Sep 13, 2011

New Findings @Boinc!



ENTIRE CATALOG OF FERRET PROTEINS TO DATE



We received a nice comment recently that re-inspired us to get back to work on this site.

This led us, first, straight back to Boinc especially now that we have access to a second, mostly unused computer for processing.
I have to say, after an extended absence, we were very happy to see not one, but TWO new protein related projects @Boinc.

After some research, we decided to add one of the new projects to the existing FerretKnots Boinc team.

Now, in addition to Rosetta@Home we are happy to be participating in

POEM@HOME, sponsored by the Karlsruhe Institute of Technology (KIT) of Germany.

Research Goals of POEM@HOME:
"... a computational approach to
  • predict the biologically active structure of proteins
  • understand the signal-processing mechanisms when the proteins interact with one another
  • understand diseases related to protein malfunction or aggregation
  • develop new drugs on the basis of the three-dimensions structure of biologically important proteins.
The scientific approach behind POEM@HOME is a computational realization of the thermodynamic hypothesis that won C. B. Anfinsen the Nobel Prize in Chemistry in 1972."

Research Goals of Rosetta@Home:
"The goal of our current research is to develop an improved model of intra- and intermolecular interactions and to use this model to predict and design macromolecular structures and interactions.  Prediction and design applications, which can be of great biological interest in their own right, also provide stringent and objective tests that improve the model and increase fundamental understanding.
We use a computer program called Rosetta to carry out protein and design calculations. At the core of Rosetta are potential functions for computing the energies of interactions within and between macromolecules, and methods for finding the lowest energy structure for an amino acid sequence (protein-structure prediction) or a protein-protein complex and for finding the lowest energy amino acid sequence for a protein or protein-protein complex (protein design). ..."

So once again, for the health and welfare of ferrets everywhere, we invite you to participate with us in the FerretKnots Boinc team.

Proteins are Pretty!
(yes, now you can even help by playing a GAME.)


Thanks for stopping in. We hope you'll be back!

All translations copyrighted and owned by myself. All copyrights of their respective owners. No part of this web site may be produced, reproduced, stored in a retrieval system, or transmitted in any form or by any means without the written permission of the copyright owner.

Labels: , , , , , , ,

May 20, 2007

2007 Week 20: Proteins

ENTIRE CATALOG OF FERRET PROTEINS TO DATE



Columbia scientists determine 3-dimensional structure of cell's 'fuel gauge'
Researchers at Columbia University Medical Center have uncovered the complex structure of a protein that serves as a central energy gauge for cells, providing crucial details about the molecule necessary for developing useful new therapies for diabetes and possibly obesity. A paper published online today in the journal Science details this structure, helping to explain one of the cell's most basic and critical processes.

Electrons travel through proteins like urban commuters
For Duke University theoretical chemist David Beratan, the results of his 15 years of studying how electrons make their way through some important protein molecules can be summed up with an analogy: how do big city dwellers get from here to there?
In the Friday, Feb. 2, issue of the journal Science, Beratan and two co-authors use similar logic to describe their unified description of electron movements through certain "electron-transfer" proteins that lie at the heart of many processes essential for life. Such processes include harvesting light in photosynthesis in plant cells and generating energy in animal cells. "I think we have discovered the physical framework for thinking about all such protein electron-transfer chemistry," Beratan said. "Having this rule book in place will let scientists pose some hard but interesting questions about evolutionary pressures on protein structures.

Indel-based targeting of essential proteins in human pathogens that have close host orthologue(s): Discovery of selective inhibitors for Leishmania donovani elongation factor-1
We propose a novel strategy for selective targeting of essential pathogen proteins that contain sizable indels (insertions/deletions) in their sequences compared with their host orthologues. This approach has been tested on elongation factor-1[alpha] (EF-1[alpha]) from the protozoan pathogen Leishmania donovani. Leishmania EF-1[alpha] is 82% identical to the corresponding human orthologue, but possesses a 12 aminoacid sequence deletion compared with human EF-1[alpha]. We used this indel-differentiated region to design small molecules that selectively bind to leishmania EF-1[alpha] and not to the human protein. Three unrelated molecules were identified with the capacity to inhibit protein synthesis in leishmania by up to 75% while exhibiting no effect on human protein translation. These candidates may serve as prototypes for future development of antiprotozoan therapeutics. More generally, these findings provide a basis for a novel drug design platform. This platform targets essential pathogen proteins that are highly conserved across species, and consequently would not typically be considered to be conventional drug targets. We anticipate that such indel-directed targeting of essential proteins in microbial pathogens may help address the growing problem of antibiotic resistance.

