Mutagenicity, carcinogenicity, and other end points.

Aiming at understanding the structural and physical chemical basis of the biological activity of chemicals, the science of structure-activity relationships has seen dramatic progress in the last decades. Coarse-grain, qualitative approaches (e.g., the structural alerts), and fine-tuned quantitative structure-activity relationship models have been developed and used to predict the toxicological properties of untested chemicals. More recently, a number of approaches and concepts have been developed as support to, and corollary of, the structure-activity methods. These approaches (e.g., chemical relational databases, expert systems, software tools for manipulating the chemical information) have dramatically expanded the reach of the structure-activity work; at present, they are powerful and inescapable tools for computer chemists, toxicologists, and regulators. This chapter, after a general overview of traditional and well-known approaches, gives a detailed presentation of the latter more recent support tools freely available in the public domain.

Assessment and validation of US EPA's OncoLogic® expert system and analysis of its modulating factors for structural alerts.

OncoLogic® is a software program able to screen chemical compounds for toxicological effects. The software predicts the potential carcinogenicity of chemicals by applying rules of structure activity relationship (SAR) analysis. To validate the predictivity of OncoLogic® (Version 7.0), 123 compounds tested with the long-term carcinogenicity bioassay on rodents were extracted from the ISSCAN database and were analyzed. The concordance between the OncoLogic® SAR analysis and the bioassay results was high. To better understand the strength of the SAR science in OncoLogic®, we investigated the influence of a select group of modulating factors on the predictions by the structural alerts.

Microsatellite instability as a marker of prognosis and response to therapy: a meta-analysis of colorectal cancer survival data.

BACKGROUND AND METHODS: We have reviewed and pooled data from published studies to evaluate the relationship between microsatellite instability (MSI) and colorectal cancer (CRC) prognosis. Thirty-one eligible studies reporting survival in 12782 patients characterised for MSI were pooled using a fixed- or random-effects model. RESULTS: The summary odds ratio (OR) estimate for overall survival (OS) associated with MSI was 0.6 (95%CI 0.53-0.69, p<0.0001), with no evidence of heterogeneity. The effect was similar for disease-free survival (DFS) (OR=0.58, 95%CI 0.47-0.72, p<0.0001). In a subset of patients treated with 5-fluorouracil (5-FU)-based chemotherapy a significant improved prognosis was found for microsatellite stable (MSS) tumours (OR=0.52, 95%CI 0.4-0.6, p<0.0001) with no heterogeneity (p=0.53; I(2)=0%). By contrast a large heterogeneity characterised the data relative to 396 patients with MSI tumours (OR=0.69, 95%CI 0.3-1.5, p=0.1; heterogeneity: p=0.03; I(2)=58%). CONCLUSIONS: This study confirmed the association between MSI and favourable prognosis as determined by both OS and DFS of CRC patients. A significant beneficial effect of 5-FU therapy was found for MSS tumours whilst no clear conclusion was reached for MSI tumours due to the high inter-study heterogeneity. We propose that this inconclusive result is due to the use of a single marker, such as MSI, that cannot account alone for the complexity of the mechanisms underlying 5-FU cytotoxicity. Future studies to predict response to 5-FU chemotherapy should include additional genome stability markers.

Hydrophobicity patterns and biological adaptation: an exemplary case from fish hemoglobins.

The dissection of phylogenetic and environmental components in biological evolution is one of the main themes of general biology. Here we propose an approach to this theme relying upon the comparison between a phylogenetic oriented metrics spanning the hemoglobin beta chains of different fishes and a more physiologically oriented metrics defining the same sequences in terms of the dynamical features of their hydrophobic distributions. By analyzing the set of sequences more similar to the Gadus morhua (Atlantic cod) hemoglobin beta chain, we were able to give a proof of concept of the possibility to discriminate the phylogenetic and environmental (evolutive convergence) components by the comparative analysis of the Clustal W (phylogenetics first) and Recurrence Quantification Analysis (physiology first) metrics in which the sequences were embedded. The use of a molecular system like hemoglobin playing a crucial role in fishes adaptation to environmental cues allowed us to span different levels of biological variability by means of the same paradigm. Starting from the reconstruction of the general taxonomy of vertebrate groups we went down to the exploitation of the peculiar role played by Met55Val and Lys62Ala polymorphisms in the beta1 hemoglobin chain of the Atlantic cod able to influence the geographical distribution of its various stocks.

