Jan 27, 2007

2007 week 05: Articles in Proteins


Getting one's protein in a bunch -- When quality control fails in cells
Over time, a relatively minor mistake in protein production at the cellular level may lead to serious neurological diseases. But exactly how the cell avoids such mistakes has remained unclear until now. Researchers at Ohio State University found the mechanism that prevents such errors, and explain their findings in the Proceedings of the National Academy of Sciences.

Quantum biology -- Powerful computer models reveal key biological mechanism
Troy, N.Y. -- Using powerful computers to model the intricate dance of atoms and molecules, researchers at Rensselaer Polytechnic Institute have revealed the mechanism behind an important biological reaction. In collaboration with scientists from the Wadsworth Center of the New York State Department of Health, the team is working to harness the reaction to develop a "nanoswitch" for a variety of applications, from targeted drug delivery to genomics and proteomics to sensors.
The research is part of a burgeoning discipline called "quantum biology," which taps the skyrocketing power of today's high-performance computers to precisely model complex biological processes. The secret is quantum mechanics -- the much-touted theory from physics that explains the inherent "weirdness" of the atomic realm.

Microtubule protein interactions visualized en masse
In a new study published online in the open access journal PLoS Biology, Philipp Niethammer, Eric Karsenti, and colleagues investigate the regulation of microtubule dynamics via application of their new method, called visual immunoprecipitation (VIP), which enables simultaneous visualization of multiple protein interactions in cell extracts.

Assignment of polar states for protein amino acid residues using a interaction cluster decomposition algorithm and its application to high resolution protein structure modeling
We have developed a new method (Independent Cluster Decomposition Algorithm, ICDA) for creating all-atom models of proteins given the heavy-atom coordinates, provided by X-ray crystallography, and the pH. In our method the ionization states of titratable residues, the crystallographic mis-assignment of amide orientations in Asn/Gln, and the orientations of OH/SH groups are addressed under the unified framework of polar states assignment. To address the large number of combinatorial possibilities for the polar hydrogen states of the protein, we have devised a novel algorithm to decompose the system into independent interacting clusters, based on the observation of the crucial interdependence between the short range hydrogen bonding network and polar residue states, thus significantly reducing the computational complexity of the problem and making our algorithm tractable using relatively modest computational resources. We utilize an all atom protein force field (OPLS) and a Generalized Born continuum solvation model, in contrast to the various empirical force fields adopted in most previous studies. We have compared our prediction results with a few well-documented methods in the literature (WHATIF, REDUCE). In addition, as a preliminary attempt to couple our polar state assignment method with real structure predictions, we further validate our method using single side chain prediction, which has been demonstrated to be an effective way of validating structure prediction methods without incurring sampling problems. Comparisons of single side chain prediction results after the application of our polar state prediction method with previous results with default polar state assignments indicate a significant improvement in the single side chain predictions for polar residues. Proteins 2007. © 2006 Wiley-Liss, Inc.

Understanding the regulation mechanisms of PAF receptor by agonists and antagonists: Molecular modeling and molecular dynamics simulation studies
Platelet-activating factor receptor (PAFR) is a member of G-protein coupled receptor (GPCR) superfamily. Understanding the regulation mechanisms of PAFR by its agonists and antagonists at the atomic level is essential for designing PAFR antagonists as drug candidates for treating PAF-mediated diseases. In this study, a 3D model of PAFR was constructed by a hierarchical approach integrating homology modeling, molecular docking and molecular dynamics (MD) simulations. Based on the 3D model, regulation mechanisms of PAFR by agonists and antagonists were investigated via three 8-ns MD simulations on the systems of apo-PAFR, PAFR-PAF and PAFR-GB. The simulations revealed that binding of PAF to PAFR triggers the straightening process of the kinked helix VI, leading to its activated state. In contrast, binding of GB to PAFR locks PAFR in its inactive state. Proteins 2007. © 2007 Wiley-Liss, Inc.

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2007 week 05: Articles of Related Interest


Chopping Off Protein Puts Immune Cells Into High Gear
The complex task of launching a well-organized, effective immune system attack on specific targets is thrown into high gear when either of two specific enzymes chop a protein called LAG-3 off the immune cells leading that battle, according to investigators at St. Jude Children's Research Hospital.

Role For Proteomics In Identifying Hematologic Malignancies
Scientists have identified a set of biomarkers that could help clinicians identify a group of hematologic malignancies known as myelodysplastic syndromes (MDS), which affect approximately 300,000 individuals worldwide and often progress to acute myeloid leukemia.

Motor protein plays key role in connecting neurons
A motor protein called myosin X runs the main road of a developing neuron, delivering to its tip a receptor that enables it to communicate with other neurons, scientists say. In another piece of the puzzle of how neurons form connections, researchers have found myosin X travels a portion of a neuron's backbone called the actin filament, a sort of two-way highway in the cell's highest traffic area, says Dr. Wen-Cheng Xiong, developmental neurobiologist at the Medical College of Georgia.

'Quiet Revolution' May Herald New RNA Therapeutics
Scientists at the University of Oxford have identified a surprising way of switching off a gene involved in cell division. The mechanism involves a form of RNA, a chemical found in cell nuclei, whose role was previously unknown, and could have implications for preventing the growth of tumour cells.
RNA plays an important and direct role in the synthesis of proteins, the building blocks of our bodies. However, scientists have known for some time that not all types of RNA are directly involved in protein synthesis. Now, in research funded by the Wellcome Trust and the Medical Research Council, a team of scientists has shown that one particular type of RNA plays a key role in regulating the gene implicated in control of tumour growth. The research is published online today in Nature.

Chemical Switch Triggers Critical Cell Activities
The freeze-frame image of a molecular relay race, in which one enzyme passes off a protein like a baton to another enzyme, has solved a key mystery to how cells control some vital functions, according to investigators at St. Jude Children's Research Hospital. A report on this work appears in the January 14 advanced online publication issue of Nature.

Buckyballs used as 'passkey' into cancer cells
Rice University chemists and Baylor College of Medicine pediatric scientists have discovered how to use buckyballs as passkeys that allows drugs to enter cancer cells. Research in the January 21 issue of the journal Organic and Biomolecular Chemistry, describes how the researchers mimicked the techniques used by some viruses to introduce non-toxic bits of buckyball-containing protein into both neuroblastoma and liver cancer cells.