Is glycine a surrogate for a D-amino acid in the collagen triple helix?
Collagen is the most abundant protein in animals. Every third residue in a collagen strand is a glycine with , = –70°, 175°. A recent computational study suggested that replacing these glycine residues with d-alanine or d-serine would stabilize the collagen triple helix. This hypothesis is of substantial importance, as the glycine residues in collagen constitute nearly 10% of the amino acid residues in humans. To test this hypothesis, we synthesized a series of collagen mimic peptides that contain one or more d-alanine or d-serine residues replacing the canonical glycine residues. Circular dichroism spectroscopy and thermal denaturation experiments indicated clearly that the substitution of glycine with d-alanine or d-serine greatly disfavors the formation of a triple helix. Host–guest studies also revealed that replacing a single glycine residue with d-alanine is more destabilizing than is its replacement with l-alanine, a substitution that results from a common mutation in patients with collagen-related diseases. These data indicate that the glycine residues in collagen are not a surrogate for a d-amino acid and support the notion that the main-chain torsion angles of a glycine residue in the native structure (especially, > 0°) are critical determinants for its beneficial substitution with a d-amino acid in a protein.

Protein-protein recognition and interaction hot spots in an antigen-antibody complex: Free energy decomposition identifies “efficient amino acids”
The molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) method was applied to the study of the protein-protein complex between a camelid single chain variable domain (cAb-Lys3) and hen egg white lysozyme (HEL), and between cAb-Lys3 and turkey egg white lysozyme (TEL). The electrostatic energy was estimated by solving the linear Poisson-Boltzmann equation. A free energy decomposition scheme was developed to determine binding energy hot spots of each complex. The calculations identified amino acids of the antibody that make important contributions to the interaction with lysozyme. They further showed the influence of small structural variations on the energetics of binding and they showed that the antibody amino acids that make up the hot spots are organized in such a way as to mimic the lysozyme substrate. Through further analysis of the results, we define the concept of "efficient amino acids," which can provide an assessment of the binding potential of a particular hot spot interaction. This information, in turn, can be useful in the rational design of small molecules that mimic the antibody. The implications of using free energy decomposition to identify regions of a protein-protein complex that could be targeted by small molecules inhibitors are discussed.


Thanks for stopping in! We hope you'll be back!

Ads make the world go around. Help us out!

Labels: , , , , , , , ,

2007 Week 20: Ferret Medical Studies

ENTIRE CATALOG OF FERRET PROTEINS TO DATE


The effect of inflammation on Fos expression in the ferret trigeminal nucleus
We have previously carried out detailed characterization and identification of Fos expression within the trigeminal nucleus after tooth pulp stimulation in ferrets. The aim of this study was to determine the effect of pulpal inflammation on the excitability of central trigeminal neurons following tooth pulp stimulation. Adult ferrets were prepared under anesthesia to allow tooth pulp stimulation, recording from the digastric muscle, and intravenous injections at a subsequent experiment. In some animals, pulpal inflammation was induced by introducing human caries into a deep buccal cavity. After 5 d, animals were re-anaethetized, and the teeth were stimulated at 10 times the threshold of the jaw-opening reflex. Stimulation of all tooth pulps induced ipsilateral Fos in the trigeminal subnuclei caudalis and oralis. All non-stimulated animals showed negligible Fos labeling, with no differences recorded between inflamed and non-inflamed groups. Following tooth pulp stimulation, Fos expression was greater in animals with inflamed teeth than in animals with non-inflamed teeth, with the greatest effect seen in the subnucleus caudalis. These results suggest that inflammation increases the number of trigeminal brainstem neurons activated by tooth pulp stimulation; this may be mediated by peripheral or central mechanisms.

Neuronal vacuolation in an adult ferret
The brain of a ferret showing abnormal neurologic signs was evaluated by histopathologic, histochemical, immunohistochemical, and ultrastructural examinations. Extensive neuronal vacuolation was observed. Since the brain was negative for protease-resistant protein prion (PrP'"), it was concluded that this was not a case of transmissible spongiform encephalopathy.


