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!

Proteins are FUN!

(yes, now you can even help by playing a GAME.)

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

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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.

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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.


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2007 week 01: Articles in Proteins

ENTIRE CATALOG OF FERRET PROTEINS TO DATE


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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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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