Filamins Tether Cystic Fibrosis Protein To Cell Surface
Cystic fibrosis (CF) is caused by mutations in a gene that encodes a protein known as CFTR. More than 1000 different disease-causing mutations in CFTR have been identified, and although the overall effect of each mutation is to decrease CFTR expression at the cell surface, it is not known for every one of these mutations what the molecular defect is that causes the decreased cell surface expression of CFTR.
From the article itself: "Our data demonstrate what we believe to be a previously unrecognized role for the CFTR N terminus in the regulation of the plasma membrane stability and metabolic stability of CFTR. In addition, we elucidate the molecular defect associated with the S13F mutation."

Breakthrough Could Prevent Multiple Fibrotic Diseases: Tests Find Protein Stops Fibrosis In Lung, Heart, Other Tissues Science Daily
A scientific breakthrough at Rice University could lead to the first treatment that prevents the build-up of deadly scar tissue in a broad class of diseases that account for an estimated 45 percent of U.S. deaths each year.
"Fibrotic diseases kill so many people because they can crop up in almost any part of the body, and cardiac fibrosis is a particular problem for anyone who's had a heart attack," said Richard Gomer, professor of biochemistry and cell biology at Rice. "We've discovered a naturally occurring blood protein that prevents dangerous scar tissue from forming."

Brown team finds crucial protein role in deadly prion spread
Brown University biologists have made another major advance toward understanding the deadly work of prions, the culprits behind fatal brain diseases such as mad cow and their human counterparts. In new work published online in PLoS Biology, researchers show that the protein Hsp104 must be present and active for prions to multiply and cause disease.

Scripps Research study reveals new function of protein kinase pathway in tumor suppression
Scientists at the Scripps Research Institute have discovered a surprising new function of a well-known signaling pathway that, when activated, can inhibit tumor development. This finding may lead to the development of drugs that can serve as an effective cancer therapy by artificially activating this pathway in cancer cells.

Disabling key protein may give physicians time to treat pneumonic plague
The deadly attack of the bacterium that causes pneumonic plague is significantly slowed when it can't make use of a key protein, scientists at Washington University School of Medicine in St. Louis report in this week's issue of Science.

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2007 week 05: Articles in Maths


Statistical Method Used Influences Results Of Observational Studies
A study comparing different statistical methods used to remove the effects of selection bias in observational studies finds that results may vary and caution may be warranted when interpreting findings of studies using certain methods, according to an article in the January 17 issue of JAMA.
"Randomized clinical trials cannot be undertaken in all situations in which evidence is needed to guide care. Well-designed observational studies are still needed to assess population effectiveness and to extend results to a general population setting. Our study serves as a cautionary note regarding their analysis and interpretation. First, propensity scores and propensity-based matching have the same limitations as multivariable risk adjustment model methods, and are no more likely to remove bias due to unmeasured confounding when strong selection bias exists. Second, instrumental variable analyses may remove both overt and hidden biases but are more suited to answer policy questions than to provide insight into a specific clinical question for a specific patient. Caution is advised regarding clinical protocols and policy statements for invasive care based on expected mortality benefits derived from traditional multivariable modeling and propensity score risk adjustment of observational studies," the researchers conclude.
Note: This story has been adapted from a news release issued by JAMA and Archives Journals.

Microlocal Analysis
In mathematical analysis, microlocal analysis is a term use to describe techniques developed from the 1950s onwards based on Fourier transforms related to the study of variable-coefficients-linear and nonlinear partial differential equations. This includes generalized functions, pseudo-differential operators, wave front sets, Fourier integral operators, and paradifferential operators.
The term microlocal implies localisation not just at a point, but in terms of cotangent space directions at a given point. This gains in importance on manifolds of dimension greater than one.
This entry was adapted from the Wikipedia article Microlocal analysis as of January 17, 2007.

The articles below contains text in the LaTex format. To view the article correctly, please visit the source link.

Fuzzy Subset
Fuzzy set theory is based on the idea that vague notions as "big", "near", "hold" can be modelled by "fuzzy subsets". A fuzzy subset of a set S is a map ... from S into the interval ... . More precisely, the interval ... is considered as a complete lattic ...

Eventual Property
Let be a set and a property on the elements of . Let be a net ( a directed set) in (that is, ). As each , either has or does not have property . We say that the net has property above if has property for all . Furthermore, we say that eventually has property if it has property above some .

Partial Ordering In A Topological Space
Let X be a T0 space. For any ... , we define a binary relation le as follows: ... Proposition . The binary relation just defined is a partial order. ... Clearly ... . Suppose next that ... and ... . If ... , then there is an open set A such that ... and . ...

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Jan 13, 2007

2007 week 03: Articles in Proteins


Spanish Scientists Reveal Dynamic Map Of Proteins, Possibilities For New Drugs

Scientists from the Institute for Research in Biomedicine (IRB Barcelona), the Life Sciences Programme at the Barcelona Supercomputing Center (BSC) and the National Institute for Bioinformatics (INB) have published a provisional "atlas" of the dynamic behaviour of proteins in the prestigious scientific journal, Proceedings of the National Academy of Sciences USA.

Proteins determine the shape and structure of cells and drive nearly all of a cell's vital processes. All proteins carry out their functions according to the same process -- by binding with other molecules. Now, the scientists have compiled a map that shows them how proteins can move and form complexes, a valuable tool that will help them understand the basic functions of the molecules, but also what happens when they function incorrectly. Such a map opens vast possibilities for the design of new drugs.

