String-based Multi-adjoint Lattices for Tracing Fuzzy Logic Computations

Classically, most programming languages use in a predefined way thenotion of “string” as an standard data structure for a comfortable management of arbitrary sequences of characters. However, in this paper we assign a different role to this concept: here we are concerned with fuzzy logic programming, a somehow recent paradigm trying to introduce fuzzy logic into logic programming. In this setting, the mathematical concept of multi-adjoint lattice has been successfully exploited into the so-called Multi-adjoint Logic Programming approach, MALP in brief, for modeling flexible notions of truth-degrees beyond the simpler case of true and false. Our main goal points out not only our formal proof verifying that stringbased lattices accomplish with the so-called multi-adjoint property (as well as its Cartesian product with similar structures), but also its correspondence with interesting debugging tasks into the FLOPER system (from “Fuzzy LOgic Programming Environment for Research”) developed in our research group

A Bioinformatics Study of Protein Conformational Flexibility and Misfolding: a Sequence, Structure and Dynamics Approach

This PhD Thesis titled "A Bioinformatics Study of Protein Conformational Flexibility and Misfolding: a Sequence, Structure and Dynamics Approach" comprises the results and conclusions obtained by us from the study of three different but somehow related research projects, covering aspects of the phenomenon of protein local conformational instability, its relationship with protein function, evolvability and aggregation, and the effect of genetic variations on protein conformational instability related to Conformational Diseases. These projects include the prediction of putative prion proteins in complete proteomes and the study of prion biology from a genomic perspective, the prediction of conformationally unstable protein regions and the existence of a structural framework for linking conformational instability to folding and function, and the establishment of a rationale for assessing the connection among mutations and disease phenotypes in Conformational Diseases.Esta tesis doctoral comprende los resultados y conclusiones obtenidos por nosotros a partir del estudio de tres proyectos de investigación diferentes pero de alguna manera relacionados, cubriendo los aspectos del fenómeno de la inestabilidad conformacional local de la proteína, su relación con la función de la proteína, la capacidad de evolución y agregación, y el efecto de las variaciones genéticas en la inestabilidad conformacional de la proteína relacionados con las enfermedades conformacionales. Estos proyectos incluyen la predicción de presuntas proteínas priónicas en proteomas complejos y el estudio de la biología de priones desde una perspectiva genómica, la predicción de las regiones de proteínas conformacionalmente inestables y la existencia de un marco estructural para la vinculación de la inestabilidad conformacional del plegado y la función, y el establecimiento de una razón fundamental para la evaluación de la relación entre las mutaciones y fenotipos de la enfermedad en enfermedades conformacionales

Environment matters : the impact of urea and macromolecular crowding on proteins

[eng] This work aims to analytically understand the impact of two diametric opposite environments on protein structure and dynamics and compared them to the most common solvent on earth: water. The first environment is a popular denaturing solution (urea 8M), which has served for years in protein-science laboratories to investigate protein stability; still many open questions regarding its mechanism of action remained unclear. The second environment instead moves towards a more physiological representation of proteins. The cell interior, in fact, is a crowded solution highly populated prevalently by proteins, but studies on protein structure and dynamics have lead so far to confusing or even opposite observations. The lack of a consensus view in both phenomena possibly derives from the bias of the system under study. This work is an attempt of a comparative study using the most general systems: a diverse spectrum of proteins folds, different stages along the reaction path (early stages or end-point) and/or different protein force-fields. Our main objective was to derive common pattern and general rules valid at proteome level, focusing on three major aspects of proteins: the structure, the dynamic and the interactions with the solvent molecules. Molecular dynamics simulation appeared then as the most suitable tool because of its ability to i) analyze proteins at broad range of resolutions; ii) access the direct time-resolved dynamic of the system and iii) dissect the specific interactions that arise in the new settings. Specifically, the case of urea-induced unfolding needs a system for which is possible to clearly identify folded and unfolded state – globular proteins are then the most suitable ones. We extracted general rules on the folded/unfolded transition by studying independently the two end-points of folded/unfolded reaction. We simulated the urea-induced unfolded state of a model protein, ubiquitin to understand the energetics stabilizing unfolded structures in urea. We found that the unfolded ubiquitin in 8M urea is fully extend and flexible and capturing efficiently urea molecules to the first solvation shell. Dispersion, rather than electrostatic, appear the main energetic contribution to explain the stabilization of the unfolded state. We then simulated the early stages of urea-induced unfolding on a large dataset of folded proteins, which represent the major folds of globular proteins, aiming also to investigate the kinetic role of urea in triggering the protein unfolding. We found that partially unfolded proteins expose the apolar residues buried in the protein interior, mainly via cavitation. Similar to the unfolded state, it is the dispersion interactions that drive urea accumulation in the solvation shell but here urea molecules take advantage of microscopic unfolding events to penetrate the protein interior. Macromolecular crowding instead is a phenomenon that universally affects all the proteins. We simulated a system that included as crowding agents proteins with different conformational landscapes (a globular protein, an intrinsically disordered proteins and a molten globule) arranged to reach cell-like concentrations. We conclude that the universal effect of crowding, valid for all the proteins types, is exerted via the aspecific interactions and favors open and moderately extended conformations with higher secondary structure content. This phenomenon counterbalances the volume-exclusion, which prevails at higher crowding concentrations. The impact of crowding is proportional to the degree of disorder of the protein and for folded protein crowding favors structural rearrangements while unfolded structures experience a stronger stabilization and a higher secondary structures content. The synthetic crowder PEG doesn’t reproduce any of these effects, arising concerns about its employment in study cell-like environments

