The underlying pathway structure of biochemical reaction networks

Bioinformatics is yielding extensive, and in some cases complete, genetic and biochemical information about individual cell types and cellular processes, providing the composition of living cells and the molecular structure of its components. These components together perform integrated cellular functions that now need to be analyzed. In particular, the functional definition of biochemical pathways and their role in the context of the whole cell is lacking. In this study, we show how the mass balance constraints that govern the function of biochemical reaction networks lead to the translation of this problem into the realm of linear algebra. The functional capabilities of biochemical reaction networks, and thus the choices that cells can make, are reflected in the null space of their stoichiometric matrix. The null space is spanned by a finite number of basis vectors. We present an algorithm for the synthesis of a set of basis vectors for spanning the null space of the stoichiometric matrix, in which these basis vectors represent the underlying biochemical pathways that are fundamental to the corresponding biochemical reaction network. In other words, all possible flux distributions achievable by a defined set of biochemical reactions are represented by a linear combination of these basis pathways. These basis pathways thus represent the underlying pathway structure of the defined biochemical reaction network. This development is significant from a fundamental and conceptual standpoint because it yields a holistic definition of biochemical pathways in contrast to definitions that have arisen from the historical development of our knowledge about biochemical processes. Additionally, this new conceptual framework will be important in defining, characterizing, and studying biochemical pathways from the rapidly growing information on cellular function.

Crystal structure of the RNA-dependent RNA polymerase of hepatitis C virus

We report the crystal structure of the RNA-dependent RNA polymerase of hepatitis C virus, a major human pathogen, to 2.8-Å resolution. This enzyme is a key target for developing specific antiviral therapy. The structure of the catalytic domain contains 531 residues folded in the characteristic fingers, palm, and thumb subdomains. The fingers subdomain contains a region, the “fingertips,” that shares the same fold with reverse transcriptases. Superposition to the available structures of the latter shows that residues from the palm and fingertips are structurally equivalent. In addition, it shows that the hepatitis C virus polymerase was crystallized in a closed fingers conformation, similar to HIV-1 reverse transcriptase in ternary complex with DNA and dTTP [Huang H., Chopra, R., Verdine, G. L. & Harrison, S. C. (1998) Science 282, 1669–1675]. This superposition reveals the majority of the amino acid residues of the hepatitis C virus enzyme that are likely to be implicated in binding to the replicating RNA molecule and to the incoming NTP. It also suggests a rearrangement of the thumb domain as well as a possible concerted movement of thumb and fingertips during translocation of the RNA template-primer in successive polymerization rounds.

A link between protein structure and enzyme catalyzed hydrogen tunneling

We present evidence that the size of an active site side chain may modulate the degree of hydrogen tunneling in an enzyme-catalyzed reaction. Primary and secondary kH/kT and kD/kT kinetic isotope effects have been measured for the oxidation of benzyl alcohol catalyzed by horse liver alcohol dehydrogenase at 25°C. As reported in earlier studies, the relationship between secondary kH/kT and kD/kT isotope effects provides a sensitive probe for deviations from classical behavior. In the present work, catalytic efficiency and the extent of hydrogen tunneling have been correlated for the alcohol dehydrogenase-catalyzed hydride transfer among a group of site-directed mutants at position 203. Val-203 interacts with the opposite face of the cofactor NAD+ from the alcohol substrate. The reduction in size of this residue is correlated with diminished tunneling and a two orders of magnitude decrease in catalytic efficiency. Comparison of the x-ray crystal structures of a ternary complex of a high-tunneling (Phe-93 → Trp) and a low-tunneling (Val-203 → Ala) mutant provides a structural basis for the observed effects, demonstrating an increase in the hydrogen transfer distance for the low-tunneling mutant. The Val-203 → Ala ternary complex crystal structure also shows a hyperclosed interdomain geometry relative to the wild-type and the Phe-93 → Trp mutant ternary complex structures. This demonstrates a flexibility in interdomain movement that could potentially narrow the distance between the donor and acceptor carbons in the native enzyme and may enhance the role of tunneling in the hydride transfer reaction.