The goal of this study is to define a map of the dynamic properties of a very representative group of proteins. This involves taking stock of the basic rules that govern the flexibility of proteins and allows scientists to predict the structures that these proteins can form based on the presence of ligands or modifications. This allows scientists to go beyond the traditional simple static vision of proteins, which has not been able to capture the subtle conformational changes necessary for proteins to function. These changes modify, for example, how proteins bind to metabolites or drugs.
This is the first study of a larger scientific project, called MoDel (Molecular Dynamics Extended Library), the scope of which is even more ambitious. "MoDel aims to establish a 'fourth dimension' for protein structures thereby providing a complete landscape of possible conformations for the entire proteome (the complete network of protein interactions in a cell), over time. In the near future, a biochemist will be able to understand the behaviour of a protein, or design a drug that can interact with that protein, drawing on not only the knowledge of a single structure, but of an entire repertory spontaneously occurring in physiological conditions," says project director Modesto Orozco, principal investigator of the Molecular Modelling and Bioinformatics group at IRB Barcelona, director of the Department of Life Sciences of the BSC, and Professor in the Department of Biochemistry at the University of Barcelona.
Source article: M.Rueda, C.Ferrer, T.Meyer, A.Pérez, J.Camps, A.Hospital, J.L.Gelpí and M.Orozco. "A consensus view of protein dynamics". Proc. Natl. Acad. Sci. USA. (2007) 104, 796-801

Prediction of side-chain conformations on protein surfaces
An approach is described that improves the prediction of the conformations of surface side chains in crystal structures, given the main-chain conformation of a protein. A key element of the methodology involves the use of the colony energy. This phenomenological term favors conformations found in frequently sampled regions, thereby approximating entropic effects and serving to smooth the potential energy surface. Use of the colony energy significantly improves prediction accuracy for surface side chains with little additional computational cost. Prediction accuracy was quantified as the percentage of side-chain dihedral angles predicted to be within 40° of the angles measured by X-ray diffraction. Use of the colony energy in predictions for single side chains improved the prediction accuracy for [chi]1 and [chi]1+2 from 65 and 40% to 74 and 59%, respectively. Several other factors that affect prediction of surface side-chain conformations were also analyzed, including the extent of conformational sampling, details of the rotamer library employed, and accounting for the crystallographic environment. The prediction of conformations for polar residues on the surface was generally found to be more difficult than those for hydrophobic residues, except for polar residues participating in hydrogen bonds with other protein groups. For surface residues with hydrogen-bonded side chains, the prediction accuracy of [chi]1 and [chi]1+2 was 79 and 63%, respectively. For surface polar residues, in general (all side-chain prediction), the accuracy of [chi]1 and [chi]1+2 was only 73 and 56%, respectively. The most accurate results were obtained using the colony energy and an all-atom description that includes neighboring molecules in the crystal (protein chains and hetero atoms). Here, the accuracy of [chi]1 and [chi]1+2 predictions for surface side chains was 82 and 73%, respectively. The root mean square deviations obtained for hydrogen-bonding surface side chains were 1.64 and 1.81 Å, with and without consideration of crystal packing effects, respectively. Proteins 2007. © 2007 Wiley-Liss, Inc.

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2007 week 03: Articles in Maths


Interaction geometry involving planar groups in protein-protein interfaces
The geometry of interactions of planar residues is nonrandom in protein tertiary structures and gives rise to conventional, as well as nonconventional (XH···, XH···O, where X = C, N, or O) hydrogen bonds. Whether a similar geometry is maintained when the interaction is across the protein-protein interface is addressed here. The relative geometries of interactions involving planar residues, and the percentage of contacts giving rise to different types of hydrogen bonds are quite similar in protein structures and the biological interfaces formed by protein chains in homodimers and protein-protein heterocomplexes - thus pointing to the similarity of chemical interactions that occurs during protein folding and binding. However, the percentage is considerably smaller in the nonspecific and nonphysiological interfaces that are formed in crystal lattices of monomeric proteins. The CH···O interaction linking the aromatic and the peptide groups is quite common in protein structures as well as the three types of interfaces. However, as the interfaces formed by crystal contacts are depleted in aromatic residues, the weaker hydrogen bond interactions would contribute less toward their stability. Proteins 2007; © 2007 Wiley-Liss, Inc.

Science's breakthrough of the year -- The Poincaré Theorem

Science honors the top 10 research advances of 2006
In 2006, researchers closed a major chapter in mathematics, reaching a consensus that the elusive Poincaré Conjecture, which deals with abstract shapes in three-dimensional space, had finally been solved. Science and its publisher AAAS, the nonprofit society, now salute this development as the Breakthrough of the Year and also give props to nine other of the year’s most significant scientific accomplishments.
The Poincaré Conjecture is part of a branch of mathematics called topology, informally known as "rubber sheet geometry" because it involves surfaces that can undergo arbitrary amounts of stretching. The conjecture, proposed in 1904 by Henri Poincaré, describes a test for showing that a space is equivalent to a "hypersphere," the three-dimensional surface of a four-dimensional ball.

Partial least squares: a versatile tool for the analysis of high-dimensional genomic data
Partial least squares (PLS) is an efficient statistical regression technique that is highly suited for the analysis of genomic and proteomic data. In this article, we review both the theory underlying PLS as well as a host of bioinformatics applications of PLS. In particular, we provide a systematic comparison of the PLS approaches currently employed, and discuss analysis problems as diverse as, e.g. tumor classification from transcriptome data, identification of relevant genes, survival analysis and modeling of gene networks and transcription factor activities.

Multivariate Distribution Function

Multivariate distribution functions are typically found in probability theory, and especially in statistics. An example of a commonly used multivariate distribution function is the multivariate Gaussian distribution function.
The attempt here is to study a class of functions that can be used as models for distributions of distances between points in a “probabilistic metric space”.

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2007 week 03: Articles of Related Interest


Finding Patterns Of Importance In A Deluge Of Data
Science Daily — Dartmouth engineers George Cybenko and Vincent Berk think that PQS, or process query systems, are the way to go to make sense of the huge volume of data we collect each day... The duo present their case in a paper published in this month's IEEE Computer, the flagship magazine of the Institute of Electrical and Electronics Engineers' Computer Society.
According to Cybenko, "PQS can do for discrete, categorical data analysis problems what classical times series analysis did for finance and control systems where the data are numerical."