Bioelectric properties of chloride channels in human, pig, ferret, and mouse airway epithelia

In the study reported here, we sought to comparatively characterize the bioelectric properties of in vitro polarized airway epithelia--from human, mouse, pig and ferret--grown at the air-liquid interface (ALI). Bioelectric properties analyzed include amiloride-sensitive Na(+) transport, 4,4'-diisothiocyanato-stilbene-2,2'-disulfonic acid (DIDS)-sensitive Cl(-) transport, and cAMP-sensitive Cl(-) transport. In addition, as an index for CFTR functional conservation, we evaluated the ability of four CFTR inhibitors, including glibenclamide, 5-nitro-2-(3-phenylpropyl-amino)-benzoic acid, CFTR (inh)-172, and CFTR(inh)-GlyH101, to block cAMP-mediated Cl(-) transport. Compared with human epithelia, pig epithelia demonstrated enhanced amiloride-sensitive Na(+) transport. In contrast, ferret epithelia exhibited significantly reduced DIDS-sensitive Cl(-) transport. Interestingly, although the four CFTR inhibitors effectively blocked cAMP-mediated Cl(-) secretion in human airway epithelia, each species tested demonstrated unique differences in its responsiveness to these inhibitors. These findings suggest the existence of substantial species-specific differences at the level of the biology of airway epithelial electrolyte transport, and potentially also in terms of CFTR structure/function.

High-throughput immunophenotyping of 43 ferret lymphomas using tissue microarray technology
To validate the use of the tissue microarray (TMA) method for immunophenotyping of ferret lymphomas, a TMA was constructed containing duplicate 1-mm cores sampled from 112 paraffin-embedded lymphoma tissue specimens obtained from 43 ferret lymphoma cases. Immunohistochemical (IHC) expression of CD3, CD79alpha, and Ki-67 (MIB-1) was determined by TMA and whole mount (WM) staining of each individual case for result comparison. There was a high correlation between CD79alpha and CD3 results comparing ferret TMA and WM sections (kappa statistic 0.71-0.73 for single-core TMA and 0.79-0.95 for duplicate-core TMA) and between continuous data from Ki-67 staining of ferret TMA sections and WM sections (concordance correlation coefficients 0.77 for single cores and 0.87 for duplicate cores). Subsequently, a panel of commercially available antibodies was applied to the TMA for the analysis of expression in ferret lymphomas. The results of this study confirmed previously published results suggesting specific cross-reactivity of the applied IHC markers (CD3, CD79alpha, Ki67) with ferret lymphoma tissue. Other IHC markers (CD45Ro, bcl2, bcl10, MUM1, CD30, vimentin) were also expressed in subsets of the included ferret lymphomas. Further studies are necessary to determine the usefulness of these markers for diagnostic and prognostic evaluation of ferret lymphomas. In conclusion, the TMA technology was useful for rapid and accurate analysis of protein expression in large archival cohorts of ferret lymphoma cases.


Thanks for stopping in! We hope you'll be back!

Ads make the world go around. Help us out!

Labels: , , , , , ,

May 5, 2007

2007 week 18: Gentle Intro to Proteins & Folding

ENTIRE CATALOG OF FERRET PROTEINS TO DATE

Some articles to help you get your feet wet...
Follow the links for the full article as usual.

PROTEINS: GENERAL

Rensselaer Researchers Develop Approach That Predicts Protein Separation Behavior:
Applying math and computers to the drug discovery process, researchers at Rensselaer Polytechnic Institute have developed a method to predict protein separation behavior directly fromprotein structure. This new multi-scale protein modeling approach may reduce the time it takes to bring pharmaceuticals to market and mayhave significant implications for an array of biotechnology applications, including bioprocessing, drug discovery, and proteomics,the study of protein structure and function.
"Weintend to test the model against more complicated protein structures aspart of its further development," said Breneman. "The outcome of this work will yield fundamental information about the complex relationship between a protein's structural features and its chemical binding properties, and also aid in evaluating its potential biomedical applications."