Statistical prediction of single-stranded regions in RNA secondary structure and application to predicting effective antisense target sites and beyond

Single-stranded regions in RNA secondary structure are important for RNA–RNA and RNA–protein interactions. We present a probability profile approach for the prediction of these regions based on a statistical algorithm for sampling RNA secondary structures. For the prediction of phylogenetically-determined single-stranded regions in secondary structures of representative RNA sequences, the probability profile offers substantial improvement over the minimum free energy structure. In designing antisense oligonucleotides, a practical problem is how to select a secondary structure for the target mRNA from the optimal structure(s) and many suboptimal structures with similar free energies. By summarizing the information from a statistical sample of probable secondary structures in a single plot, the probability profile not only presents a solution to this dilemma, but also reveals ‘well-determined’ single-stranded regions through the assignment of probabilities as measures of confidence in predictions. In antisense application to the rabbit β-globin mRNA, a significant correlation between hybridization potential predicted by the probability profile and the degree of inhibition of in vitro translation suggests that the probability profile approach is valuable for the identification of effective antisense target sites. Coupling computational design with DNA–RNA array technique provides a rational, efficient framework for antisense oligonucleotide screening. This framework has the potential for high-throughput applications to functional genomics and drug target validation.

Elongation factor TFIIS contains three structural domains: solution structure of domain II.

Transcription elongation by RNA polymerase II is regulated by the general elongation factor TFIIS. This factor stimulates RNA polymerase II to transcribe through regions of DNA that promote the formation of stalled ternary complexes. Limited proteolytic digestion showed that yeast TFIIS is composed of three structural domains, termed I, II, and III. The two C-terminal domains (II and III) are required for transcription activity. The structure of domain III has been solved previously by using NMR spectroscopy. Here, we report the NMR-derived structure of domain II: a three-helix bundle built around a hydrophobic core composed largely of three tyrosines protruding from one face of the C-terminal helix. The arrangement of known inactivating mutations of TFIIS suggests that two surfaces of domain II are critical for transcription activity.

Structure-activity relationships derived by machine learning: the use of atoms and their bond connectivities to predict mutagenicity by inductive logic programming.

We present a general approach to forming structure-activity relationships (SARs). This approach is based on representing chemical structure by atoms and their bond connectivities in combination with the inductive logic programming (ILP) algorithm PROGOL. Existing SAR methods describe chemical structure by using attributes which are general properties of an object. It is not possible to map chemical structure directly to attribute-based descriptions, as such descriptions have no internal organization. A more natural and general way to describe chemical structure is to use a relational description, where the internal construction of the description maps that of the object described. Our atom and bond connectivities representation is a relational description. ILP algorithms can form SARs with relational descriptions. We have tested the relational approach by investigating the SARs of 230 aromatic and heteroaromatic nitro compounds. These compounds had been split previously into two subsets, 188 compounds that were amenable to regression and 42 that were not. For the 188 compounds, a SAR was found that was as accurate as the best statistical or neural network-generated SARs. The PROGOL SAR has the advantages that it did not need the use of any indicator variables handcrafted by an expert, and the generated rules were easily comprehensible. For the 42 compounds, PROGOL formed a SAR that was significantly (P < 0.025) more accurate than linear regression, quadratic regression, and back-propagation. This SAR is based on an automatically generated structural alert for mutagenicity.

X-ray structure of clotting factor IXa: active site and module structure related to Xase activity and hemophilia B.

Hereditary deficiency of factor IXa (fIXa), a key enzyme in blood coagulation, causes hemophilia B, a severe X chromosome-linked bleeding disorder afflicting 1 in 30,000 males; clinical studies have identified nearly 500 deleterious variants. The x-ray structure of porcine fIXa described here shows the atomic origins of the disease, while the spatial distribution of mutation sites suggests a structural model for factor X activation by phospholipid-bound fIXa and cofactor VIIIa. The 3.0-A-resolution diffraction data clearly show the structures of the serine proteinase module and the two preceding epidermal growth factor (EGF)-like modules; the N-terminal Gla module is partially disordered. The catalytic module, with covalent inhibitor D-Phe-1I-Pro-2I-Arg-3I chloromethyl ketone, most closely resembles fXa but differs significantly at several positions. Particularly noteworthy is the strained conformation of Glu-388, a residue strictly conserved in known fIXa sequences but conserved as Gly among other trypsin-like serine proteinases. Flexibility apparent in electron density together with modeling studies suggests that this may cause incomplete active site formation, even after zymogen, and hence the low catalytic activity of fIXa. The principal axes of the oblong EGF-like domains define an angle of 110 degrees, stabilized by a strictly conserved and fIX-specific interdomain salt bridge. The disorder of the Gla module, whose hydrophobic helix is apparent in electron density, can be attributed to the absence of calcium in the crystals; we have modeled the Gla module in its calcium form by using prothrombin fragment 1. The arched module arrangement agrees with fluorescence energy transfer experiments. Most hemophilic mutation sites of surface fIX residues occur on the concave surface of the bent molecule and suggest a plausible model for the membrane-bound ternary fIXa-FVIIIa-fX complex structure: fIXa and an equivalently arranged fX arch across an underlying fVIIIa subdomain from opposite sides; the stabilizing fVIIIa interactions force the catalytic modules together, completing fIXa active site formation and catalytic enhancement.