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Jan 10, 2007

2007 week 03: Articles in Folding


Modelling of the ABL and ARG proteins predicts two functionally critical regions that are natively unfolded
The ABL and ARG tyrosine kinases regulate many pivotal cellular processes and are implicated in the pathogenesis of several forms of leukemia. We have modelled the previously uncharacterized core domain (SH3-SH2-tyrosine kinase) and C-terminal actin-binding domain of ARG. We have also investigated the structural arrangement of the ABL and ARG Cap region and of the long multifunctional region located downstream of the tyrosine kinase domain. We report that the ARG core domain is homologous to the corresponding ABL region, therefore suggesting that ARG catalytic activity is likely regulated by the same SH3-SH2 clamp described for ABL. We also report that the Cap of both ABL and ARG is natively unfolded. Hence, biological events determining the folding of the Cap are critical to allow its interaction with the tyrosine kinase C-lobe. Furthermore, our results show that, with the exception of the C-terminal actin-binding domain, the entire region encoded by the ABL and ARG last exon is natively unfolded. Phosphorylation events or protein-protein interactions regulating the folding of this region will therefore modulate the activity of its numerous functional domains. Finally, our analyses show that the C-terminal actin-binding domain of ARG displays a four-helix bundle structure similar to the one reported for the corresponding ABL region. Our findings imply that many biological activities attributed to ABL, ARG, and their oncogenic counterparts are regulated by natively unfolded regions. Proteins 2007. © 2007 Wiley-Liss, Inc.

Secondary structure length as a determinant of folding rate of proteins with two- and three-state kinetics
We present a simple method for determining the folding rates of two- and three-state proteins from the number of residues in their secondary structures (secondary structure length). The method is based on the hypothesis that two- and three-state foldings share a common pattern. Three-state proteins first condense into metastable intermediates, subsequent forming of [alpha]-helices, turns, and [beta]-sheets at slow rate-limiting step. The folding rate of such proteins anticorrelate with the length of these [beta]-secondary structures. It is also assumed that in two-state folding, rapidly folded [alpha]-helices and turns may facilitate formation of fleeting unobservable "intermediates" and thus show two-state behavior. There is an inverse relationship between the folding rate and the length of [beta]-sheets and loops. Our study achieves 94.0 and 88.1% correlations with folding rates determined experimentally for 21 three- and 38 two-state proteins, respectively, suggesting that protein-folding rates are determined by the secondary structure length. The kinetic kinds are selected on the basis of a competitive formation of hydrophobic collapse and [alpha]-structure in early intermediates. Proteins 2007. © 2007 Wiley-Liss, Inc.

Contact patterns between helices and strands of sheet define protein folding patterns
Comparing and classifying protein folding patterns allows organizing the known structures and enumerating possible protein structural patterns including those not yet observed. We capture the essence of protein folding patterns in a concise tableau representation based on the order and contact patterns of secondary structures: helices and strands of sheet. The tableaux are intelligible to both humans and computers. They provide a database, derived from the Protein Data Bank, mineable in studies of protein architecture. Using this database, we have: (i) determined statistical properties of secondary structure contacts in an unbiased set of protein domains from ASTRAL, (ii) observed that in 98% of cases, the tableau is a faithful representation of the folding pattern as classified in SCOP, (iii) demonstrated that to a large extent the local structure of proteins indicates their complete folding topology, and (iv) studied the use of the representation for fold identification. Proteins 2007. © 2007 Wiley-Liss, Inc.

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Jan 8, 2007

An Intro to Proteins & Biochemistry

A list of free online books with their relevant chapters of interest.
*direct links to the individual chapters where necessary will be added as time permits*


1.3. Chemical Bonds in Biochemistry

Protein Structure and Function
  • 3.1. Proteins Are Built from a Repertoire of 20 Amino Acids
  • 3.2. Primary Structure: Amino Acids Are Linked by Peptide Bonds to Form Polypeptide Chains
  • 3.3. Secondary Structure: Polypeptide Chains Can Fold Into Regular Structures Such as the Alpha Helix, the Beta Sheet, and Turns and Loops
  • 3.4. Tertiary Structure: Water-Soluble Proteins Fold Into Compact Structures with Nonpolar Cores
  • 3.5. Quaternary Structure: Polypeptide Chains Can Assemble Into Multisubunit Structures
  • 3.6. The Amino Acid Sequence of a Protein Determines Its Three-Dimensional Structure

Exploring Proteins
  • 4.1. The Purification of Proteins Is an Essential First Step in Understanding Their Function
  • 4.2. Amino Acid Sequences Can Be Determined by Automated Edman Degradation
  • 4.3. Immunology Provides Important Techniques with Which to Investigate Proteins
  • 4.4. Peptides Can Be Synthesized by Automated Solid-Phase Methods
  • 4.5. Three-Dimensional Protein Structure Can Be Determined by NMR Spectroscopy and X-Ray Crystallography

DNA, RNA, and the Flow of Genetic Information
  • 5.1. A Nucleic Acid Consists of Four Kinds of Bases Linked to a Sugar-Phosphate Backbone
  • 5.2. A Pair of Nucleic Acid Chains with Complementary Sequences Can Form a Double-Helical Structure
  • 5.3. DNA Is Replicated by Polymerases that Take Instructions from Templates
  • 5.4. Gene Expression Is the Transformation of DNA Information Into Functional Molecules
  • 5.5. Amino Acids Are Encoded by Groups of Three Bases Starting from a Fixed Point
  • 5.6. Most Eukaryotic Genes Are Mosaics of Introns and Exons

7.3. Examination of Three-Dimensional Structure Enhances Our Understanding of Evolutionary Relationships

12. Lipids and Cell Membranes
  • 12.1. Many Common Features Underlie the Diversity of Biological Membranes
  • 12.2. Fatty Acids Are Key Constituents of Lipids
  • 12.3. There Are Three Common Types of Membrane Lipids
  • 12.4. Phospholipids and Glycolipids Readily Form Bimolecular Sheets in Aqueous Media
  • 12.5. Proteins Carry Out Most Membrane Processes

23. Protein Turnover and Amino Acid Catabolism
  • 23.1. Proteins Are Degraded to Amino Acids
  • 23.2. Protein Turnover Is Tightly Regulated

28. RNA Synthesis and Splicing
  • 28.1. Transcription Is Catalyzed by RNA Polymerase
  • 28.2. Eukaryotic Transcription and Translation Are Separated in Space and Time
  • 28.3. The Transcription Products of All Three Eukaryotic Polymerases Are Processed
  • 28.4. The Discovery of Catalytic RNA Was Revealing in Regard to Both Mechanism and Evolution