A Survey on Compiler Autotuning using Machine Learning

Since the mid-1990s, researchers have been trying to use machine-learning based approaches to solve a number of different compiler optimization problems. These techniques primarily enhance the quality of the obtained results and, more importantly, make it feasible to tackle two main compiler optimization problems: optimization selection (choosing which optimizations to apply) and phase-ordering (choosing the order of applying optimizations). The compiler optimization space continues to grow due to the advancement of applications, increasing number of compiler optimizations, and new target architectures. Generic optimization passes in compilers cannot fully leverage newly introduced optimizations and, therefore, cannot keep up with the pace of increasing options. This survey summarizes and classifies the recent advances in using machine learning for the compiler optimization field, particularly on the two major problems of (1) selecting the best optimizations and (2) the phase-ordering of optimizations. The survey highlights the approaches taken so far, the obtained results, the fine-grain classification among different approaches and finally, the influential papers of the field.Comment: version 5.0 (updated on September 2018)- Preprint Version For our Accepted Journal @ ACM CSUR 2018 (42 pages) - This survey will be updated quarterly here (Send me your new published papers to be added in the subsequent version) History: Received November 2016; Revised August 2017; Revised February 2018; Accepted March 2018

The Amazing World of IDPs in Human Diseases

It is now clearly established that some proteins or protein regions are devoid of any stable secondary and/or tertiary structure under physiological conditions, but still possess fundamental biological functions. These intrinsically disordered proteins (IDPs) or regions (IDRs) have peculiar features due to their plasticity such as the capacity to bind their biological targets with high specificity and low affinity, and the possibility of interaction with numerous partners. A correlation between intrinsic disorder and various human diseases such as cancer, diabetes, amyloidoses and neurodegenerative diseases is now evident, highlighting the great importance of the topic. In this volume, we have collected recent high-quality research about IDPs and human diseases. We have selected nine papers which deal with a wide range of topics, from neurodegenerative disease to cancer, from IDR-mediated interactions to bioinformatics tools, all related to IDP peculiar features. Recent advances in the IDPs/IDRs issue are here presented, contributing to the progress of knowledge of the intrinsic disorder field in human disease

Functionally Relevant Macromolecular Interactions of Disordered Proteins

Disordered proteins are relatively recent newcomers in protein science. They were first described in detail by Wright and Dyson, in their J. Mol. Biol. paper in 1999. First, it was generally thought for more than a decade that disordered proteins or disordered parts of proteins have different amino acid compositions than folded proteins, and various prediction methods were developed based on this principle. These methods were suitable for distinguishing between the disordered (unstructured) and structured proteins known at that time. In addition, they could predict the site where a folded protein binds to the disordered part of a protein, shaping the latter into a well-defined 3D structure. Recently, however, evidence has emerged for a new type of disordered protein family whose members can undergo coupled folding and binding without the involvement of any folded proteins. Instead, they interact with each other, stabilizing their structure via “mutual synergistic folding” and, surprisingly, they exhibit the same residue composition as the folded protein. Increasingly more examples have been found where disordered proteins interact with non-protein macromolecules, adding to the already large variety of protein–protein interactions. There is also a very new phenomenon when proteins are involved in phase separation, which can represent a weak but functionally important macromolecular interaction. These phenomena are presented and discussed in the chapters of this book

Molecular Modeling of Bacterial Nanomachineries

Proteins have the ability to assemble in multimeric states to perform their specific biological function. Unfortunately, characterizing experimentally these structures at atomistic resolution is usually difficult. For this reason, in silico methodologies aiming at predicting how multiple protein copies arrange to forma multimeric complex would be desirable. We present Parallel OptimizationWorkbench (POW), a swarm intelligence based optimization framework able to deal, in principle, with any optimization problem. We show that POW can be applied to biologically relevant problems such as prediction of protein assemblies and the parameterization of a Coarse-Grained force field for proteins. By combining POW optimizations, Molecular Dynamics simulations, Poisson-Boltzmann calculations and a variety of experiments, we subsequently study two bacterial nanomachieries: Aeromonas hydrophila's pore-forming toxin aerolysin, and Yersinia enterocolitica injectisome. These structures are challenging both for their size, and for the timescales involved in their functioning. Aerolysin is a pore-forming toxin secreted as an hydrophilic monomer. By means of large conformational changes, the protein heptamerizes on the target cell's surface, and finally inserts β-barrel into its lipid bilayer, causing cell death. The main hurdle in the study of this structure is the complexity of the mode of action, which spans timescales currently unreachable by classical molecular dynamics. We show that aerolysin C-terminal region has the dual role of preventing premature oligomerization and helping the folding of tertiary structure, qualifying therefore as an intramolecular chaperone. We study the transmembrane β-barrel properties and compare them with those of the homologous protein α-hemolysin. We show that aerolysin's barrel is more rigid than α-hemolysin's, and should be anion selective. We present models for aerolysin heptamer both in prepore and, for the first time, in membrane-inserted conformation. Our results are validated experimentally, and are consistent with known biochemical and structural data. The injectisome is an example of a type III secretion system. Its most striking feature is probably its size: hundreds of proteins assemble in a unique structure spanning the Gram-negative bacterial double membrane, and protruding outside the cell as a needle for tenth of nanometers. Obtaining an atomistic representation of this massive structure, and therefore some insights about its mode of action, is one of the greatest challenges. We show that the final length of injectisome's needle is determined by the secondary structure content of a ruler protein located inside its cavity during assembly. Using POW, we also produce the first model for Yersinia injectisome's basal body, highlighting the flexibility of this region in adapting between the inner and outer membranes. As a whole, this work demonstrates that a synergy of dry and wet experiments can provide precious insights into macromolecular structure and function