Introducing Catastrophe-QSAR. Application on Modeling Molecular Mechanisms of Pyridinone Derivative-Type HIV Non-Nucleoside Reverse Transcriptase Inhibitors

The classical method of quantitative structure-activity relationships (QSAR) is enriched using non-linear models, as Thom’s polynomials allow either uni- or bi-variate structural parameters. In this context, catastrophe QSAR algorithms are applied to the anti-HIV-1 activity of pyridinone derivatives. This requires calculation of the so-called relative statistical power and of its minimum principle in various QSAR models. A new index, known as a statistical relative power, is constructed as an Euclidian measure for the combined ratio of the Pearson correlation to algebraic correlation, with normalized t-Student and the Fisher tests. First and second order inter-model paths are considered for mono-variate catastrophes, whereas for bi-variate catastrophes the direct minimum path is provided, allowing the QSAR models to be tested for predictive purposes. At this stage, the max-to-min hierarchies of the tested models allow the interaction mechanism to be identified using structural parameter succession and the typical catastrophes involved. Minimized differences between these catastrophe models in the common structurally influential domains that span both the trial and tested compounds identify the “optimal molecular structural domains” and the molecules with the best output with respect to the modeled activity, which in this case is human immunodeficiency virus type 1 HIV-1 inhibition. The best molecules are characterized by hydrophobic interactions with the HIV-1 p66 subunit protein, and they concur with those identified in other 3D-QSAR analyses. Moreover, the importance of aromatic ring stacking interactions for increasing the binding affinity of the inhibitor-reverse transcriptase ligand-substrate complex is highlighted

Exploring the Null Space of the Acoustic-to-Articulatory Inversion Using a Hypercube Codebook

Our acoustic to articulatory inversion method exploits an original codebook representing the articulatory space by hypercubes. The articulatory space is decomposed into regions where the articulatory-to-acoustic mapping is linear. Each region is represented by a hypercube. The inversion procedure retrieves articulatory vectors corresponding to an acoustic entry from the hypercube codebook. The main issue is about how all the possible inverse solutions in a given hypercube could be found. As the dimension of the articulatory space is greater than the dimension of the acoustic space, the corresponding null space is sampled by linear programming to retrieve all the possible solutions. Indeed, the sampling of the null space is a crucial point because it directly controls the smoothness of articulatory trajectories recovered from the original signal. This approach permits more realistic articulatory trajectories to be obtained. 1

Efficient Overlapped FFT Algorithms for

In this work, we propose parallel FFT algorithms, for medium-to-coarse grain hypercubeconnected multicomputers, which are more elegant and efficient than the existing ones. The proposed algorithms achieve perfect load-balance for the efficient simplified-butterfly scheme, minimize the communication overhead by decreasing both the number and the volume of concurrent communications. Communication and computation cannot be overlapped easily due to the strong data dependencies in the FFT algorithm. In this paper, we propose a restructuring for the FFT algorithm which enables overlapping each communication with one fifth of the local computations involved in a stage. Two of the proposed parallel FFT algorithms achieve overlapping by exploiting this restructuring while using the efficient table-lookup scheme for complex coefficients. The proposed algorithms are implemented on an Intel’s 32-node iPSC/2 hypercube multicomputer. High efficiency values are obtained even for small size FFT problems