29. Protein Synthesis
  • 29.1. Protein Synthesis Requires the Translation of Nucleotide Sequences Into Amino Acid Sequences
  • 29.2. Aminoacyl-Transfer RNA Synthetases Read the Genetic Code
  • 29.3. A Ribosome Is a Ribonucleoprotein Particle (70S) Made of a Small (30S) and a Large (50S) Subunit
  • 29.4. Protein Factors Play Key Roles in Protein Synthesis
  • 29.5. Eukaryotic Protein Synthesis Differs from Prokaryotic Protein Synthesis Primarily in Translation Initiation


Entry into the Endoplasmic Reticulum: Protein Translocation, Folding and Quality Control
Protein Translocation Across the ER Membrane
Quality Control in the ER
The Unfolded Protein Response (UPR)
ER and Human Health
Protein Misassembly: Macromolecular Crowding and Molecular Chaperones
Inside the Cell
The Principle of Protein Self-Assembly: Yesterday and Today
The Molecular Chaperone Concept
The Problem of Protein Misassembly
Macromolecular Crowding
Stimulation of Misassembly by Crowding Agents
How do Chaperones Combat Misassembly?
The Molecular Chaperone Function


I. Introduction to the Cell: 3. Proteins
  • The Shape and Structure of Proteins
  • Protein Function

II. Basic Genetic Mechanisms 6. How Cells Read the Genome: From DNA to Protein
  • From DNA to RNA
  • From RNA to Protein
  • The RNA World and the Origins of Life


3. Protein Structure and Function
  • 3.1. Hierarchical Structure of Proteins
  • 3.2. Folding, Modification, and Degradation of Proteins
  • 3.3. Functional Design of Proteins
  • 3.4. Membrane Proteins
  • 3.5. Purifying, Detecting, and Characterizing Proteins

3D, rotating samples of some proteins.
-Display options "backbone" and "strand" are a very nice feature.

Moviesof some folding proteins.
-Quicktime Required

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Jan 3, 2007

2007 week 01: Articles in Veterinary Science


Isolation of ferret protein promising for cancer, reproductive studies
Although the focus of the study was about pregnancy, there was this interesting general finding.
The protein -- glucose-6-phosphate isomerase (GPI) -- already is widely known as a highly conserved enzyme occurring in intracellular metabolism, converting sugars in glycolysis in many organisms and humans. "In the domestic ferrets that we studied, we found a unique role for this enzyme as a secreted protein that is essential in the reproductive process," Bahr said. "Interestingly, he same ability to secrete this protein is found in many types of metastatic tumors, suggesting that tumor cells have co-opted this process. The secretion of GPI allows the tumors to find and lock onto receptors to invade healthy tissues." The ability of tumors to spread is similar to the invasive process of implantation.

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2007 week 01: Articles in Proteins


Locating missing water molecules in protein cavities by the three-dimensional reference interaction site model theory of molecular solvation

Water molecules confined in protein cavities are of great importance in understanding the protein structure and functions. However, it is a nontrivial task to locate such water molecules in protein by the ordinary molecular simulation and modeling techniques as well as experimental methods. The present study proves that the three-dimensional reference interaction site model (3D-RISM) theory, a recently developed statistical-mechanical theory of molecular solvation, has an outstanding advantage in locating such water molecules. In this paper, we demonstrate that the 3D-RISM theory is able to reproduce the structure and the number of water molecules in cavities of hen egg-white lysozyme observed commonly in the X-ray structures of different resolutions and conditions. Furthermore, we show that the theory successfully identified a water molecule in a cavity, the existence of which has been ambiguous even from the X-ray results. In contrast, we confirmed that molecular dynamics simulation is helpless at present to find such water molecules because the results substantially depend on the initial coordinates of water molecules. Possible applications of the theory to problems in the fields of biochemistry and biophysics are also discussed. Proteins 2007. © 2006 Wiley-Liss, Inc.

Protein-RNA interactions: Structural analysis and functional classes

A data set of 89 protein-RNA complexes has been extracted from the Protein Data Bank, and the nucleic acid recognition sites characterized through direct contacts, accessible surface area, and secondary structure motifs.
However, the analysis of hydrogen bond and van der Waal contacts showed that in general proteins complexed with messenger RNA, transfer RNA and viral RNA have more base specific contacts and less backbone contacts than expected, while proteins complexed with ribosomal RNA have less base-specific contacts than the expected. Hence, whilst the types of amino acids involved in the interfaces are similar, the distribution of specific contacts is dependent upon the functional class of the RNA bound. Proteins 2007. © 2006 Wiley-Liss, Inc.

valuating protein structures determined by structural genomics consortia

Structural genomics projects are providing large quantities of new 3D structural data for proteins. To monitor the quality of these data, we have developed the protein structure validation software suite (PSVS), for assessment of protein structures generated by NMR or X-ray crystallographic methods. PSVS is broadly applicable for structure quality assessment in structural biology projects.
PSVS is particularly useful in assessing protein structures determined by NMR methods, but is also valuable for assessing X-ray crystal structures or homology models. Using these tools, we assessed protein structures generated by the Northeast Structural Genomics Consortium and other international structural genomics projects, over a 5-year period. Protein structures produced from structural genomics projects exhibit quality score distributions similar to those of structures produced in traditional structural biology projects during the same time period. However, while some NMR structures have structure quality scores similar to those seen in higher-resolution X-ray crystal structures, the majority of NMR structures have lower scores. Potential reasons for this "structure quality score gap" between NMR and X-ray crystal structures are discussed. Proteins 2007. © 2006 Wiley-Liss, Inc.

Achieving 80% ten-fold cross-validated accuracy for secondary structure prediction by large-scale training

An integrated system of neural networks, called SPINE, is established and optimized for predicting structural properties of proteins. SPINE is applied to three-state secondary-structure and residue-solvent-accessibility (RSA) prediction in this paper. The integrated neural networks are carefully trained with a large dataset of 2640 chains, sequence profiles generated from multiple sequence alignment, representative amino acid properties, a slow learning rate, overfitting protection, and an optimized sliding-widow size. Proteins 2007. © 2006 Wiley-Liss, Inc.

