Regularity of Bound States

We study regularity of bound states pertaining to embedded eigenvalues of a self-adjoint operator $H$, with respect to an auxiliary operator $A$ that is conjugate to $H$ in the sense of Mourre. We work within the framework of singular Mourre theory which enables us to deal with confined massless Pauli-Fierz models, our primary example, and many-body AC-Stark Hamiltonians. In the simpler context of regular Mourre theory our results boils down to an improvement of results obtained recently in \cite{CGH}.Comment: 70 page

The M-Superfamily of Conotoxins: A Review

Throughout the world there exist both predator and prey. This distinction is apparent though sometimes misleading. Take for example marine snails of the genus Conus that are present across the oceans of the southern hemisphere [1]. These snails are slow moving animals that appear more prey than predator. However, they have evolved into effective predators through the development of venom consisting of biologically active peptides. The venom is loaded into a hollow harpoon that the snail injects into the intended prey: fish, worms, or other snails [2]. The categories of cone snails based on prey preference are piscivorous (fish eating), molluscivorous (mollusk eating), and vermivorous (worm eating) [3]. The cone snail venom contains myriad peptide components significant to the survival of the organism with respect to hunting and defense against being eaten [4]. Interest by researchers in snails of the genus Conus began in the early nineteen seventies as evidence of their involvement in numerous human fatalities mounted [5]. Dr. Alan Kohn, an early pioneer in the study of hunter/prey relationship of cone snails, recognized that the venom of cone snails may possess therapeutic components [6]. During that time, Dr. Robert Endean and coworkers in Australia demonstrated that the venom of dissimilar species of cone snail contained a diversity of biologically active components. Dr. Baldomero (Toto) Olivera and coworkers at the University of Utah became the primary innovators of successful laboratory techniques in the study of venom components extracted from cone snails [7]. Foremost among these innovations was an avant-garde method of bio-assay using intracranial rather than intraperitoneal injection of toxin into subject mice. This new delivery method revealed greater sensitivity to individual peptides in fish and mouse studies than those from standard M-superfamily intraperitoneal injections [8]. This early research revealed the disulfide rich nature of the majority of peptide components from Conus snail venom. The disulfide rich peptides became broadly defined as conotoxins [9]

Dockomatic: An Emerging Resource to Manage Molecular Docking

The application of computational modeling to rationally design drugs and characterize macro-biomolecular receptors has proven increasingly useful due to the accessibility of computing clusters and clouds. AutoDock is a well-known and powerful software program used to model ligand to receptor binding interactions. A limitation of AutoDock is the inability of a user to automatically create ligands and manage the input and output of data when dealing with large numbers of simulations; a problem that arises in High Throughput Virtual Screening (HTVS) or Inverse Virtual Screening (IVS). We have designed DockoMatic, a user friendly Graphical User Interface (GUI) application that constructs peptide-based ligands, integrates with the software program TreePack to create user defined peptide analogs, and automates the creation and management of AutoDock jobs for HTVS of ligand to receptor interactions. DockoMatic is a valuable tool for studying complex systems such as conotoxins, from the genus Conus, and their interactions with the well-characterized molecular receptor, Aplysia californica acetylcholine binding protein (Ac-AChBP)

Minor Fibrillar Collagens, Variable Regions Alternative Splicing, Intrinsic Disorder, and Tyrosine Sulfation

Minor fibrillar collagen types V and XI, are those less abundant than the fibrillar collagens types I, II and III. The alpha chains share a high degree of similarity with respect to protein sequence in all domains except the variable region. Genomic variation and, in some cases, extensive alternative splicing contribute to the unique sequence characteristics of the variable region. While unique expression patterns in tissues exist, the functions and biological relevance of the variable regions have not been elucidated. In this review, we summarize the existing knowledge about expression patterns and biological functions of the collagen types V and XI alpha chains. Analysis of biochemical similarities among the peptides encoded by each exon of the variable region suggest the potential for shared function. The alternative splicing, conservation of biochemical characteristics in light of low sequence conservation, and evidence for intrinsic disorder, suggests modulation of binding events between the surface of collagen fibrils and surrounding extracellular molecules as a shared function

DockoMatic - Automated Ligand Creation and Docking

Background: The application of computational modeling to rationally design drugs and characterize macro biomolecular receptors has proven increasingly useful due to the accessibility of computing clusters and clouds. AutoDock is a well-known and powerful software program used to model ligand to receptor binding interactions. In its current version, AutoDock requires significant amounts of user time to setup and run jobs, and collect results. This paper presents DockoMatic, a user friendly Graphical User Interface (GUI) application that eases and automates the creation and management of AutoDock jobs for high throughput screening of ligand to receptor interactions. Results: DockoMatic allows the user to invoke and manage AutoDock jobs on a single computer or cluster, including jobs for evaluating secondary ligand interactions. It also automates the process of collecting, summarizing, and viewing results. In addition, DockoMatic automates creation of peptide ligand .pdb files from strings of single-letter amino acid abbreviations. Conclusions: DockoMatic significantly reduces the complexity of managing multiple AutoDock jobs by facilitating ligand and AutoDock job creation and management

Harnessing Nature’s Diversity: Discovering organophosphate bioscavenger characteristics among low molecular weight proteins

