Computational learning of the conditional phase-type (C-Ph) distribution: Learning C-Ph distributions

This paper presents a new algorithm for learning the structure of a special type of Bayesian network. The conditional phase-type (C-Ph) distribution is a Bayesian network that models the probabilistic causal relationships between a skewed continuous variable, modelled by the Coxian phase-type distribution, a special type of Markov model, and a set of interacting discrete variables. The algorithm takes a dataset as input and produces the structure, parameters and graphical representations of the fit of the C-Ph distribution as output.The algorithm, which uses a greedy-search technique and has been implemented in MATLAB, is evaluated using a simulated data set consisting of 20,000 cases. The results show that the original C-Ph distribution is recaptured and the fit of the network to the data is discussed.

Computational identification of self-inhibitory peptides from envelope proteins

Fusion process is known to be the initial step of viral infection and hence targeting the entry process is a promising strategy to design antiviral therapy. The self-inhibitory peptides derived from the enveloped (E) proteins function to inhibit the proteinprotein interactions in the membrane fusion step mediated by the viral E protein. Thus, they have the potential to be developed into effective antiviral therapy. Herein, we have developed a Monte Carlo-based computational method with the aim to identify and optimize potential peptide hits from the E proteins. The stability of the peptides, which indicates their potential to bind in situ to the E proteins, was evaluated by two different scoring functions, dipolar distance-scaled, finite, ideal-gas reference state and residue-specific all-atom probability discriminatory function. The method was applied to a-helical Class I HIV-1 gp41, beta-sheet Class II Dengue virus (DENV) type 2 E proteins, as well as Class III Herpes Simplex virus-1 (HSV-1) glycoprotein, a E protein with a mixture of a-helix and beta-sheet structural fold. The peptide hits identified are in line with the druggable regions where the self-inhibitory peptide inhibitors for the three classes of viral fusion proteins were derived. Several novel peptides were identified from either the hydrophobic regions or the functionally important regions on Class II DENV-2 E protein and Class III HSV-1 gB. They have potential to disrupt the proteinprotein interaction in the fusion process and may serve as starting points for the development of novel inhibitors for viral E proteins. 

Modeled structure of a G-protein-coupled receptor:The cholecystokinin-1 receptor

The Cholecystokinin-1 receptor (CCK1R) mediates actions of CCK in areas of the central nervous system and of the gut. It is a potential target to treat a number of diseases. As for all G-protein-coupled receptors, docking of ligands into modeled CCK1R binding site should greatly help to understand intrinsic mechanisms of activation. Here, we describe the procedure we used to progressively build a structural model for the CCK1R, to integrated, and on the basis of site-directed mutagenesis data on its binding site. Reliability of the CCK1R model was confirmed by interaction networks that involved conserved and functionally crucial motifs in G-protein-coupled receptors, such as Glu/Asp-Arg-Tyr and Asn-Pro-Xaa-Xaa-Tyr motifs. In addition, the 3-D structure of CCK1R-bound CCK resembled that determined by NMR in a lipid environment. The derived computational model was also used for revealing binding modes of several nonpeptide ligands and for rationalizing ligand structure-activity relationships known from experiments. Our findings indeed support that our "validated CCK1R model" could be used to study the intrinsic mechanism of CCK1R activation and design new ligands.

CoMFA and homology-based models of the glycine binding site of N-methyl-D-aspartate receptor

Homology modeling was used to build 3D models of the N-methyl-D-aspartate (NMDA) receptor glycine binding site on the basis of an X-ray structure of the water-soluble AMPA-sensitive receptor. The docking of agonists and antagonists to these models was used to reveal binding modes of ligands and to explain known structure-activity relationships. Two types of quantitative models, 3D-QSAR/CoMFA and a regression model based on docking energies, were built for antagonists (derivatives of 4-hydroxy-2-quinolone, quinoxaline-2,3-dione, and related compounds). The CoMFA steric and electrostatic maps were superimposed on the homology-based model, and a close correspondence was marked. The derived computational models have permitted the evaluation of the structural features crucial for high glycine binding site affinity and are important for the design of new ligands.

The Computational Complexity of Dominance and Consistency in CP-Nets

We investigate the computational complexity of testing dominance and consistency in CP-nets. Previously, the complexity of dominance has been determined for restricted classes in which the dependency graph of the CP-net is acyclic. However, there are preferences of interest that define cyclic dependency graphs; these are modeled with general CP-nets. In our main results, we show here that both dominance and consistency for general CP-nets are PSPACE-complete. We then consider the concept of strong dominance, dominance equivalence and dominance incomparability, and several notions of optimality, and identify the complexity of the corresponding decision problems. The reductions used in the proofs are from STRIPS planning, and thus reinforce the earlier established connections between both areas.

