Publications

Venom peptide toxins such as conotoxins play a critical role in the characterization of nicotinic acetylcholine receptor (nAChR) structure and function and have potential as nervous system therapeutics as well. However, the lack of solved structures of conotoxins bound to nAChRs and the large size of these peptides are barriers to their computational docking and design. We addressed these challenges in the context of the α4β2 nAChR, a widespread ligand-gated ion channel in the brain and a target for nicotine addiction therapy, and the 19-residue conotoxin α-GID that antagonizes it. We developed a docking algorithm, ToxDock, which used ensemble-docking and extensive conformational sampling to dock α-GID and its analogs to an α4β2 nAChR homology model. Experimental testing demonstrated that a virtual screen with ToxDock correctly identified three bioactive α-GID mutants (α-GID[A10V], α-GID[V13I], and α-GID[V13Y]) and one inactive variant (α-GID[A10Q]). Two mutants, α-GID[A10V] and α-GID[V13Y], had substantially reduced potency at the human α7 nAChR relative to α-GID, a desirable feature for α-GID analogs. The general usefulness of the docking algorithm was highlighted by redocking of peptide toxins to two ion channels and a binding protein in which the peptide toxins successfully reverted back to near-native crystallographic poses after being perturbed. Our results demonstrate that ToxDock can overcome two fundamental challenges of docking large toxin peptides to ion channel homology models, as exemplified by the α-GID:α4β2 nAChR complex, and is extendable to other toxin peptides and ion channels.

We explore the significance of phenylalanine outside of the phosphotriesterase (PTE) dimer interface through mutagenesis studies and computational modeling. Previous studies have demonstrated that the residue-specific incorporation of para-fluorophenylalanine (pFF) into PTE improves stability, suggesting the importance of phenylalanines in stabilization of the dimer. However, this comes at a cost of decreased solubility due to pFF incorporation into other parts of the protein. Motivated by this, eight single solvent-exposed phenylalanine mutants are evaluated via ROSETTA and good correspondence between experiments and these predictions is observed. Three residues, F304, F327, and F335, appear to be important for PTE activity and stability, even though they do not reside in the dimer interface region or active site. While the remaining mutants do not significantly affect structure or activity, one variant, F306L, reveals improved activity at ambient and elevated temperatures. These studies provide further insight into role of these residues on PTE function and stability.

Determining the three-dimensional (3D) structure of proteins and protein complexes at atomic resolution is a fundamental task in structural biology. Over the last decade, remarkable progress has been made using “single particle” cryo-electron microscopy (cryo-EM) for this purpose. In cryo-EM, hundreds of thousands of two-dimensional (2D) images are obtained of individual copies of the same particle, each held in a thin sheet of ice at some unknown orientation. Each image corresponds to the noisy projection of the particle's electron-scattering density. The reconstruction of a high-resolution image from this data is typically formulated as a nonlinear, nonconvex optimization problem for unknowns which encode the angular pose and lateral offset of each particle. Since there are hundreds of thousands of such parameters, this leads to a very CPU-intensive task---limiting both the number of particle images which can be processed and the number of independent reconstructions which can be carried out for the purpose of statistical validation. Moreover, existing reconstruction methods typically require a good initial guess to converge. Here, we propose a deterministic method for high-resolution reconstruction that operates in an ab initio manner---that is, without the need for an initial guess. It requires a predictable and relatively modest amount of computational effort, by marching out radially in the Fourier domain from low to high frequency, increasing the resolution by a fixed increment at each step.

Read More: http://epubs.siam.org/doi/abs/10.1137/16M1097171

The combination of charge and spin degrees of freedom with electronic correlations in condensed matter systems leads to a rich array of phenomena, such as magnetism, superconductivity, and novel conduction mechanisms. While such phenomena are observed in bulk materials, a richer array of behaviors becomes possible when these degrees of freedom are controlled in atomically layered heterostructures, where one can constrain dimensionality and impose interfacial boundary conditions. Here, we unlock a host of unique, hidden electronic and magnetic phase transitions in
NdNi
O
3
while approaching the two-dimensional (2D) limit, resulting from the differing influences of dimensional confinement and interfacial coupling. Most notably, we discover a phase in fully 2D, single-layer
NdNi
O
3
, in which all signatures of the bulk magnetic and charge ordering are found to vanish. In addition, for quasi-two-dimensional layers down to a thickness of two unit cells, bulk-type ordering persists but separates from the onset of insulating behavior in a manner distinct from that found in the bulk or thin-film nickelates. Using resonant x-ray spectroscopies, first-principles theory, and model calculations, we propose that the single-layer phase suppression results from an alternative mechanism of interfacial electronic reconstruction based on ionicity differences across the interface, while the phase separation in multilayer
NdNi
O
3
emerges due to enhanced 2D fluctuations. These findings provide insights into the intertwined mechanisms of charge and spin ordering in strongly correlated systems in reduced dimensions and illustrate the ability to use atomic layering to access hidden phases.