Organophosphate poisoning can occur from exposure to agricultural pesticides or chemical weapons. This exposure inhibits acetylcholinesterase resulting in increased acetylcholine levels within the synaptic cleft causing loss of muscle control, seizures, and death. Mitigating the effects of organophosphates in our bodies is critical and yet an unsolved challenge. Here, we present a computational strategy that integrates structure mining and modeling approaches, using which we identify novel candidates capable of interacting with a serine hydrolase probe (with equilibrium binding constants ranging from 4 to 120 μM). One candidate Smu. 1393c catalyzes the hydrolysis of the organophosphate omethoate (kcat/Km of (2.0 ± 1.3) × 10−1 M−1s−1) and paraoxon (kcat/Km of (4.6 ± 0.8) × 103 M−1s−1), V- and G-agent analogs respectively. In addition, Smu. 1393c protects acetylcholinesterase activity from being inhibited by two organophosphate simulants. We demonstrate that the utilized approach is an efficient and highly-extendable framework for the development of prophylactic therapeutics against organophosphate poisoning and other important targets. Our findings further suggest currently unknown molecular evolutionary rules governing natural diversity of the protein universe, which make it capable of recognizing previously unseen ligands

Oncostatin M Binds to Extracellular Matrix in a Bioactive Conformation: Implications for Inflammation and Metastasis

Oncostatin M (OSM) is an interleukin-6-like inflammatory cytokine reported to play a role in a number of pathological processes including cancer. Full-length OSM is expressed as a 26 kDa protein that can be proteolytically processed into 24 kDa and 22 kDa forms via removal of C-terminal peptides. In this study, we examined both the ability of OSM to bind to the extracellular matrix (ECM) and the activity of immobilized OSM on human breast carcinoma cells. OSM was observed to bind to ECM proteins collagen types I and XI, laminin, and fibronectin in a pH-dependent fashion, suggesting a role for electrostatic bonds that involves charged amino acids of both the ECM and OSM. The C-terminal extensions of 24 kDa and 26 kDa OSM, which contains six and thirteen basic amino acids, respectively, enhanced electrostatic binding to ECM at pH 6.5–7.5 when compared to 22 kDa OSM. The highest levels of OSM binding to ECM, though, were observed at acidic pH 5.5, where all forms of OSM bound to ECM proteins to a similar extent. This indicates additional electrostatic binding properties independent of the OSM C-terminal extensions. The reducing agent dithiothreitol also inhibited the binding of OSM to ECM suggesting a role for disulfide bonds in OSM immobilization. OSM immobilized to ECM was protected from cleavage by tumor-associated proteases and maintained activity following incubation at acidic pH for extended periods of time. Importantly, immobilized OSM remained biologically active and was able to induce and sustain the phosphorylation of STAT3 in T47D and ZR-75-1 human breast cancer cells over prolonged periods, as well as increase levels of STAT1 and STAT3 protein expression. Immobilized OSM also induced epithelial–mesenchymal transition-associated morphological changes in T47D cells. Taken together, these data indicate that OSM binds to ECM in a bioactive state that may have important implications for the development of chronic inflammation and tumor metastasis

Fortilin potentiates the peroxidase activity of Peroxiredoxin-1 and protects against alcohol-induced liver damage in mice

Fortilin, a pro-survival molecule, inhibits p53-induced apoptosis by binding to the sequence-specific DNA-binding domain of the tumor suppressor protein and preventing it from transcriptionally activating Bax. Intriguingly, fortilin protects cells against ROS-induced cell death, independent of p53. The signaling pathway through which fortilin protects cells against ROS-induced cell death, however, is unknown. Here we report that fortilin physically interacts with the antioxidant enzyme peroxiredoxin-1 (PRX1), protects it from proteasome-mediated degradation, and keeps it enzymatically active by blocking its deactivating phosphorylation by Mst1, a serine/threonine kinase. At the whole animal level, the liver-specific overexpression of fortilin reduced PRX1 phosphorylation in the liver, enhanced PRX1 activity, and protected the transgenic animals against alcohol-induced, ROS-mediated, liver damage. These data suggest the presence of a novel oxidative-stress-handling pathway where the anti-p53 molecule fortilin augments the peroxidase PRX1 by protecting it against degradation and inactivation of the enzyme. Fortilin-PRX1 interaction in the liver could be clinically exploited further to prevent acute alcohol-induced liver damage in humans

Search algorithms as a framework for the optimization of drug combinations

Combination therapies are often needed for effective clinical outcomes in the management of complex diseases, but presently they are generally based on empirical clinical experience. Here we suggest a novel application of search algorithms, originally developed for digital communication, modified to optimize combinations of therapeutic interventions. In biological experiments measuring the restoration of the decline with age in heart function and exercise capacity in Drosophila melanogaster, we found that search algorithms correctly identified optimal combinations of four drugs with only one third of the tests performed in a fully factorial search. In experiments identifying combinations of three doses of up to six drugs for selective killing of human cancer cells, search algorithms resulted in a highly significant enrichment of selective combinations compared with random searches. In simulations using a network model of cell death, we found that the search algorithms identified the optimal combinations of 6-9 interventions in 80-90% of tests, compared with 15-30% for an equivalent random search. These findings suggest that modified search algorithms from information theory have the potential to enhance the discovery of novel therapeutic drug combinations. This report also helps to frame a biomedical problem that will benefit from an interdisciplinary effort and suggests a general strategy for its solution.Comment: 36 pages, 10 figures, revised versio