Beyond Biology: Simple System Yields Custom-designed Proteins:
The diversity of nature may be enormous, but for Michael Hecht it is just a starting point.Hecht, a Princeton professor of chemistry, has invented a technique for making protein molecules from scratch, a long-sought advance that will allow scientists to design the most basic building blocks of all living things with a variety of shapes and compositions far greater than those available in nature.
Nearly all the internal workings of living things are built from proteins. While genes are the "blueprints" for organisms, proteins are the products built from those instructions. The molecules that transmit signals in the brain, carry oxygen in the blood and turn genes on and off are all proteins.
Scientists have long wanted to design their own proteins, but doing so has proved a major challenge. Proteins are strings of chemical units called amino acids and are often more than 100 amino acids long. When cells make them, these long chains fold spontaneously into complex three-dimensional shapes that fit like puzzle pieces with other molecules and give proteins their unique abilities. There are 20 different amino acids, so the number of possible combinations is enormous. However, the vast majority of these combinations are useless because they cannot fold into protein-like structures.
The advance reported by Hecht and colleagues involves a simple system for designing amino acid sequences that fold like natural proteins. First publishing the idea in 1993, Hecht realized that some amino acids were strongly "water-loving" while others were "oil-loving." The two types naturally separate from each other, with the oil-loving ones clustering in the protein core and water-loving ones forming the perimeter. He also saw that natural proteins with good structures tend to have certain repeating patterns of oil-loving and water-loving amino acids. For example, taking a string of water-loving units -- no matter which ones -- and inserting any oil-loving unit every three or four positions typically creates proteins that fold into bundles of helices.

Lasers Improve Scientists' Understanding Of Complex Proteins:
By shooting lasers at an RNA polymerase (RNAP) and a strand of DNA, scientists have learned a critical component of how a complex protein develops.
Using a system called fluorescence resonance energy transfer (FRET) on a single molecule, a researcher at the Lawrence Livermore National Laboratory’s Physical Biosciences Institute (PBI) in collaboration with UCLA scientists found that the procedure that regulates genes in a strand of DNA is a single process.
Earlier studies done with less precision resulted in scientists believing that the beginning and end phases of RNAP copying a DNA strand into RNA were two different processes. Using FRET, however, the recent study suggests that “there is no mechanistic difference between the start and finish,” said Ted Laurence of Livermore’s PBI. RNAP is the molecular machine that serves as a gene transcription tool. When it attaches to a strand of DNA, RNAP transcribes genes to RNA, which then is translated into a protein.

Livermore & NIH Scientists Create Technique To Examine Behavior Of Proteins At Single Molecule Level:
The work, presented in the Aug. 29 edition of Science, marks the first time protein-folding kinetics has been monitored on the single-molecule level. Proteins are long chains of amino acids. Like shoelaces, they loop about each other or fold in a variety of ways, and only one way allows the protein to function properly. Just as a knotted shoelace can be a problem, a misfolded protein can do serious damage. Many diseases, such as Alzheimer's, cystic fibrosis, mad cow disease and many cancers result from misfolded protein.

PROTEINS: FOLDING
The Path To A Folded Protein, Long A Subject Of Debate, Appears In Many Cases To Be Long And Winding:
It's a long-simmering debate in the world of physical chemistry: Does the folding of proteins into biologically active shapes better resemble a luge run fast, linear and predictable or the more freeform trajectories of a ski slope? New research from the University of Pennsylvania offers the strongest evidence yet that proteins shimmy into their characteristic shapes not via a single, unyielding route but by paths as individualistic as those followed by skiers coursing from a mountain summit down to the base lodge. The new support for a more heterogeneous model of protein folding comes in a paper published today on the Web site of the Proceedings of the National Academy of Sciences.

"The traditional view has been that a protein passes through a series of fixed reactions to reach its folded state," said senior author Feng Gai, a Penn chemist. "Our work suggests quite strongly that folding is a far richer phenomenon. Like skiers, some proteins rocket down an energy gradient to their destination while others take their time, meandering indiscriminately."

Gai's work subtly shifts scientists' understanding of one possible remedy: molecular chaperones, promising compounds that "rescue" misfolded proteins and are believed capable of blocking the progression of neurodegenerative disease. Rather than giving sluggish proteins the oomph to finish folding, the Penn work indicates that chaperones may return misfolded proteins to an unfolded state so they can start all over again.

"In the skiing analogy, chaperones could be thought of as rescue helicopters that return wayward skiers to the summit so they can try to make their way down the mountain again," said Gai, an assistant professor of chemistry at Penn.

Untangling The Protein Folding Problem:
Protein folding research is "undergoing explosive growth," according to an editorial by Jay Winkler, Ph.D., and Harry Gray, Ph.D., both chemists at the California Institute of Technology and guest editors for the special issue. "Protein folding was once considered an almost intractable problem," write Winkler and Gray, but new efforts "are beginning to reveal the secrets of this prototypal spontaneous self-assembly process."

The special journal issue focuses on the chemical kinetics of the folding phenomenon -- the rate of change as the protein assumes its three-dimensional structure -- and includes a study on recent efforts to make "real time" observations. Folding happens very quickly, which makes it difficult to observe.

