Web-based toolkits for topology prediction of transmembrane helical proteins, fold recognition, structure and binding scoring, folding-kinetics analysis and comparative analysis of domain combinations

HINT, a code for understanding the interaction between biomolecules: a tribute to Donald J. Abraham

A long-lasting goal of computational biochemists, medicinal chemists, and structural biologists has been the development of tools capable of deciphering the molecule-molecule interaction code that produces a rich variety of complex biomolecular assemblies comprised of the many different simple and biological molecules of life: water, small metabolites, cofactors, substrates, proteins, DNAs, and RNAs. Software applications that can mimic the interactions amongst all of these species, taking account of the laws of thermodynamics, would help gain information for understanding qualitatively and quantitatively key determinants contributing to the energetics of the bimolecular recognition process. This, in turn, would allow the design of novel compounds that might bind at the intermolecular interface by either preventing or reinforcing the recognition. HINT, hydropathic interaction, was a model and software code developed from a deceptively simple idea of Donald Abraham with the close collaboration with Glen Kellogg at Virginia Commonwealth University. HINT is based on a function that scores atom-atom interaction using LogP, the partition coefficient of any molecule between two phases; here, the solvents are water that mimics the cytoplasm milieu and octanol that mimics the protein internal hydropathic environment. This review summarizes the results of the extensive and successful collaboration between Abraham and Kellogg at VCU and the group at the University of Parma for testing HINT in a variety of different biomolecular interactions, from proteins with ligands to proteins with DNA.

Misfolding of galactose 1-phosphate uridylyltransferase can result in type I galactosemia

Type I galactosemia is a genetic disorder that is caused by the impairment of galactose-1-phosphate uridylyltransferase (GALT; EC 2.7.7.12). Although a large number of mutations have been detected through genetic screening of the human GALT (hGALT) locus, for many it is not known how they cause their effects. The majority of these mutations are missense, with predicted substitutions scattered throughout the enzyme structure and thus causing impairment by other means rather than direct alterations to the active site. To clarify the fundamental, molecular basis of hGALT impairment we studied five disease-associated variants p.D28Y, p.L74P, p.F171S, p.F194L and p.R333G using both a yeast model and purified, recombinant proteins. In a yeast expression system there was a correlation between lysate activity and the ability to rescue growth in the presence of galactose, except for p.R333G. Kinetic analysis of the purified proteins quantified each variant's level of enzymatic impairment and demonstrated that this was largely due to altered substrate binding. Increased surface hydrophobicity, altered thermal stability and changes in proteolytic sensitivity were also detected. Our results demonstrate that hGALT requires a level of flexibility to function optimally and that altered folding is the underlying reason of impairment in all the variants tested here. This indicates that misfolding is a common, molecular basis of hGALT deficiency and suggests the potential of pharmacological chaperones and proteostasis regulators as novel therapeutic approaches for type I galactosemia.

Stabilizing proteins from sequence statistics: the interplay of conservation and correlation in triosephosphate isomerase stability

Understanding the determinants of protein stability remains one of protein science's greatest challenges. There are still no computational solutions that calculate the stability effects of even point mutations with sufficient reliability for practical use. Amino acid substitutions rarely increase the stability of native proteins; hence, large libraries and high-throughput screens or selections are needed to stabilize proteins using directed evolution. Consensus mutations have proven effective for increasing stability, but these mutations are successful only about half the time. We set out to understand why some consensus mutations fail to stabilize, and what criteria might be useful to predict stabilization more accurately. Overall, consensus mutations at more conserved positions were more likely to be stabilizing in our model, triosephosphate isomerase (TIM) from Saccharomyces cerevisiae. However, positions coupled to other sites were more likely not to stabilize upon mutation. Destabilizing mutations could be removed both by removing sites with high statistical correlations to other positions and by removing nearly invariant positions at which "hidden correlations" can occur. Application of these rules resulted in identification of stabilizing mutations in 9 out of 10 positions, and amalgamation of all predicted stabilizing positions resulted in the most stable yeast TIM variant we produced (+8 °C). In contrast, a multimutant with 14 mutations each found to stabilize TIM independently was destabilized by 2 °C. Our results are a practical extension to the consensus concept of protein stabilization, and they further suggest the importance of positional independence in the mechanism of consensus stabilization.

