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.


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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.
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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 Folding

ENTIRE CATALOG OF FERRET PROTEINS TO DATE

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

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

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

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

Exploring zipping and assembly as a protein folding principle

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

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

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

A knowledge-based move set for protein folding

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

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