Haemoglobin polymorphisms affect the oxygen-binding properties in Atlantic cod populations.

A major challenge in evolutionary biology is to identify the genes underlying adaptation. The oxygen-transporting haemoglobins directly link external conditions with metabolic needs and therefore represent a unique system for studying environmental effects on molecular evolution. We have discovered two haemoglobin polymorphisms in Atlantic cod populations inhabiting varying temperature and oxygen regimes in the North Atlantic. Three-dimensional modelling of the tetrameric haemoglobin structure demonstrated that the two amino acid replacements Met55beta1Val and Lys62beta1Ala are located at crucial positions of the alpha1beta1 subunit interface and haem pocket, respectively. The replacements are proposed to affect the oxygen-binding properties by modifying the haemoglobin quaternary structure and electrostatic feature. Intriguingly, the same molecular mechanism for facilitating oxygen binding is found in avian species adapted to high altitudes, illustrating convergent evolution in water- and air-breathing vertebrates to reduction in environmental oxygen availability. Cod populations inhabiting the cold Arctic waters and the low-oxygen Baltic Sea seem well adapted to these conditions by possessing the high oxygen affinity Val55-Ala62 haplotype, while the temperature-insensitive Met55-Lys62 haplotype predominates in the southern populations. The distinct distributions of the functionally different haemoglobin variants indicate that the present biogeography of this ecologically and economically important species might be seriously affected by global warming.

Dissecting drug and vehicle metabolic effects in rats by a metabonomic approach.

A combined application of high resolution (1)H NMR spectroscopy and multivariate statistical techniques focused on establishing a consistent statistical approach to metabonomic studies was tested. The data reduction, which is preliminary to the application of multivariate analysis to NMR spectra, was carried out by means of two complementary methods: pure Pattern Recognition (PR) and Assigned Signal Analysis (ASA). The simultaneous use of both approaches allowed us to obtain additional information in the analysis of metabonomic data, compared to the use of PR alone. This additional information consists in the possibility of a biochemical interpretation of the effects induced by treatment with xenobiotics, such as drugs or drug vehicles, on the metabolic networks of the systems under investigation. This approach allowed us to ascertain that a single-dose treatment with ST1959 vehicled by Sesame oil affects the production of hepatic glucose associated to an increment of the amino acid ketogenic process.

Entropic criteria for protein folding derived from recurrences: six residues patch as the basic protein word.

Some research has suggested that patches of six constitute an important amino acid window length in proteins for conveying information. We present database evidence that supports this conjecture, as well as additional recurrence-based data that characterization and quantification of these words affect the folding/aggregation features of proteins. Other indirect evidence is presented and discussed.

Simulated point mutations in the Aalpha-chain of human fibrinogen support a role of the alphaC domain in the stabilization of fibrin gel.

The hydrophobicity pattern distribution in the Aalpha-, Bbeta- and gamma-chains of human fibrinogen has been studied by a nonlinear method, recurrence quantification analysis, in the wild type and in a number of naturally occurring or simulated mutants. The aim was to find a structural basis for distinguishing between silent and pathological mutants. We were successful in the case of mutations on the Aalpha-chain, thanks to the peculiar features of this chain as compared to the other two. Relevant findings concerning the point mutants of the Aalpha-chain are the following: (a) the recurrence quantification analysis-based classification of such mutants is in good agreement with the clinical classification, and (b) the location of the mutated residue on the sequence plays a more relevant role than its hydrophobic features. Artificial point mutants in the terminal zone (600-866 residues) of the extended isoform of the Aalpha-chain cluster together with the natural hemorrhagic mutants of the first (1-207) residues.

