Desmoplakin (DSP) is a large (~260 kDa) protein found in the desmosome, the subcellular structure that links the intermediate filament network of one cell to its neighbor. A mutation “hot-spot” within the NH2-terminal of the DSP protein (residues 299–515) is associated with arrhythmogenic cardiomyopathy. In a subset of DSP variants, disease is linked to calpain hypersensitivity. Previous studies show that calpain hypersensitivity can be corrected in vitro through the addition of a bulky residue neighboring the cleavage site, suggesting that physically blocking calpain accessibility is a viable strategy to restore DSP levels. Here, we aim to find drug-like molecules that also block calpain-dependent degradation of DSP. To do this, we screened ~2500 small molecules to identify compounds that specifically rescue DSP protein levels in the presence of proteases. We find that several molecules, including sodium dodecyl sulfate, palmitoylethanolamide, GW0742, salirasib, eprosarten mesylate, and GSK1838705A prevent wildtype and disease-variant-carrying DSP protein degradation in the presence of both trypsin and calpain without altering protease function. Computational screenings did not predict which molecules would protect DSP, likely due to a lack of specific DSP–drug interactions. Molecular dynamic simulations of DSP–drug complexes suggest that some long hydrophobic molecules can bind in a shallow hydrophobic groove that runs alongside the protease cleavage site. Identification of these compounds lays the groundwork for pharmacological treatment for individuals harboring these hypersensitive DSP variants.
DSP-Inspired Deep Learning: A Case Study Using Ramanujan Subspaces
Can Deep Learning be used to augment DSP techniques?
Algorithms in DSP are typically developed starting from
a mathematical model of an application. In some cases however,
simplicity of the model can result in deterioration of performance
when there is a severe modeling mis-match. This paper explores
the idea of implementing a DSP technique as a computational
graph, so that hundreds of parameters can jointly be trained to
adapt to any given dataset. Using the specific example of period
estimation by Ramanujan Subspaces, significant improvement in
estimation accuracies under high noise and very short datalengths
is demonstrated.
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- Award ID(s):
- 1712633
- PAR ID:
- 10148057
- Date Published:
- Journal Name:
- Proc. Asil. Conf. Sig., Sys., and Comp.
- Page Range / eLocation ID:
- 2072 to 2076
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Bringmann, Karl ; Grohe, Martin ; Puppis, Gabriele ; Svensson, Ola (Ed.)In the k-Disjoint Shortest Paths (k-DSP) problem, we are given a graph G (with positive edge weights) on n nodes and m edges with specified source vertices s_1, … , s_k, and target vertices t_1, … , t_k, and are tasked with determining if G contains vertex-disjoint (s_i,t_i)-shortest paths. For any constant k, it is known that k-DSP can be solved in polynomial time over undirected graphs and directed acyclic graphs (DAGs). However, the exact time complexity of k-DSP remains mysterious, with large gaps between the fastest known algorithms and best conditional lower bounds. In this paper, we obtain faster algorithms for important cases of k-DSP, and present better conditional lower bounds for k-DSP and its variants. Previous work solved 2-DSP over weighted undirected graphs in O(n⁷) time, and weighted DAGs in O(mn) time. For the main result of this paper, we present optimal linear time algorithms for solving 2-DSP on weighted undirected graphs and DAGs. Our linear time algorithms are algebraic however, and so only solve the detection rather than search version of 2-DSP (we show how to solve the search version in O(mn) time, which is faster than the previous best runtime in weighted undirected graphs, but only matches the previous best runtime for DAGs). We also obtain a faster algorithm for k-Edge Disjoint Shortest Paths (k-EDSP) in DAGs, the variant of k-DSP where one seeks edge-disjoint instead of vertex-disjoint paths between sources and their corresponding targets. Algorithms for k-EDSP on DAGs from previous work take Ω(m^k) time. We show that k-EDSP can be solved over DAGs in O(mn^{k-1}) time, matching the fastest known runtime for solving k-DSP over DAGs. Previous work established conditional lower bounds for solving k-DSP and its variants via reductions from detecting cliques in graphs. Prior work implied that k-Clique can be reduced to 2k-DSP in DAGs and undirected graphs with O((kn)²) nodes. We improve this reduction, by showing how to reduce from k-Clique to k-DSP in DAGs and undirected graphs with O((kn)²) nodes (halving the number of paths needed in the reduced instance). A variant of k-DSP is the k-Disjoint Paths (k-DP) problem, where the solution paths no longer need to be shortest paths. Previous work reduced from k-Clique to p-DP in DAGs with O(kn) nodes, for p = k + k(k-1)/2. We improve this by showing a reduction from k-Clique to p-DP, for p = k + ⌊k²/4⌋. Under the k-Clique Hypothesis from fine-grained complexity, our results establish better conditional lower bounds for k-DSP for all k ≥ 4, and better conditional lower bounds for p-DP for all p ≤ 4031. Notably, our work gives the first nontrivial conditional lower bounds 4-DP in DAGs and 4-DSP in undirected graphs and DAGs. Before our work, nontrivial conditional lower bounds were only known for k-DP and k-DSP on such graphs when k ≥ 6.more » « less
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Desmoplakin (DSP) is a large (~260 kDa) protein found in the desmosome, a subcellular complex that links the cytoskeleton of one cell to its neighbor. A mutation ‘hot-spot’ within the NH2-terminal third of the DSP protein (specifically, residues 299–515) is associated with both cardiomyopathies and skin defects. In select DSP variants, disease is linked specifically to the uncovering of a previously-occluded calpain target site (residues 447–451). Here, we partially stabilize these calpain-sensitive DSP clinical variants through the addition of a secondary single point mutation—tyrosine for leucine at amino acid position 518 (L518Y). Molecular dynamic (MD) simulations and enzymatic assays reveal that this stabilizing mutation partially blocks access to the calpain target site, resulting in restored DSP protein levels. This ‘molecular band-aid’ provides a novel way to maintain DSP protein levels, which may lead to new strategies for treating this subset of DSP-related disorders.more » « less
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Programming by example allows users to create programs without coding, by simply specifying input and output pairs.We introduce the problem of digital signal processing programming by example (DSP-PBE), where users specify input and output wave files, and a tool automatically synthesizes a program that transforms the input to the output. This program can then be applied to new wave files, giving users a new way to interact with music and program code. We formally define the problem of DSP-PBE, and provide a first implementation of a solution that can handle synthesis over commutative filters.more » « less
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null (Ed.)Here we present a combined RF hardware/DSP technique to synthesize effective channel diversity in single-antenna wireless systems. This allows digital suppression of out-of-band interference artifacts in widely tunable wireless receivers with one or more antennas, including artifacts from LO phase noise. A passive inductor-capacitor (LC) network provides gain and phase diversity between channels and across frequency. Since amplitude and phase of in-band artifacts are set by the amplitude and phase of the out-of-band interference that generates them, they can be suppressed in DSP without knowledge about the interferer itself. The feasibility of this approach is demonstrated mathematically, with numerical system simulations, and full circuit simulation.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/IEEECONF44664.2019.9048783
