A conservation and rigidity based method for detecting critical protein residues

Background

Certain amino acids in proteins play a critical role in determining their structural stability and function. Examples include flexible regions such as hinges which allow domain motion, and highly conserved residues on functional interfaces which allow interactions with other proteins. Detecting these regions can aid in the analysis and simulation of protein rigidity and conformational changes, and helps characterizing protein binding and docking. We present an analysis of critical residues in proteins using a combination of two complementary techniques. One method performs in-silico mutations and analyzes the protein's rigidity to infer the role of a point substitution to Glycine or Alanine. The other method uses evolutionary conservation to find functional interfaces in proteins.

Results

We applied the two methods to a dataset of proteins, including biomolecules with experimentally known critical residues as determined by the free energy of unfolding. Our results show that the combination of the two methods can detect the vast majority of critical residues in tested proteins.

Conclusions

Our results show that the combination of the two methods has the potential to detect more information than each method separately. Future work will provide a confidence level for the criticalness of a residue to improve the accuracy of our method and eliminate false positives. Once the combined methods are integrated into one scoring function, it can be applied to other domains such as estimating functional interfaces.

     

A conservation and biophysics guided stochastic approach to refining docked multimeric proteins

Background

We introduce a protein docking refinement method that accepts complexes consisting of any number of monomeric units. The method uses a scoring function based on a tight coupling between evolutionary conservation, geometry and physico-chemical interactions. Understanding the role of protein complexes in the basic biology of organisms heavily relies on the detection of protein complexes and their structures. Different computational docking methods are developed for this purpose, however, these methods are often not accurate and their results need to be further refined to improve the geometry and the energy of the resulting complexes. Also, despite the fact that complexes in nature often have more than two monomers, most docking methods focus on dimers since the computational complexity increases exponentially due to the addition of monomeric units.

Results

Our results show that the refinement scheme can efficiently handle complexes with more than two monomers by biasing the results towards complexes with native interactions, filtering out false positive results. Our refined complexes have better IRMSDs with respect to the known complexes and lower energies than those initial docked structures.

Conclusions

Evolutionary conservation information allows us to bias our results towards possible functional interfaces, and the probabilistic selection scheme helps us to escape local energy minima. We aim to incorporate our refinement method in a larger framework which also enables docking of multimeric complexes given only monomeric structures.

     

Combining bulk segregation analysis and microarrays for mapping of the pH trait in melon

The availability of sequence information for many plants has opened the way to advanced genetic analysis in many non-model plants. Nevertheless, exploration of genetic variation on a large scale and its use as a tool for the identification of traits of interest are still rare. In this study, we combined a bulk segregation approach with our own-designed microarrays to map the pH locus that influences fruit pH in melon. Using these technologies, we identified a set of markers that are genetically linked to the pH trait. Further analysis using a set of melon cultivars demonstrated that some of these markers are tightly linked to the pH trait throughout our germplasm collection. These results validate the utility of combining microarray technology with a bulk segregation approach in mapping traits of interest in non-model plants.     

Organization of repetitive DNAs and the genomic regions carrying ribosomal RNA,<Emphasis Type="Italic"> cob</Emphasis>, and<Emphasis Type="Italic"> atp9</Emphasis> genes in the cucurbit mitochondrial genomes

Plants in the genus Cucumis (cucumber and melon) have the largest mitochondrial genomes known among all plants, due in part to the accumulation of repetitive DNAs of varying complexities. Recombination among these repetitive DNAs should produce highly rearranged mitochondrial genomes relative to the smaller mitochondrial genomes of related plants. We cloned and sequenced mitochondrial genomic regions near the rRNA, atp9 and cob genes from cucumber, melon, squash and watermelon (all members of the Cucurbitaceae family), and compared to the previously sequenced mitochondrial genomes of Arabidopsis thaliana and sugar beet to study the distribution and arrangement of coding and repetitive DNAs. Cucumber and melon had regions of concentrated repetitive DNAs spread throughout the sequenced regions; few repetitive DNAs were revealed in the mitochondrial genomes of A. thaliana, sugar beet, squash and watermelon. Recombination among these repetitive DNAs most likely produced unique arrangements of the rrn18 and rrn5 genes in the genus Cucumis. Cucumber mitochondrial DNA had more pockets of dispersed direct and inverted repeats than melon and the other plants, and we did not reveal repetitive sequences significantly contributing to mitochondrial genome expansion in both cucumber and melon.Disclaimer. Names are necessary to report factually on available data; however, the U.S. Department of Agriculture (USDA) neither guarantees nor warrants the standard of the product, and the use of the name by USDA implies no approval of the product to the exclusion of others that may also be suitable.Communicated by R. Hagemann     