Structure of human T-cell receptors specific for an immunodominant myelin basic protein peptide: positioning of T-cell receptors on HLA-DR2/peptide complexes.

T-cell receptors (TCRs) recognize peptide bound within the relatively conserved structural framework of major histocompatibility complex (MHC) class I or class II molecules but can discriminate between closely related MHC molecules. The structural basis for the specificity of ternary complex formation by the TCR and MHC/peptide complexes was examined for myelin basic protein (MBP)-specific T-cell clones restricted by different DR2 subtypes. Conserved features of this system allowed a model for positioning of the TCR on DR2/peptide complexes to be developed: (i) The DR2 subtypes that presented the immunodominant MBP peptide differed only at a few polymorphic positions of the DR beta chain. (ii) TCR recognition of a polymorphic residue on the helical portion of the DR beta chain (position DR beta 67) was important in determining the MHC restriction. (iii) The TCR variable region (V) alpha 3.1 gene segment was used by all of the T-cell clones. TCR V beta usage was more diverse but correlated with the MHC restriction--i.e., with the polymorphic DR beta chains. (iv) Two clones with conserved TCR alpha chains but different TCR beta chains had a different MHC restriction but a similar peptide specificity. The difference in MHC restriction between these T-cell clones appeared due to recognition of a cluster of polymorphic DR beta-chain residues (DR beta 67-71). MBP-(85-99)-specific TCRs therefore appeared to be positioned on the DR2/peptide complex such that the TCR beta chain contacted the polymorphic DR beta-chain helix while the conserved TCR alpha chain contacted the nonpolymorphic DR alpha chain.

GE models and algorithms for condensed phase equilibrium data regression in ternary systems: limitations and proposals

Phase equilibrium data regression is an unavoidable task necessary to obtain the appropriate values for any model to be used in separation equipment design for chemical process simulation and optimization. The accuracy of this process depends on different factors such as the experimental data quality, the selected model and the calculation algorithm. The present paper summarizes the results and conclusions achieved in our research on the capabilities and limitations of the existing GE models and about strategies that can be included in the correlation algorithms to improve the convergence and avoid inconsistencies. The NRTL model has been selected as a representative local composition model. New capabilities of this model, but also several relevant limitations, have been identified and some examples of the application of a modified NRTL equation have been discussed. Furthermore, a regression algorithm has been developed that allows for the advisable simultaneous regression of all the condensed phase equilibrium regions that are present in ternary systems at constant T and P. It includes specific strategies designed to avoid some of the pitfalls frequently found in commercial regression tools for phase equilibrium calculations. Most of the proposed strategies are based on the geometrical interpretation of the lowest common tangent plane equilibrium criterion, which allows an unambiguous comprehension of the behavior of the mixtures. The paper aims to show all the work as a whole in order to reveal the necessary efforts that must be devoted to overcome the difficulties that still exist in the phase equilibrium data regression problem.

Evaluation of pronoun resolution algorithm for Spanish dialogues

In this paper, we present an algorithm for anaphora resolution in Spanish dialogues and an evaluation of the algorithm for pronominal anaphora. The proposed algorithm uses both linguistic information and the structure of the dialogue to find the antecedent of the anaphors. The system has been evaluated on ten dialogues.