For some proteins, the change occurs in milliseconds (thousandths of a second); for others, it can be even faster. Despite recent progress toward understanding the mechanisms of protein folding, scientists still don't agree on exactly how it happens, as evidenced in the journal by the differing conclusions of several articles about the same protein.

Proteins are involved in many vital roles in humans, including metabolism, immunity and muscle movement. They are made up of amino acids, and it is the sequence of these amino acids that determines the eventual folded structures of the proteins, as well as the actual mechanism of the folding process.

Since a protein's structure is a key factor in how it functions in the body, the goal for researchers is to be able to predict the final three-dimensional structure based on the amino acid sequence.

How Proteins Fold Into Their Critical Shapes:
Experimental evidence provided by a Cornell researcher and colleagues at the Scripps Research Institute in La Jolla, Calif., support a long-held theory of how and where proteins fold to create their characteristic shapes and biological functions.
The theory proposes that proteins start to fold in specific places along an amino acid chain (called a polypeptide chain) that contains nonpolar groups, or groups of molecules without a charge, and continue to fold by aggregation, i.e., as several individuals of these nonpolar groupings combine. Using the same principle that separates oil and water, these molecules are hydrophobic -- they avoid water and associate with each other.

In the water-based cell fluid, where long polypeptide chains are manufactured and released by ribosomes, the polypeptide chains rapidly fold up into their biologically functional structure. The theory proposes that there are sites along the polypeptide chains where hydrophobic groups initially fold in on themselves, creating small nonpolar (hydrophobic) pockets that are protected from the water.

Research Answers Key Question In Biochemistry: How Proteins Fold Into 3-D Structures:
In research published in the July 29 issue of Nature, U of T post-doctoral fellow Dmitry Korzhnev and his supervisor, Professor Lewis Kay of the Department of Biochemistry, become the first researchers to characterize at an atomic level of detail the intermediate -- or substructure -- that forms as a protein folds to its 3-D state.

"Understanding how proteins fold is one of the Holy Grails of biochemistry," says Kay. "The intermediates that we can study make up only one or two per cent of the population of protein molecules in solution. It's hard to study them because they are present at such low levels. This is the first time we have been able to characterize an intermediate state at this level of detail."

If scientists can understand the pathway a protein takes from one state to another, they may be able to predict protein structure, something that can't be done very reliably at present. The ability to accurately predict protein structure has implications for drug design, as well as for improving commercial products.

Understanding the pathway a protein follows will also help scientists understand errors in folding, a problem linked to diseases such as cystic fibrosis and Alzheimer's.

Most Stable Parts Of Protein Are The First To Fold, Study Finds:
Like a 1950's Detroit automaker, it appears that nature prefers to build its proteins around a solid, sturdy chassis.

A new study combining advanced computational modeling and cutting-edge experiments by molecular biologists at Rice University and Baylor College of Medicine suggests that the most stable parts of a protein are also the parts that fold first.

Nature refuses to choose between form and function when it comes to protein folding; each protein's function is directly related to its shape, and when proteins misfold -- something that's known to occur in a number of diseases like Alzheimer's and Huntington's -- they don't function as they should.

In the new study, scientists designed and tested a new computational approach that aimed to study proteins with known shapes in order to ascertain which of their parts were the most stable in the face of chemical and thermal fluctuations.

"As far as we know, no one has ever used this type of knowledge-based, statistical approach to predict the stability cores of proteins," Ma said. "Our results suggest that thermodynamics and kinetics are closely correlated in proteins and appear to have co-evolved for optimizing both the folding rate and the stability of proteins."

Quantum Leap In Protein Folding Calculations:
Applying techniques derived from classical and quantum physics calculations may radically reduce the time it takes to simulate the way that proteins fold.

It's vital to understand the shapes that proteins take on as they fold up because the shapes determine how they function, both in keeping cells running and in leading to various diseases.

Rather than calculating the motions of a protein molecule step by step, as most simulations do, a team of Italian and French physicists studied the evolution of a molecule using variational principles. The technique allowed the physicists to evaluate all the possible paths that the molecule's parts would follow and then pick out the most likely one.

As a result, they expect to streamline protein folding calculations from trillions of steps to hundreds. The improvement is significant because conventional protein folding simulations that currently require supercomputers or large PC farms could instead be solved with individual desktop PCs running variational principle calculations.