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Jan 2, 2007

2007 week 01: Articles of Related Interest

Designer Protein Usage:

How Bacteria Can Escape Destruction: Scientists Discover Mechanism Used To Pump Out Drugs

Bacterial resistance to antibiotics is a major challenge for the current treatment of infectious diseases. One way bacteria can escape destruction is by pumping out administered drugs through specific transporter proteins that span the cell membrane, such as AcrB.


Genetically Modified Cattle Are Prion Free

The U.S. Department of Agriculture's Agricultural Research Service have announced initial results of a research project involving prion-free cattle. ARS scientists evaluated cattle that have been genetically modified so they do not produce prions, and determined that there were no observable adverse effects on the animals' health.


Genomic Variation Easier To Identify With 'Microinversions' Software

Computer scientists at the University of California, San Diego, and Brown University have created a software system that more accurately detects "microinversions," mutations that consist of tiny sequences of reversed DNA. The software gives biologists a powerful new tool to study genomic variation between and within species. The system is explained in the online edition of the Proceedings of the National Academy of Sciences.

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2007 week 01: Articles in General Medicine

Study Sheds New Light On Rare Immunodeficiency Disease

USC researchers have determined the 3-D atomic structure of the Apo2 protein, the first of the APOBEC enzyme family to be described. The protein structure has guided them to a new understanding of what goes wrong on a molecular level in a rare, but serious immunodeficiency syndrome.

Solution structure of a small protein containing a fluorinated side chain in the core

We report the first high-resolution structure for a protein containing a fluorinated side chain... Our findings are important because they complement several studies that have shown that fluorination of saturated side chain carbon atoms can provide enhanced conformational stability.

BPPred: A Web-based computational tool for predicting biophysical parameters of proteins

We exploit the availability of recent experimental data on a variety of proteins to develop a Web-based prediction algorithm (BPPred) to calculate several biophysical parameters commonly used to describe the folding process. These parameters include the equilibrium m-values, the length of proteins, and the changes upon unfolding in the solvent-accessible surface area, in the heat capacity, and in the radius of gyration. We also show that the knowledge of any one of these quantities allows an estimate of the others to be obtained, and describe the confidence limits with which these estimations can be made. Furthermore, we discuss how the kinetic m-values, or the Beta Tanford values, may provide an estimate of the solvent-accessible surface area and the radius of gyration of the transition state for protein folding. Taken together, these results suggest that BPPred should represent a valuable tool for interpreting experimental measurements, as well as the results of molecular dynamics simulations.

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2007 week 01: Articles in Folding


Steiner minimal trees, twist angles, and the protein folding problem

The Steiner Minimal Tree (SMT) problem determines the minimal length network for connecting a given set of vertices in three-dimensional space. SMTs have been shown to be useful in the geometric modeling and characterization of proteins. Even though the SMT problem is an NP-Hard Optimization problem, one can define planes within the amino acids that have a surprising regularity property for the twist angles of the planes. This angular property is quantified for all amino acids through the Steiner tree topology structure. The twist angle properties and other associated geometric properties unique for the remaining amino acids are documented in this paper. We also examine the relationship between the Steiner ratio [rho] and the torsion energy in amino acids with respect to the side chain torsion angle [chi]1. The [rho] value is shown to be inversely proportional to the torsion energy. Hence, it should be a useful approximation to the potential energy function. Finally, the Steiner ratio is used to evaluate folded and misfolded protein structures. We examine all the native proteins and their decoys at . and compare their Steiner ratio values. Because these decoy structures have been delicately misfolded, they look even more favorable than the native proteins from the potential energy viewpoint. However, the [rho] value of a decoy folded protein is shown to be much closer to the average value of an empirical Steiner ratio for each residue involved than that of the corresponding native one, so that we recognize the native folded structure more easily. The inverse relationship between the Steiner ratio and the energy level in the protein is shown to be a significant measure to distinguish native and decoy structures. These properties should be ultimately useful in the ab initio protein folding prediction. Proteins 2007. © 2006 Wiley-Liss, Inc.

Cooperative folding mechanism of a [beta]-hairpin peptide studied by a multicanonical replica-exchange molecular dynamics simulation

G-peptide is a 16-residue peptide of the C-terminal end of streptococcal protein G B1 domain, which is known to fold into a specific [beta]-hairpin within 6 [mu]s. Here, we study molecular mechanism on the stability and folding of G-peptide by performing a multicanonical replica-exchange (MUCAREM) molecular dynamics simulation with explicit solvent. Unlike the preceding simulations of the same peptide, the simulation was started from an unfolded conformation without any experimental information on the native conformation. In the 278-ns trajectory, we observed three independent folding events. Thus MUCAREM can be estimated to accelerate the folding reaction more than 60 times than the conventional molecular dynamics simulations. The free-energy landscape of the peptide at room temperature shows that there are three essential subevents in the folding pathway to construct the native-like [beta]-hairpin conformation: (i) a hydrophobic collapse of the peptide occurs with the side-chain contacts between Tyr45 and Phe52, (ii) then, the native-like turn is formed accompanying with the hydrogen-bonded network around the turn region, and (iii) finally, the rest of the backbone hydrogen bonds are formed. A number of stable native hydrogen bonds are formed cooperatively during the second stage, suggesting the importance of the formation of the specific turn structure. This is also supported by the accumulation of the nonnative conformations only with the hydrophobic cluster around Tyr45 and Phe52. These simulation results are consistent with high [phis]-values of the turn region observed by experiment. Proteins 2007. © 2006 Wiley-Liss, Inc.

Exploring zipping and assembly as a protein folding principle

It has been proposed that proteins fold by a process called "Zipping and Assembly" (Z&A). Zipping refers to the growth of local substructures within the chain, and assembly refers to the coming together of already-formed pieces. Our interest here is in whether Z&A is a general method that can fold most of sequence space, to global minima, efficiently. Using the HP model, we can address this question by enumerating full conformation and sequence spaces. We find that Z&A reaches the global energy minimum native states, even though it searches only a very small fraction of conformational space, for most sequences in the full sequence space. We find that Z&A, a mechanism-based search, is more efficient in our tests than the replica exchange search method. Folding efficiency is increased for chains having: (a) small loop-closure steps, consistent with observations by Plaxco et al. 1998;277;985-994 that folding rates correlate with contact order, (b) neither too few nor too many nucleation sites per chain, and (c) assembly steps that do not occur too early in the folding process. We find that the efficiency increases with chain length, although our range of chain lengths is limited. We believe these insights may be useful for developing faster protein conformational search algorithms. Proteins 2007. © 2006 Wiley-Liss, Inc.