Side chain interactions determine the amyloid organization: a single layer beta-sheet molecular structure of the calcitonin peptide segment 15-19

In this paper we present a detailed atomic model for a protofilament, the most basic organization level, of the amyloid fibre formed by the peptide DFNKF. This pentapeptide is a segment derived from the human calcitonin, a natural amyloidogenic protein. Our model, which represents the outcome of extensive explicit solvent molecular dynamics (MD) simulations of different strand/sheet organizations, is a single beta-sheet filament largely without a hydrophobic core. Nevertheless, this structure is capable of reproducing the main features of the characteristic amyloid fibril organization and provides clues to the molecular basis of its experimental aggregation behaviour. Our results show that the side chains' chemical diversity induces the formation of a complex network of interactions that finally determine the microscopic arrangement of the strands at the protofilament level. This network of interactions, consisting of both side chain-side chain and backbone-side chain interactions, confers on the final single beta-sheet arrangement an unexpected stability, both by enhancing the association of related chemical groups and, at the same time, by shielding the hydrophobic segments from the polar solvent. The chemical physical characterization of this protofilament provides hints to the possible thermodynamical basis of the supra molecular organization that allows the formation of the filaments by lateral association of the preformed protofibrils. Its regular, highly polarized structure shows how other protofilaments can assemble. In terms of structural biology, our results clearly indicate that an amyloid organization implies a degree of complexity far beyond a simple nonspecific association of peptide strands via amide hydrogen bonds.     

Expression of mRNA of lipoprotein receptor related protein 8, low density lipoprotein receptor, and very low density lipoprotein receptor in bovine ovarian cells during follicular development and corpus luteum formation and regression

Lipoproteins in the plasma are the major source of cholesterol obtained by the ovarian theca and granulosa cells for steroidogenesis. In this study, we have identified mRNA expression in bovine theca and granulosa cells of two lipoprotein receptors, low density lipoprotein receptor (LDLr) and very low density lipoprotein receptor (VLDLr) in granulosa cells from small antral follicles through preovulatory follicles and in theca cells from large and medium sized antral follicles. In the corpus luteum (CL) both these receptors were found in the developing and differentiating stages whereas only mRNA for VLDLr was detected in the regression stage. This study also described for the first time, the presence of lipoprotein receptor related protein (LRP8) in granulosa cells from small antral follicles through preovulatory follicles and in theca cells from large and medium sized antral follicles. This may indicate a role of LRP8 in cholesterol delivery to steriodogenic cells. LRP8 was not detected in any of the CL stages. The roles of the LDLr superfamily in lipid transport to ovarian cells and its participation in follicular and CL development and regression is discussed.     

Reducing the computational complexity of protein folding via fragment folding and assembly

Understanding, and ultimately predicting, how a 1-D protein chain reaches its native 3-D fold has been one of the most challenging problems during the last few decades. Data increasingly indicate that protein folding is a hierarchical process. Hence, the question arises as to whether we can use the hierarchical concept to reduce the practically intractable computational times. For such a scheme to work, the first step is to cut the protein sequence into fragments that form local minima on the polypeptide chain. The conformations of such fragments in solution are likely to be similar to those when the fragments are embedded in the native fold, although alternate conformations may be favored during the mutual stabilization in the combinatorial assembly process. Two elements are needed for such cutting: (1) a library of (clustered) fragments derived from known protein structures and (2) an assignment algorithm that selects optimal combinations to "cover" the protein sequence. The next two steps in hierarchical folding schemes, not addressed here, are the combinatorial assembly of the fragments and finally, optimization of the obtained conformations. Here, we address the first step in a hierarchical protein-folding scheme. The input is a target protein sequence and a library of fragments created by clustering building blocks that were generated by cutting all protein structures. The output is a set of cutout fragments. We briefly outline a graph theoretic algorithm that automatically assigns building blocks to the target sequence, and we describe a sample of the results we have obtained.