Comprehensive Model Is First To Map Protein Folding At Atomic Level:
Scientists at Harvard University have developed a computer model that, for the first time, can fully map and predict how small proteins fold into three-dimensional, biologically active shapes. The work could help researchers better understand the abnormal protein aggregation underlying some devastating diseases, as well as how natural proteins evolved and how proteins recognize correct biochemical partners within living cells.

The technique, which can track protein folding for some 10 microseconds -- about as long as some proteins take to assume their biologically stable configuration, and at least a thousand times longer than previous methods -- is described this week in the Proceedings of the National Academy of Sciences.

"For years, a sizable army of scientists has been working toward better understanding how proteins fold," says co-author Eugene I. Shakhnovich, professor of chemistry and chemical biology in Harvard's Faculty of Arts and Sciences. "One of the great problems in science has been deciphering how amino acid sequence -- a protein's primary structure -- also determines its three-dimensional structure, and through that its biological function. Our paper provides a first solution to the folding problem, for small proteins, at an atomic level of detail."

Fiendishly intricate, protein folding is crucial to the chemistry of life. Each of the body's 20 amino acids, the building blocks of proteins, is attracted or repulsed by water; it's largely these affinities that drive the contorting of proteins into distinctive three-dimensional shapes within the watery confines of a cell. The split-second folding of gangly protein chains into tight three-dimensional shapes has broad implications for the growing number of disorders believed to result from misfolded proteins or parts of proteins, most notably neurodegenerative disorders such as Alzheimer's and Parkinson's diseases.

The model developed by Shakhnovich and colleagues faithfully describes and catalogs countless interactions between the individual atoms that comprise proteins. In so doing, it essentially predicts, given a string of amino acids, how the resulting protein will fold -- the first computer model to fully replicate folding of a protein as happens in nature. In more than 4,000 simulations conducted by the researchers, the computer model consistently predicted folded structures nearly identical to those that have been observed experimentally.

PROTEINS: FOLDING MUTATIONS & ERRORS

What Mutations Tell Us About Protein Folding:
Scientists continue to be puzzled by how proteins fold intotheir three-dimensional structures. Small single-domain proteins mayhold the key to solving this puzzle. These proteins often fold intotheir three-dimensional structures by crossing only a single barrier.The barrier consists of an ensemble of extremely short-lived transitionstate structures which cannot be observed directly. However, mutations that slightly shift the folding barrier may provide indirect access to transition states.

The reliable folding of proteins is a prerequisite forthem to function robustly. Mis-folding can lead to protein aggregates that cause severe diseases, such as Alzheimer's, Parkinson's, or the variant Creutzfeldt-Jakob disease. To understand protein folding,research has long focused on metastable folding intermediates, whichwere thought to guide the unfolded protein chain into its foldedstructure. It came as a surprise about a decade ago that certain smallproteins fold without any detectable intermediates. This astonishingly direct folding from the unfolded state into the folded state has been termed 'two-state folding'. In the past few years, scientists have shown that the majority of small single-domain proteins are 'two-state folders', which are now a new paradigm in protein folding.

The characteristic event of two-state folding is the crossing of a barrierbetween the unfolded and folded state. This folding barrier is thought to consist of a large number of extremely short-lived transition state structures. Each of these structures is partially folded and will either complete the folding process, or will unfold again, with equal probability. Transition state structures are thus similar to a ball ona saddle point, which has the same probability, 0.5, of rolling toeither side of the saddle.

Since transition state structures arehighly instable, they cannot be observed directly. To explore two-statefolding, experimentalists instead create mutants of a protein. Themutants typically differ from the original protein -- the wild type --in just a single amino acid. The majority of these mutants still foldinto the same structure, however the mutations may slightly change thetransition state barrier and, thus the folding time; that is, the timean unfolding protein chain on average needs to cross the foldingbarrier.

The central question is: can we reconstruct the transition state from the observed changes in the folding times? Such a reconstruction clearly requires experimental data on a large number of mutants. In the traditional interpretation, the structural information is extracted for each mutation, independent of the other mutations. Ifa mutation does not change the folding time, then the mutated amino acid traditionally is interpreted to be still unstructured in the transition state. In contrast, if a mutation changes the folding time,the mutated amino acid is interpreted to be partially or fully structured in the transition state, depending on the magnitude of the change.