Strategies for high-throughput comparative modeling: Applications to leverage analysis in structural genomics and protein family organization

The technological breakthroughs in structural genomics were designed to facilitate the solution of a sufficient number of structures, so that as many protein sequences as possible can be structurally characterized with the aid of comparative modeling. The leverage of a solved structure is the number and quality of the models that can be produced using the structure as a template for modeling and may be viewed as the "currency" with which the success of a structural genomics endeavor can be measured. Moreover, the models obtained in this way should be valuable to all biologists. To this end, at the Northeast Structural Genomics Consortium (NESG), a modular computational pipeline for automated high-throughput leverage analysis was devised and used to assess the leverage of the 186 unique NESG structures solved during the first phase of the Protein Structure Initiative (January 2000 to July 2005). Here, the results of this analysis are presented. The number of sequences in the nonredundant protein sequence database covered by quality models produced by the pipeline is [sim]39,000, so that the average leverage is [sim]210 models per structure. Interestingly, only 7900 of these models fulfill the stringent modeling criterion of being at least 30% sequence-identical to the corresponding NESG structures. This study shows how high-throughput modeling increases the efficiency of structure determination efforts by providing enhanced coverage of protein structure space. In addition, the approach is useful in refining the boundaries of structural domains within larger protein sequences, subclassifying sequence diverse protein families, and defining structure-based strategies specific to a particular family. Proteins 2007. © 2006 Wiley-Liss, Inc.

A knowledge-based move set for protein folding

The free energy landscape of protein folding is rugged, occasionally characterized by compact, intermediate states of low free energy. In computational folding, this landscape leads to trapped, compact states with incorrect secondary structure. We devised a residue-specific, protein backbone move set for efficient sampling of protein-like conformations in computational folding simulations. The move set is based on the selection of a small set of backbone dihedral angles, derived from clustering dihedral angles sampled from experimental structures. We show in both simulated annealing and replica exchange Monte Carlo (REMC) simulations that the knowledge-based move set, when compared with a conventional move set, shows statistically significant improved ability at overcoming kinetic barriers, reaching deeper energy minima, and achieving correspondingly lower RMSDs to native structures. The new move set is also more efficient, being able to reach low energy states considerably faster. Use of this move set in determining the energy minimum state and for calculating thermodynamic quantities is discussed. Proteins 2007. © 2006 Wiley-Liss, Inc.

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2007 week 01: Articles in Maths


Resources for integrative systems biology: from data through databases to networks and dynamic system models

In systems biology, biologically relevant quantitative modelling of physiological processes requires the integration of experimental data from diverse sources. Recent developments in high-throughput methodologies enable the analysis of the transcriptome, proteome, interactome, metabolome and phenome on a previously unprecedented scale, thus contributing to the deluge of experimental data held in numerous public databases. In this review, we describe some of the databases and simulation tools that are relevant to systems biology and discuss a number of key issues affecting data integration and the challenges these pose to systems-level research.

Strategies for dealing with incomplete information in the modeling of molecular interaction networks

Modelers of molecular interaction networks encounter the paradoxical situation that while large amounts of data are available, these are often insufficient for the formulation and analysis of mathematical models describing the network dynamics. In particular, information on the reaction mechanisms and numerical values of kinetic parameters are usually not available for all but a few well-studied model systems. In this article we review two strategies that have been proposed for dealing with incomplete information in the study of molecular interaction networks: parameter sensitivity analysis and model simplification. These strategies are based on the biologically justified intuition that essential properties of the system dynamics are robust against moderate changes in the value of kinetic parameters or even in the rate laws describing the interactions. Although advanced measurement techniques can be expected to relieve the problem of incomplete information to some extent, the strategies discussed in this article will retain their interest as tools providing an initial characterization of essential properties of the network dynamics.

Dynamic modelling and analysis of biochemical networks: mechanism-based models and model-based experiments

Systems biology applies quantitative, mechanistic modelling to study genetic networks, signal transduction pathways and metabolic networks. Mathematical models of biochemical networks can look very different. An important reason is that the purpose and application of a model are essential for the selection of the best mathematical framework. Fundamental aspects of selecting an appropriate modelling framework and a strategy for model building are discussed.

Concepts and methods from system and control theory provide a sound basis for the further development of improved and dedicated computational tools for systems biology. Identification of the network components and rate constants that are most critical to the output behaviour of the system is one of the major problems raised in systems biology. Current approaches and methods of parameter sensitivity analysis and parameter estimation are reviewed. It is shown how these methods can be applied in the design of model-based experiments which iteratively yield models that are decreasingly wrong and increasingly gain predictive power.

Estimating the parameters of a model for protein-protein interaction graphs

We find accurate approximations for the expected number of three-cycles and unchorded four-cycles under a stochastic distribution for graphs that has been proposed for modelling yeast two-hybrid protein–protein interaction networks. We show that unchorded four-cycles are characteristic motifs under this model and that the count of unchorded four-cycles in the graph is a reliable statistic on which to base parameter estimation. Finally, we test our model against a range of experimental data, obtain parameter estimates from these data and investigate possible improvements in the model. Characterization of this model lays the foundation for its use as a prior distribution in a Bayesian analysis of yeast two-hybrid networks that can potentially aid in identifying false-positive and false-negative results.

A new approach to intensity-dependent normalization of two-channel microarrays

A two-channel microarray measures the relative expression levels of thousands of genes from a pair of biological samples. In order to reliably compare gene expression levels between and within arrays, it is necessary to remove systematic errors that distort the biological signal of interest. The standard for accomplishing this is smoothing "MA-plots" to remove intensity-dependent dye bias and array-specific effects. However, MA methods require strong assumptions, which limit their general applicability. We review these assumptions and derive several practical scenarios in which they fail. The "dye-swap" normalization method has been much less frequently used because it requires two arrays per pair of samples. We show that a dye-swap is accurate under general assumptions, even under intensity-dependent dye bias, and that a dye-swap removes dye bias from a single pair of samples in general. Based on a flexible model of the relationship between mRNA amount and single-channel fluorescence intensity, we demonstrate the general applicability of a dye-swap approach. We then propose a common array dye-swap (CADS) method for the normalization of two-channel microarrays. We show that CADS removes both dye bias and array-specific effects, and preserves the true differential expression signal for every gene under the assumptions of the model.