One of the puzzles in the recent observations of gravitational waves from binary black hole mergers is the observed low (projected) spins of the progenitor black holes. In two of the four events, GW150914, and the recent GW170104, the observed spins are most likely negative (but consistent with zero). In the third case LVT151012 it is practically zero and only in the forth case, GW151226, the spin is positive but low. These observations are puzzling within the field binary scenario in which positive higher spins are expected. Considering the most favorable Wolfe Rayet (WR) progenitors we estimate the expected spin distribution for different evolution scenarios and compare it to the observations. With typical parameters one expects a significant fraction (≥25%) of the mergers to have high effective spin values. However due to uncertainties in the outcome of the common envelope phase (typical separation and whether the stars are rotating or not) and in the late stages of massive star evolution (the strength of the winds) one cannot rule our scenarios in which the expected spins are low. While observations of high effective spin events will support this scenario, further observations of negative spin events would rule it out.

The Brownian motion of two particles in three dimensions serves as a model for predicting the diffusion-limited reaction rate, as first discussed by von Smoluchowski. Deutch and Felderhof extended the calculation to account for hydrodynamic interactions between the particles and the target, which results in a reduction of the rate coefficient by about half. Many chemical reactions take place in quasi-two-dimensional systems, such as on the membrane or surface of a cell. We perform a Smoluchowski-like calculation in a quasi-two-dimensional geometry, i.e., a membrane surrounded by fluid, and account for hydrodynamic interactions between the particles. We show that rate coefficients are reduced relative to the case of no interactions. The reduction is more pronounced than the three-dimensional case due to the long-range nature of two-dimensional flows.

Use of low resolution single cell DNA FISH and population based high resolution chromosome conformation capture techniques have highlighted the importance of pairwise chromatin interactions in gene regulation. However, it is unlikely that associations involving regulatory elements act in isolation of other interacting partners that also influence their impact. Indeed, the influence of multi-loci interactions remains something of an enigma as beyond low-resolution DNA FISH we do not have the appropriate tools to analyze these. Here we present a method that uses standard 4C-seq data to identify multi-loci interactions from the same cell. We demonstrate the feasibility of our method using 4C-seq data sets that identify known pairwise and novel tri-loci interactions involving the Tcrb and Igk antigen receptor enhancers. We further show that the three Igk enhancers, MiEκ, 3′Eκ and Edκ, interact simultaneously in this super-enhancer cluster, which add to our previous findings showing that loss of one element decreases interactions between all three elements as well as reducing their transcriptional output. These findings underscore the functional importance of simultaneous interactions and provide new insight into the relationship between enhancer elements. Our method opens the door for studying multi-loci interactions and their impact on gene regulation in other biological settings.

Background

The preparation consisting of a head-fixed mouse on a spherical or cylindrical treadmill offers unique advantages in a variety of experimental contexts. Head fixation provides the mechanical stability necessary for optical and electrophysiological recordings and stimulation. Additionally, it can be combined with virtual environments such as T-mazes, enabling these types of recording during diverse behaviors.
New method

In this paper we present a low-cost, easy-to-build acquisition system, along with scalable computational methods to quantitatively measure behavior (locomotion and paws, whiskers, and tail motion patterns) in head-fixed mice locomoting on cylindrical or spherical treadmills.

Existing methods

Several custom supervised and unsupervised methods have been developed for measuring behavior in mice. However, to date there is no low-cost, turn-key, general-purpose, and scalable system for acquiring and quantifying behavior in mice.

Results

We benchmark our algorithms against ground truth data generated either by manual labeling or by simpler methods of feature extraction. We demonstrate that our algorithms achieve good performance, both in supervised and unsupervised settings.

Conclusions

We present a low-cost suite of tools for behavioral quantification, which serve as valuable complements to recording and stimulation technologies being developed for the head-fixed mouse preparation.

In the microenvironment of a malignancy, tumor cells do not exist in isolation, but rather in a diverse ecosystem consisting not only of heterogeneous tumor-cell clones, but also normal cell types such as fibroblasts, vasculature, and an extensive pool of immune cells at numerous possible stages of activation and differentiation. This results in a complex interplay of diverse cellular signaling systems, where the immune cell component is now established to influence cancer progression and therapeutic response. It is experimentally difficult and laborious to comprehensively and systematically profile these distinct cell types from heterogeneous tumor samples in order to capitalize on potential therapeutic and biomarker discoveries. One emerging solution to address this challenge is to computationally extract cell-type specific information directly from bulk tumors. Such in silico approaches are advantageous because they can capture both the cell-type specific profiles and the tissue systems level of cell-cell interactions. Accurately and comprehensively predicting these patterns in tumors is an important challenge to overcome, not least given the success of immunotherapeutic drug treatment of several human cancers. This is especially challenging for subsets of closely related immune cell phenotypes with relatively small gene expression differences, which have critical functional distinctions. Here, we outline the existing and emerging novel bioinformatics strategies that can be used to profile the tumor immune landscape.

An engineered supercharged coiled-coil protein (CSP) and the cationic transfection reagent Lipofectamine 2000 are combined to form a lipoproteoplex for the purpose of dual delivery of siRNA and doxorubicin. CSP, bearing an external positive charge and axial hydrophobic pore, demonstrates the ability to condense siRNA and encapsulate the small-molecule chemotherapeutic, doxorubicin. The lipoproteoplex demonstrates improved doxorubicin loading relative to Lipofectamine 2000. Furthermore, it induces effective transfection of GAPDH (60% knockdown) in MCF-7 breast cancer cells with efficiencies comparing favorably to Lipofectamine 2000. When the lipoproteoplex is loaded with doxorubicin, the improved doxorubicin loading (∼40 μg Dox/mg CSP) results in a substantial decrease in MCF-7 cell viability.