Structure-related statistical singularities along protein sequences: a correlation study.

A data set composed of 1141 proteins representative of all eukaryotic protein sequences in the Swiss-Prot Protein Knowledge base was coded by seven physicochemical properties of amino acid residues. The resulting numerical profiles were submitted to correlation analysis after the application of a linear (simple mean) and a nonlinear (Recurrence Quantification Analysis, RQA) filter. The main RQA variables, Recurrence and Determinism, were subsequently analyzed by Principal Component Analysis. The RQA descriptors showed that (i) within protein sequences is embedded specific information neither present in the codes nor in the amino acid composition and (ii) the most sensitive code for detecting ordered recurrent (deterministic) patterns of residues in protein sequences is the Miyazawa-Jernigan hydrophobicity scale. The most deterministic proteins in terms of autocorrelation properties of primary structures were found (i) to be involved in protein-protein and protein-DNA interactions and (ii) to display a significantly higher proportion of structural disorder with respect to the average data set. A study of the scaling behavior of the average determinism with the setting parameters of RQA (embedding dimension and radius) allows for the identification of patterns of minimal length (six residues) as possible markers of zones specifically prone to inter- and intramolecular interactions.

Charge and hydrophobicity patterning along the sequence predicts the folding mechanism and aggregation of proteins: a computational approach.

The presence of partially folded intermediates along the folding funnel of proteins has been suggested to be a signature of potentially aggregating systems. Many studies have concluded that metastable, highly flexible intermediates are the basic elements of the aggregation process. In a previous paper, we demonstrated how the choice between aggregation and folding behavior was influenced by hydrophobicity distribution patterning along the sequence, as quantified by recurrence quantification analysis (RQA) of the Myiazawa-Jernigan coded primary structures. In the present paper, we tried to unify the "partially folded intermediate" and "hydrophobicity/charge" models of protein aggregation verifying the ability of an empirical relation, developed for rationalizing the effect of different mutations on aggregation propensity of acyl-phosphatase and based on the combination of hydrophobicity RQA and charge descriptors, to discriminate in a statistically significant way two different protein populations: (a) proteins that fold by a process passing by partially folded intermediates and (b) proteins that do not present partially folded intermediates.

Protein aggregation/folding: the role of deterministic singularities of sequence hydrophobicity as determined by nonlinear signal analysis of acylphosphatase and Abeta(1-40).

The problem of protein folding vs. aggregation was investigated in acylphosphatase and the amyloid protein Abeta(1-40) by means of nonlinear signal analysis of their chain hydrophobicity. Numerical descriptors of recurrence patterns provided the basis for statistical evaluation of folding/aggregation distinctive features. Static and dynamic approaches were used to elucidate conditions coincident with folding vs. aggregation using comparisons with known protein secondary structure classifications, site-directed mutagenesis studies of acylphosphatase, and molecular dynamics simulations of amyloid protein, Abeta(1-40). The results suggest that a feature derived from principal component space characterized by the smoothness of singular, deterministic hydrophobicity patches plays a significant role in the conditions governing protein aggregation.

Large contact surface interactions between proteins detected by time series analysis methods: case study on C-phycocyanins.

A purely sequence-dependent approach to the modeling of protein-protein interaction was applied to the study of C-phycocyanin alphabeta dimers. The interacting pairs (alpha and beta subunits) share an almost complete structural homology, together with a general lack of sequence superposition; thus, they constitute a particularly relevant example for protein-protein interaction prediction. The present analysis is based on a description posited at an intermediate level between sequence and structure, that is, the hydrophobicity patterning along the chains. Based on the description of the sequence hydrophobicity patterns through a battery of nonlinear tools (recurrence quantification analysis and other sequence complexity descriptors), we were able to generate an explicit equation modeling alpha and beta monomers interaction; the model consisted of canonical correlation between the hydrophobicity autocorrelation structures of the interacting pairs. The general implications of this holistic approach to the modeling of protein-protein interactions, which considers the protein primary structures as a whole, are discussed.