Regularized linear discriminant analysis and its application in microarrays

In this paper, we introduce a modified version of linear discriminant analysis, called the "shrunken centroids regularized discriminant analysis" (SCRDA). This method generalizes the idea of the "nearest shrunken centroids" (NSC) (Tibshirani and others, 2003) into the classical discriminant analysis. The SCRDA method is specially designed for classification problems in high dimension low sample size situations, for example, microarray data. Through both simulated data and real life data, it is shown that this method performs very well in multivariate classification problems, often outperforms the PAM method (using the NSC algorithm) and can be as competitive as the support vector machines classifiers. It is also suitable for feature elimination purpose and can be used as gene selection method. The open source R package for this method (named "rda") is available on CRAN (http://www.r-project.org) for download and testing.

Are clusters found in one dataset present in another dataset?

In many microarray studies, a cluster defined on one dataset is sought in an independent dataset. If the cluster is found in the new dataset, the cluster is said to be "reproducible" and may be biologically significant. Classifying a new datum to a previously defined cluster can be seen as predicting which of the previously defined clusters is most similar to the new datum. If the new data classified to a cluster are similar, molecularly or clinically, to the data already present in the cluster, then the cluster is reproducible and the corresponding prediction accuracy is high. Here, we take advantage of the connection between reproducibility and prediction accuracy to develop a validation procedure for clusters found in datasets independent of the one in which they were characterized. We define a cluster quality measure called the "in-group proportion" (IGP) and introduce a general procedure for individually validating clusters. Using simulations and real breast cancer datasets, the IGP is compared to four other popular cluster quality measures (homogeneity score, separation score, silhouette width, and weighted average discrepant pairs score). Moreover, simulations and the real breast cancer datasets are used to compare the four versions of the validation procedure which all use the IGP, but differ in the way in which the null distributions are generated. We find that the IGP is the best measure of prediction accuracy, and one version of the validation procedure is the more widely applicable than the other three. An implementation of this algorithm is in a package called "clusterRepro" available through The Comprehensive R Archive Network.

A topologically related singularity suggests a maximum preferred size for protein domains

A variety of protein physicochemical as well as topological properties, demonstrate a scaling behavior relative to chain length. Many of the scalings can be modeled as a power law which is qualitatively similar across the examples. In this article, we suggest a rational explanation to these observations on the basis of both protein connectivity and hydrophobic constraints of residues compactness relative to surface volume. Unexpectedly, in an examination of these relationships, a singularity was shown to exist near 255-270 residues length, and may be associated with an upper limit for domain size. Evaluation of related G-factor data points to a wide range of conformational plasticity near this point. In addition to its theoretical importance, we show by an application of CASP experimental and predicted structures, that the scaling is a practical filter for protein structure prediction. Proteins 2007. © 2006 Wiley-Liss, Inc.

Probabilistic alignment detects remote homologyin a pair of protein sequences without homologous sequence information

Dynamic programming (DP) and its heuristic algorithms are the most fundamental methods for similarity searches of amino acid sequences. Their detection power has been improved by including supplemental information, such as homologous sequences in the profile method. Here, we describe a method, probabilistic alignment (PA), that gives improved detection power, but similarly to the original DP, uses only a pair of amino acid sequences. Receiver operating characteristic (ROC) analysis demonstrated that the PA method is far superior to BLAST, and that its sensitivity and selectivity approach to those of PSI-BLAST. Particularly for orphan proteins having few homologues in the database, PA exhibits much better performance than PSI-BLAST. On the basis of this observation, we applied the PA method to a homology search of two orphan proteins, Latexin and Resuscitation-promoting factor domain. Their molecular functions have been described based on structural similarities, but sequence homologues have not been identified by PSI-BLAST. PA successfully detected sequence homologues for the two proteins and confirmed that the observed structural similarities are the result of an evolutional relationship. Proteins 2007 © 2006 Wiley-Liss, Inc.

iGibbs: Improving Gibbs motif sampler for proteins by sequence clustering and iterative pattern sampling

The motif prediction problem is to predict short, conserved subsequences that are part of a family of sequences, and it is a very important biological problem. Gibbs is one of the first successful motif algorithms and it runs very fast compared with other algorithms, and its search behavior is based on the well-studied Gibbs random sampling. However, motif prediction is a very difficult problem and Gibbs may not predict true motifs in some cases. Thus, the authors explored a possibility of improving the prediction accuracy of Gibbs while retaining its fast runtime performance. In this paper, the authors considered Gibbs only for proteins, not for DNA binding sites. The authors have developed iGibbs, an integrated motif search framework for proteins that employs two previous techniques of their own: one for guiding motif search by clustering sequences and another by pattern refinement. These two techniques are combined to a new double clustering approach to guiding motif search.
Tests on the PROSITE database show that their framework improved the prediction accuracy of Gibbs significantly. Compared with more exhaustive search methods like MEME, iGibbs predicted motifs more accurately and runs one order of magnitude faster. Proteins 2007. © 2006 Wiley-Liss, Inc.

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Welcome Mathematicians and Ferret-Lovers!


This brain-child was first spontaneously conceived at the end of 2006, but the full-blown birth occurred in 2007, ringing in the New Year of the Boar!!

What We Are Doing:
As the subtitle says, we're a group of interested people looking to apply maths in the quest to find solutions in veterinary science. Historically, a majority of applied mathematics has been used to study human aliments; we wish now to turn our focus to other equally worthy endeavors - our companion animals.

What Can You Expect To See Here:
We'll be posting links, articles, conjectures and information from all the relevant maths and veterinary sciences to help us further our goal. The most commonly applied maths addressed will be in the fields of dynamics, topology, biomathematics, and biostatistics.

Our Goal:
A better quality of life for animal companions, specifically Mustela putorius furo - the domesticated ferret - through advances in disease prevention, diagnosis and treatment.

No idea is without merit, so send your comments in for review & discussion!!

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