In a recent article in PNAS, a research team from the MaxPlanck Institute of Colloids and Interfaces and the University of California, San Francisco has suggested a novel interpretation of the mutational data. Instead of considering each mutation on its own, the new interpretation collectively considers all mutations within acooperative substructure, such as a helix. In case of the ±-helix ofthe protein CI2, this leads to a structurally consistent picture, inwhich the helix is fully formed in the transition state, but has not yet formed significant interactions with the ²-sheet.

In the future, the Max Planck researchers hope to construct complete transition states from mutational data. An important step is to identify the cooperative subunits of proteins, which requires molecular modelling. In a similar way to how a mountain pass shows us how to cross the landscape, the transition states eventually may help us to understand how proteins navigate from the unfolded into the folded structure.

Penn Scientists Show How Mistakes In Protein Folding Are Caught By "Protein Cages" Called Chaperonins:
It's imperative for all biological processes that proteins correctly maneuver from a simple string of amino acids to their pre-destined three-dimensional structure. This transformation -- called protein folding - is one of the most active areas of molecular biological research, and has taken on even more importance with the growing knowledge that misfolding can lead to such disorders as Alzheimer's disease, Huntington's disease, and prion-related neurodegenerative diseases. Recently, researchers at the University of Pennsylvania Medical Center have discovered how proteins called chaperonins protect cells from harm by sequestering and unfolding misshapened proteins. A report on this study appears in the April 30 issue of Science.

"Proteins should know how to fold by themselves, but they sometimes get into trouble," says senior author S. Walter Englander, PhD, a professor of biochemistry and biophysics at the University of Pennsylvania School of Medicine. In times of stress, cells produce chaperonins, which are huge protein molecules that police other proteins that have misfolded as a result of any number of stressors -- including heat, heavy-metal poisoning, and ultraviolet radiation. If left unchecked, the misfolded proteins tend to clump, which can be harmful to normal cellular functions.

The Penn study looked specifically at a chaperonin called GroEL. "GroEL grabs the misfolded protein, engulfs it, pulls it open, and then throws it back out into the cytoplasm of the cell to fend for itself, " explains Englander. "The protein then takes its chances -- it may fold successfully, or it may get into trouble again." This entire process takes place within 13 seconds.

GroEL -- a sandwich of two circular proteins with a large central core into which average-sized proteins can fit - is able to capture thousands of different types of misfolded proteins. Its cavity is ringed with sites that bind nonspecifically to the hydrophobic, or water-avoiding, portions of proteins, which are normally found tucked deep inside a properly folded protein. "When a protein is misfolded and its hydrophobic insides are exposed, chaperonins snatch them up and help them to fold correctly by forcing them to unfold, so that they can try again," notes Englander.

Mechanism Of Protein Folding Unraveled, With Eventual Implications For Treating Diseases Caused By Folding Errors:
How a protein manages to fold is a seemingly impossible problem, suggests S. Walter Englander, PhD, a professor of biochemistry and biophysics at the University of Pennsylvania School of Medicine: "Even with a small, 100-amino-acid-long protein, the number of possible three-dimensional structures that the protein might manifest is larger than the number of molecules in the universe." Protein biologists believe that the amino-acid sequences laid out by the genetic machinery contain chemical instructions for the pathway that carries each protein to its final structure.

The Penn experiments show that the amino-acid chain progresses through a series of pre-determined, intermediate arrangements. Englander's lab has demonstrated that the protein cytochrome c builds its structure in steps by first making helices at either end that lay at right angles to each other. Then, strands, loops, and other helices build up against that initial foundation until the final arrangement is reached. All this can occur in less than one second, but trouble can arise along the way. "A few years ago we showed that on the complicated journey to their final structure, proteins have a large tendency to make mistakes that greatly slow them down," notes Englander. "Proteins need to fold fast because if they spend too much time in one intermediate state, they're vulnerable to aggregation with other proteins in the midst of folding, which can be very destructive to the cell."

The recent work straightens out misinterpretations about how fast this process can proceed. "Numerous papers published in the past two years all conclude that when you initiate folding in a rapid reaction experiment, you see some very fast sub-millisecond optical signal changes, as well as some slower ones" explains Englander. "This has always been interpreted as a rapid formation of some real structural intermediates. It is crucially important to understand which of these signals represent real protein behavior and which give you misleading clues that simply depend on the kind of experiment you are doing. Understanding the folding process and the real time scale of events begins to give you some idea of what you can do to fight diseases like Alzheimer's."

