Get Phases from Arsenic Anomalous Scattering: de novo SAD Phasing of Two Protein Structures Crystallized in Cacodylate Buffer

The crystal structures of two proteins, a putative pyrazinamidase/nicotinamidase from the dental pathogen Streptococcus mutans (SmPncA) and the human caspase-6 (Casp6), were solved by de novo arsenic single-wavelength anomalous diffraction (As-SAD) phasing method. Arsenic (As), an uncommonly used element in SAD phasing, was covalently introduced into proteins by cacodylic acid, the buffering agent in the crystallization reservoirs. In SmPncA, the only cysteine was bound to dimethylarsinoyl, which is a pentavalent arsenic group (As (V)). This arsenic atom and a protein-bound zinc atom both generated anomalous signals. The predominant contribution, however, was from the As anomalous signals, which were sufficient to phase the SmPncA structure alone. In Casp6, four cysteines were found to bind cacodyl, a trivalent arsenic group (As (III)), in the presence of the reducing agent, dithiothreitol (DTT), and arsenic atoms were the only anomalous scatterers for SAD phasing. Analyses and discussion of these two As-SAD phasing examples and comparison of As with other traditional heavy atoms that generate anomalous signals, together with a few arsenic-based de novo phasing cases reported previously strongly suggest that As is an ideal anomalous scatterer for SAD phasing in protein crystallography

Mutagenesis Objective Search and Selection Tool (MOSST): an algorithm to predict structure-function related mutations in proteins

<p>Abstract</p> <p>Background</p> <p>Functionally relevant artificial or natural mutations are difficult to assess or predict if no structure-function information is available for a protein. This is especially important to correctly identify functionally significant non-synonymous single nucleotide polymorphisms (nsSNPs) or to design a site-directed mutagenesis strategy for a target protein. A new and powerful methodology is proposed to guide these two decision strategies, based only on conservation rules of physicochemical properties of amino acids extracted from a multiple alignment of a protein family where the target protein belongs, with no need of explicit structure-function relationships.</p> <p>Results</p> <p>A statistical analysis is performed over each amino acid position in the multiple protein alignment, based on different amino acid physical or chemical characteristics, including hydrophobicity, side-chain volume, charge and protein conformational parameters. The variances of each of these properties at each position are combined to obtain a global statistical indicator of the conservation degree of each property. Different types of physicochemical conservation are defined to characterize relevant and irrelevant positions. The differences between statistical variances are taken together as the basis of hypothesis tests at each position to search for functionally significant mutable sites and to identify specific mutagenesis targets. The outcome is used to statistically predict physicochemical consensus sequences based on different properties and to calculate the amino acid propensities at each position in a given protein. Hence, amino acid positions are identified that are putatively responsible for function, specificity, stability or binding interactions in a family of proteins. Once these key functional positions are identified, position-specific statistical distributions are applied to divide the 20 common protein amino acids in each position of the protein's primary sequence into a group of functionally non-disruptive amino acids and a second group of functionally deleterious amino acids.</p> <p>Conclusions</p> <p>With this approach, not only conserved amino acid positions in a protein family can be labeled as functionally relevant, but also non-conserved amino acid positions can be identified to have a physicochemically meaningful functional effect. These results become a discriminative tool in the selection and elaboration of rational mutagenesis strategies for the protein. They can also be used to predict if a given nsSNP, identified, for instance, in a genomic-scale analysis, can have a functional implication for a particular protein and which nsSNPs are most likely to be functionally silent for a protein. This analytical tool could be used to rapidly and automatically discard any irrelevant nsSNP and guide the research focus toward functionally significant mutations. Based on preliminary results and applications, this technique shows promising performance as a valuable bioinformatics tool to aid in the development of new protein variants and in the understanding of function-structure relationships in proteins.</p

Flexible mapping of homology onto structure with Homolmapper

<p>Abstract</p> <p>Background</p> <p>Over the past decade, a number of tools have emerged for the examination of homology relationships among protein sequences in a structural context. Most recent software implementations for such analysis are tied to specific molecular viewing programs, which can be problematic for collaborations involving multiple viewing environments. Incorporation into larger packages also adds complications for users interested in adding their own scoring schemes or in analyzing proteins incorporating unusual amino acid residues such as selenocysteine.</p> <p>Results</p> <p>We describe homolmapper, a command-line application for mapping information from a multiple protein sequence alignment onto a protein structure for analysis in the viewing software of the user's choice. Homolmapper is small (under 250 K for the application itself) and is written in Python to ensure portability. It is released for non-commercial use under a modified University of California BSD license. Homolmapper permits facile import of additional scoring schemes and can incorporate arbitrary additional amino acids to allow handling of residues such as selenocysteine or pyrrolysine. Homolmapper also provides tools for defining and analyzing subfamilies relative to a larger alignment, for mutual information analysis, and for rapidly visualizing the locations of mutations and multi-residue motifs.</p> <p>Conclusion</p> <p>Homolmapper is a useful tool for analysis of homology relationships among proteins in a structural context. There is also extensive, example-driven documentation available. More information about homolmapper is available at <url>http://www.mcb.ucdavis.edu/faculty-labs/lagarias/homolmapper_home/homolmapper%20web%20page.htm</url>.</p

Statistical and functional analyses of viral and cellular proteins with N-terminal amphipathic alpha-helices with large hydrophobic moments: importance to macromolecular recognition and organelle targeting.

A total of 1,911 proteins with N-terminal methionyl residues were computer screened for potential N-terminal alpha-helices with strong amphipathic character. By the criteria of D. Eisenberg (Annu. Rev. Biochem. 53:595-623, 1984), only 3.5% of nonplastid, nonviral proteins exhibited potential N-terminal alpha-helices, 18 residues in length, with hydrophobic moment values per amino acyl residue ([muH]) in excess of 0.4. By contrast, 10% of viral proteins exhibited corresponding [muH] values in excess of 0.4. Of these viral proteins with known functions, 55% were found to interact functionally with nucleic acids, 30% were membrane-interacting proteins or their precursors, and 15% were structural proteins, primarily concerned with host cell interactions. These observations suggest that N-terminal amphipathic alpha-helices of viral proteins may (i) function in nucleic acid binding, (ii) facilitate membrane insertion, and (iii) promote host cell interactions. Analyses of potential amphipathic N-terminal alpha-helices of cellular proteins are also reported, and their significance to organellar or envelope targeting is discussed