Convergence analysis and validation of low cost distance metrics for computational cost reduction of the Iterative Closest Point algorithm

The Iterative Closest Point algorithm (ICP) is commonly used in engineering applications to solve the rigid registration problem of partially overlapped point sets which are pre-aligned with a coarse estimate of their relative positions. This iterative algorithm is applied in many areas such as the medicine for volumetric reconstruction of tomography data, in robotics to reconstruct surfaces or scenes using range sensor information, in industrial systems for quality control of manufactured objects or even in biology to study the structure and folding of proteins. One of the algorithm’s main problems is its high computational complexity (quadratic in the number of points with the non-optimized original variant) in a context where high density point sets, acquired by high resolution scanners, are processed. Many variants have been proposed in the literature whose goal is the performance improvement either by reducing the number of points or the required iterations or even enhancing the complexity of the most expensive phase: the closest neighbor search. In spite of decreasing its complexity, some of the variants tend to have a negative impact on the final registration precision or the convergence domain thus limiting the possible application scenarios. The goal of this work is the improvement of the algorithm’s computational cost so that a wider range of computationally demanding problems from among the ones described before can be addressed. For that purpose, an experimental and mathematical convergence analysis and validation of point-to-point distance metrics has been performed taking into account those distances with lower computational cost than the Euclidean one, which is used as the de facto standard for the algorithm’s implementations in the literature. In that analysis, the functioning of the algorithm in diverse topological spaces, characterized by different metrics, has been studied to check the convergence, efficacy and cost of the method in order to determine the one which offers the best results. Given that the distance calculation represents a significant part of the whole set of computations performed by the algorithm, it is expected that any reduction of that operation affects significantly and positively the overall performance of the method. As a result, a performance improvement has been achieved by the application of those reduced cost metrics whose quality in terms of convergence and error has been analyzed and validated experimentally as comparable with respect to the Euclidean distance using a heterogeneous set of objects, scenarios and initial situations.

A Sequential Algorithm for the Rigorous Design of Thermally Coupled Distillation Sequences

A sequential design method is presented for the design of thermally coupled distillation sequences. The algorithm starts by selecting a set of sequences in the space of basic configurations in which the internal structure of condensers and reboilers is explicitly taken into account and extended with the possibility of including divided wall columns (DWC). This first stage is based on separation tasks (except by the DWCs) and therefore it does not provide an actual sequence of columns. In the second stage the best arrangement in N-1 actual columns is performed taking into account operability and mechanical constraints. Finally, for a set of candidate sequences the algorithm try to reduce the number of total columns by considering Kaibel columns, elimination of transfer blocks or columns with vertical partitions. An example illustrate the different steps of the sequential algorithm.

A Finite Element Numerical Algorithm for Modelling and Data Fitting in Complex Systems

Numerical modelling methodologies are important by their application to engineering and scientific problems, because there are processes where analytical mathematical expressions cannot be obtained to model them. When the only available information is a set of experimental values for the variables that determine the state of the system, the modelling problem is equivalent to determining the hyper-surface that best fits the data. This paper presents a methodology based on the Galerkin formulation of the finite elements method to obtain representations of relationships that are defined a priori, between a set of variables: y = z(x1, x2,...., xd). These representations are generated from the values of the variables in the experimental data. The approximation, piecewise, is an element of a Sobolev space and has derivatives defined in a general sense into this space. The using of this approach results in the need of inverting a linear system with a structure that allows a fast solver algorithm. The algorithm can be used in a variety of fields, being a multidisciplinary tool. The validity of the methodology is studied considering two real applications: a problem in hydrodynamics and a problem of engineering related to fluids, heat and transport in an energy generation plant. Also a test of the predictive capacity of the methodology is performed using a cross-validation method.

Optimization of the Modular Educational Program Structure

Optimized structure of the educational program consisting of a set of the interconnected educational objects is offered by means of problem solution of optimum partition of the acyclic weighed graph. The condition of acyclicity preservation for subgraphs is formulated and the quantitative assessment of decision options is executed. The original algorithm of search of quasioptimum partition using the genetic algorithm scheme with coding chromosomes by permutation is offered. Object-oriented realization of algorithm in language C++ is described and results of numerical experiments are presented.

The Microphysical Structure of Mesoscale Convective Systems

Thesis (Ph.D.)--University of Washington, 2016-05