Englander's lab performed experiments that convincingly showed that these exceedingly fast initial signals are not real intermediates, but simply represent the protein stretching and pulling in the denaturing solution used in the experiment. The researchers made two copies of the same amino-acid chain, one that couldn't fold and one that could, and observed that both versions displayed the same initial ultra-fast burst of optical activity.


Thanks for stopping in! We hope you'll be back!

Ads make the world go around. Help us out!

Labels: , , , , ,

Mar 5, 2007

2007 week 10: Protein Prediction Programs

ENTIRE CATALOG OF FERRET PROTEINS TO DATE


ROSETTA@Home
This is the one I personally use. Easy setup, easy monitoring functions, allows resource allocation. You can join teams and connect with others on the message boards. Plus, with the BOINC manager, you can add and contribute to other distributed computing projects.
I have never had any errors or problems, unlike the Standford one which was CONSTANTLY "searching" and never downloaded anything. This project was also briefly introduced on the science daily website here.

Our team is ~Ferret Knots~. Join! It's painless. AND it is an easy way to contribute to the scientific community and future of medicine without the stress of needing to know what it is all about. ^.^

TANPAKU
This is a Japanese Protein Predictor program. Although the project and main pages are in Japanese, you can also view the pages in English. I wrote to them at one point about their status. They, like Rosetta, also claim to to be not-for-profit. They have some vary nice protein-related articles. Plus, like Rosetta not only do they have message boards and the ability to make/join teams, they are also BOINC-compatible. The project is based in Tokyo University.

FOLDING@Home
This is the Standford Program I mentioned above. I tried several times to no avail. As such, I really can not recommend it because it never worked for me. We are donating are time and computer resources freely, the least they should provide is a well written program. It is a more heavily graphic based program so if you can get it to run, good for you. If not you can always stick with Rosetta or Tanpaku.

Thanks for stopping in! We hope you'll be back!

Ads make the world go around. Help us out!

Labels: , ,

Jan 27, 2007

2007 week 05: Articles in Proteins

ENTIRE CATALOG OF FERRET PROTEINS TO DATE


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.


Thanks for stopping in! We hope you'll be back!

Ads make the world go around. Help us out!

Labels: , , , , , , , , , , , ,

2007 week 05: Articles of Related Interest

ENTIRE CATALOG OF FERRET PROTEINS TO DATE


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.

Thanks for stopping in! We hope you'll be back!

Ads make the world go around. Help us out!

Labels: , , , , , , , , , , ,

Jan 13, 2007

2007 week 03: Articles in Proteins

ENTIRE CATALOG OF FERRET PROTEINS TO DATE



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.


Thanks for stopping in! We hope you'll be back!

Ads make the world go around. Help us out!

Labels: , , , , , ,

2007 week 03: Articles in Maths

ENTIRE CATALOG OF FERRET PROTEINS TO DATE


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”.


Thanks for stopping in! We hope you'll be back!

Ads make the world go around. Help us out!

Labels: , , , , , , ,

Jan 10, 2007

2007 week 03: Articles in Folding

ENTIRE CATALOG OF FERRET PROTEINS TO DATE


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.

Thanks for stopping in! We hope you'll be back!

Ads make the world go around. Help us out!

Labels: , , , , , , ,

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*

BIOCHEMISTRY

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

CELL METABOLISM

Entry into the Endoplasmic Reticulum: Protein Translocation, Folding and Quality Control
Introduction
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
Introduction
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

MOLECULAR BIOLOGY OF THE CELL

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

MOLECULAR CELL BIOLOGY

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

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

Moviesof some folding proteins.
-Quicktime Required


Thanks for stopping in! We hope you'll be back!

Ads make the world go around. Help us out!

Labels: , ,

Jan 3, 2007

2007 week 01: Articles in Veterinary Science

ENTIRE CATALOG OF FERRET PROTEINS TO DATE


Isolation of ferret protein promising for cancer, reproductive studies
Although the focus of the study was about pregnancy, there was this interesting general finding.
Clip:
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.

Thanks for stopping in! We hope you'll be back!

Ads make the world go around. Help us out!

Labels: , , ,

Jan 2, 2007

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.


Thanks for stopping in! We hope you'll be back!

Ads make the world go around. Help us out!

Labels: , , ,

2007 week 01: Articles in Maths

ENTIRE CATALOG OF FERRET PROTEINS TO DATE


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.


Thanks for stopping in! We hope you'll be back!

Ads make the world go around. Help us out!

Labels: , , , , , , , , , ,