2.2]octanes

A 4-(pyrrolidin-1-yl)phenyl electron donor and 10-cyanoanthracen-9-yl electron acceptor are attached via alkyne linkages to the bridgehead carbon atoms of bicyclo[2.2.2]octane and all three benzo-annulated bicyclo[2.2.2]octanes. The sigma-system of bicyclo[2.2.2]octane provides a scaffold having nearly constant bridge geometry on which to append multiple, weakly interacting benzo pi-bridges, so that the effect of incrementally increasing numbers of pi-bridges on electron transfer rates can be studied. Surprisingly, photoinduced charge transfer rates measured by transient absorption spectroscopy in toluene show no benefit from increasing the number of bridge pi-systems, suggesting dominant transport through the sigma-system. Even more surprisingly, the significant changes in hybridization undergone by the sigma-system as a result of benzo-annulation also appear to have no effect on the charge transfer rates. Natural Bond Orbital analysis is applied to both sigma- and pi-communication pathways. The transient absorption spectra obtained in 2-methyltetrahydrofuran (MTHF) show small differences between the benzo-annulated molecules that are attributed to changes in solvation. All charge transfer rates increase significantly upon cooling the MTHF solutions to their glassy state. This behavior is rationalized using combined molecular dynamics/electronic structure trajectories.     

Translational diffusion of macromolecules and nanoparticles modeled as non-overlapping bead arrays in an effective medium

There are three objectives to the present work. First, starting from a boundary element (BE) formulation of low Reynolds number hydrodynamics, model the translational diffusion of macromolecules modeled as an array of non-overlapping beads, and show how this approach is equivalent to previous formulations of "bead hydrodynamics" and under what conditions. Second, show how this approach can be improved upon by accounting for the variation in forces over the surfaces of individual beads and also extending the approach to a gel modeled as an effective medium, EM. Third, develop a "combined obstruction and hydrodynamic effect" model of the translational diffusion of irregularly shaped macromolecules in a gel. In one of the cases studied, the BE approach is shown to be equivalent to previous "bead model" formulations in which intersubunit hydrodynamic interaction is modeled using the Rotne-Prager tensor. A bead model that accounts for the variation in hydrodynamic stress forces over the individual bead surfaces is shown to be in best agreement with exact results for simple bead arrays made up of 2-4 subunits. The translational diffusion of rods, modeled as strings of from 2 to 100 touching beads in dilute gels is examined. Interpolation formulas valid over a range of gel concentrations and rod lengths are derived for the parallel and perpendicular components of the diffusion tensor as well as the orientationally averaged diffusion tensor. The EM model accounts for the long-range hydrodynamic interaction exerted by the gel support matrix on the diffusing particle of interest but does not account for the reduction in diffusion caused by the direct obstruction of the gel, or steric effect. Both effects are accounted for by writing the translational diffusion in a gel as the product of two terms representing long-range hydrodynamic interaction and steric effects. Finally, the diffusion of a 564 base pair DNA in a 2% agarose gel is examined and model results are compared to experiment (Pluen, A.; Netti, P. A.; Jain, R. K.; Berk, D. A. Biophys. J. 1999, 77, 542-552). For reasonable choices of model parameters, fair agreement between theory and experiment is achieved.     

Reversible bridge-mediated excited-state symmetry breaking in stilbene-linked DNA dumbbells

The excited-state behavior of synthetic DNA dumbbells possessing stilbenedicarboxamide (Sa) linkers separated by short A-tracts or alternating A-T base-pair sequences has been investigated by means of fluorescence and transient absorption spectroscopy. Electronic excitation of the Sa chromophores results in conversion of a locally excited state to a charge-separated state in which one Sa is reduced and the other is oxidized. This symmetry-breaking process occurs exclusively via a multistep mechanism-hole injection followed by hole transport and hole trapping-even at short distances. Rate constants for charge separation are strongly distance-dependent at short distances but become less so at longer distances. Disruption of the A-tract by inversion of a single A-T base pair results in a pronounced decrease in both the rate constant and efficiency of charge separation. Hole trapping by Sa is highly reversible, resulting in rapid charge recombination that occurs via the reverse of the charge separation process: hole detrapping, hole transport, and charge return to regenerate the locally excited Sa singlet state. These results differ in several significant respects from those previously reported for guanine or stilbenediether as hole traps. Neither charge separation nor charge recombination occur via a single-step superexchange mechanism, and hole trapping is slower and detrapping faster when Sa serves as the electron donor. Both the occurrence of symmetry breaking and reversible hole trapping by a shallow trap in a DNA-based system are without precedent.