STRUCTURE PREDICTION OF HELICAL TRANSMEMBRANE PROTEINS AT TWO LENGTH SCALES

As the first step toward a multi-scale, hierarchical computational approach for membrane protein structure prediction, the packing of transmembrane helices was modeled at the residue and atom levels, respectively. For predictions at the residue level, the helix-helix and helix-membrane interactions were described by a set of knowledge-based energy functions. For predictions at the atom level, CHARMM19 force field was used. To facilitate the system to overcome energy barriers, the Wang–Landau method was employed, where a random walk is performed in the energy space with a uniform probability. Native-like structures were predicted at both levels for two model systems, each of which consists of two transmembrane helices. Interestingly, consistent results were obtained from simulations at the residue and atom levels for the same system, strongly suggesting the feasibility of a hierarchical approach for membrane protein structure predictions.

Vaccinia virus virulence factor N1L is a novel promising target for antiviral therapeutic intervention

The 14 kDa homodimeric N1L protein is a potent vaccinia and variola (smallpox) virulence factor. It is not essential for viral replication, but it causes a strong attenuation of viral production in culture when deleted. The N1L protein is predicted to contain the BH3-like binding domain characteristic of Bcl-2 family proteins, and it is able to bind the BH3 peptides. Its overexpression has been reported to prevent infected cells from committing apoptosis. Therefore, interfering with the N1L apoptotic blockade may be a legitimate therapeutic strategy affecting the viral growth. By using in silico ligand docking and an array of in vitro assays, we have identified submicromolar (600 nM) N1L antagonists belonging to the family of polyphenols. Their affinity is comparable to that of the BH3 peptides (70-1000 nM). We have also identified the natural polyphenol resveratrol as a moderate N1L inhibitor. Finally, we show that our ligands efficiently inhibit growth of vaccinia virus.

CoBaltDB: Complete bacterial and archaeal orfeomes subcellular localization database and associated resources

BACKGROUND

The functions of proteins are strongly related to their localization in cell compartments (for example the cytoplasm or membranes) but the experimental determination of the sub-cellular localization of proteomes is laborious and expensive. A fast and low-cost alternative approach is in silico prediction, based on features of the protein primary sequences. However, biologists are confronted with a very large number of computational tools that use different methods that address various localization features with diverse specificities and sensitivities. As a result, exploiting these computer resources to predict protein localization accurately involves querying all tools and comparing every prediction output; this is a painstaking task. Therefore, we developed a comprehensive database, called CoBaltDB, that gathers all prediction outputs concerning complete prokaryotic proteomes.

DESCRIPTION

The current version of CoBaltDB integrates the results of 43 localization predictors for 784 complete bacterial and archaeal proteomes (2.548.292 proteins in total). CoBaltDB supplies a simple user-friendly interface for retrieving and exploring relevant information about predicted features (such as signal peptide cleavage sites and transmembrane segments). Data are organized into three work-sets ("specialized tools", "meta-tools" and "additional tools"). The database can be queried using the organism name, a locus tag or a list of locus tags and may be browsed using numerous graphical and text displays.

CONCLUSIONS

With its new functionalities, CoBaltDB is a novel powerful platform that provides easy access to the results of multiple localization tools and support for predicting prokaryotic protein localizations with higher confidence than previously possible. CoBaltDB is available at http://www.umr6026.univ-rennes1.fr/english/home/research/basic/software/cobalten.