Computational techniques for a simple theory of conditional preferences

A simple logic of conditional preferences is defined, with a language that allows the compact representation of certain kinds of conditional preference statements, a semantics and a proof theory. CP-nets and TCP-nets can be mapped into this logic, and the semantics and proof theory generalise those of CP-nets and TCP-nets. The system can also express preferences of a lexicographic kind. The paper derives various sufficient conditions for a set of conditional preferences to be consistent, along with algorithmic techniques for checking such conditions and hence confirming consistency. These techniques can also be used for totally ordering outcomes in a way that is consistent with the set of preferences, and they are further developed to give an approach to the problem of constrained optimisation for conditional preferences.

A computational study of the mechanism of CO oxidation by a ceria supported surface rhodium oxide layer

A mechanism of CO oxidation by a thin surface oxide of Rh supported on ceria is proposed: CO is oxidized by the Rh-oxide film, which is subsequently reoxidized by a ceria surface O atom. The proposed mechanism is supported by in situ Raman spectroscopic investigations.

Deployment on GPUs of an application in computational atomic physics

This paper describes the deployment on GPUs of PROP, a program of the 2DRMP suite which models electron collisions with H-like atoms and ions. Because performance on GPUs is better in single precision than in double precision, the numerical stability of the PROP program in single precision has been studied. The numerical quality of PROP results computed in single precision and their impact on the next program of the 2DRMP suite has been analyzed. Successive versions of the PROP program on GPUs have been developed in order to improve its performance. Particular attention has been paid to the optimization of data transfers and of linear algebra operations. Performance obtained on several architectures (including NVIDIA Fermi) are presented.

Comparison of dynamics of wildtype and V94M human UDP-galactose 4-epimerase-A computational perspective on severe epimerase-deficiency galactosemia

UDP-galactose 4'-epimerase (GALE) catalyzes the interconversion of UDP-galactose and UDP-glucose, an important step in galactose catabolism. Type III galactosemia, an inherited metabolic disease, is associated with mutations in human GALE. The V94M mutation has been associated with a very severe form of type III galactosemia. While a variety of structural and biochemical studies have been reported that elucidate differences between the wildtype and this mutant form of human GALE, little is known about the dynamics of the protein and how mutations influence structure and function. We performed molecular dynamics simulations on the wildtype and V94M enzyme in different states of substrate and cofactor binding. In the mutant, the average distance between the substrate and both a key catalytic residue (Tyr157) and the enzyme-bound NAD(+) cofactor and the active site dynamics are altered making substrate binding slightly less stable. However, overall stability or dynamics of the protein is not altered. This is consistent with experimental findings that the impact is largely on the turnover number (kcat), with less substantial effects on Km. Active site fluctuations were found to be correlated in enzyme with substrate bound to just one of the subunits in the homodimer suggesting inter-subunit communication. Greater active site loop mobility in human GALE compared to the equivalent loop in Escherichia coli GALE explains why the former can catalyze the interconversion of UDP-N-acetylgalactosamine and UDP-N-acetylglucosamine while the bacterial enzyme cannot. This work illuminates molecular mechanisms of disease and may inform the design of small molecule therapies for type III galactosemia.

Solid phase synthesis of Smac/DIABLO-derived peptides using a 'Safety-Catch' resin:Identification of potent XIAP BIR3 antagonists

The N-terminal sequence of the Smac/DIABLO protein is known to be involved in binding to the BIR3 domain of the anti-apoptotic proteins IAPs, antagonizing their action. Short peptides and peptide mimetics based on the first 4-residues of Smac/DIABLO have been demonstrated to re-sensitize resistant cancer cells, over-expressing IAPs, to apoptosis. Based on the well-defined structural basis for this interaction, a small focused library of C-terminal capped Smac/DIABLO-derived peptides was designed in silico using docking to the XIAP BIR3 domain. The top-ranked computational hits were conveniently synthesized employing Solid Phase Synthesis (SPS) on an alkane sulfonamide 'Safety-Catch' resin. This novel approach afforded the rapid synthesis of the target peptide library with high flexibility for the introduction of various C-terminal amide-capping groups. The library members were obtained in high yield (>65%) and purity (>85%), upon nucleophilic release from the activated resin by treatment with various amine nucleophiles. In vitro caspase-9 activity reconstitution assays of the peptides in the presence of the recombinant BIR3-domain of human XIAP (500nM) revealed N-methylalanyl-tertiarybutylglycinyl-4-(R)-phenoxyprolyl-N-biphenylmethyl carboxamide (11a) to be the most potent XIAP BIR3 antagonist of the series synthesized inducing 93% recovery of caspase-9 activity, when used at 1µM concentration. Compound (11a) also demonstrated moderate cytotoxicity against the breast cancer cell lines MDA-MB-231 and MCF-7, compared to the Smac/DIABLO-derived wild-type peptide sequences that were totally inactive in the same cell lines.