Fast predictions of thermodynamics and kinetics of protein-protein recognition from structures: from molecular design to systems biology

The increasing call for an overall picture of the interactions between the components of a biological system that give rise to the observed function is often summarized by the expression systems biology. Both the interpretative and predictive capabilities of holistic models of biochemical systems, however, depend to a large extent on the level of physico-chemical knowledge of the individual molecular interactions making up the network. This review is focused on the structure-based quantitative characterization of protein-protein interactions, ubiquitous in any biochemical pathway. Recently developed, fast and effective computational methods are reviewed, which allow the assessment of kinetic and thermodynamic features of the association-dissociation processes of protein complexes, both in water soluble and membrane environments. The performance and the accuracy of fast and semi-empirical structure-based methods have reached comparable levels with respect to the classical and more elegant molecular simulations. Nevertheless, the broad accessibility and lower computational cost provide the former methods with the advantageous possibility to perform systems-level analyses including extensive in silico mutagenesis screenings and large-scale structural predictions of multiprotein complexes.

Vaccinia virus N1L protein resembles a B cell lymphoma-2 (Bcl-2) family protein

Poxviruses encode immuno-modulatory proteins capable of subverting host defenses. The poxvirus vaccinia expresses a small 14-kDa protein, N1L, that is critical for virulence. We report the crystal structure of N1L, which reveals an unexpected but striking resemblance to host apoptotic regulators of the B cell lymphoma-2 (Bcl-2) family. Although N1L lacks detectable Bcl-2 homology (BH) motifs at the sequence level, we show that N1L binds with high affinity to the BH3 peptides of pro-apoptotic Bcl-2 family proteins in vitro, consistent with a role for N1L in modulating host antiviral defenses.

Plant proteome analysis: A 2004–2006 update

Since the appearance of the review entitled "Plant Proteome Analysis" in Proteomics in February 2004 (Cánovas, F. M., Dumas-Gaudot, E., Recorbert, G., Jorrín, J. et al., Proteomics 2004, 4, 285-298), about 200 original articles focusing on plant proteomics have been published. Although this represents less than 1% of the global proteomics output during this period, it nevertheless reflects an increase in activity over the period 1999-2004. These papers concern the proteome of at least 35 plant species but have concentrated mainly on thale cress (Arabidopsis thaliana) and rice (Oryza sativa). The scientific objectives have ranged from a proteomic analysis of organs, tissues, cell suspensions, or subcellular fractions to the study of plant development and response to various stresses. A number of contributions have covered PTMs and protein interactions. The dominant analytical platform has been 2-DE coupled to MS, but "second generation" techniques such as DIGE, multidimensional protein identification technology, isotope-coded affinity tags, and stable isotope labeling by amino acids in cell culture have begun to make an impact. This review aims to provide an update of the contribution of proteomics to plant biology during the period 2004-2006, and is divided into six sections: introduction, subcellular proteomes, plant development, responses to biotic and abiotic stresses, PTMs, and protein interactions. The conclusions summarize a view of the major pitfalls and challenges of plant proteomics.

Structural analysis of Siah1-Siah-interacting protein interactions and insights into the assembly of an E3 ligase multiprotein complex

Siah1 is the central component of a multiprotein E3 ubiquitin ligase complex that targets beta-catenin for destruction in response to p53 activation. The E3 complex comprises, in addition to Siah1, Siah-interacting protein (SIP), the adaptor protein Skp1, and the F-box protein Ebi. Here we show that SIP engages Siah1 by means of two elements, both of which are required for mediating beta-catenin destruction in cells. An N-terminal dimerization domain of SIP sits across the saddle-shaped upper surface of Siah1, with two extended legs packing against the sides of Siah1 by means of a consensus PXAXVXP motif that is common to a family of Siah-binding proteins. The C-terminal domain of SIP, which binds to Skp1, protrudes from the lower surface of Siah1, and we propose that this surface provides the scaffold for bringing substrate and the E2 enzyme into apposition in the functional complex.