Pattern recognition analysis on heavy ion reaction data

One of the problems in the analysis of nucleus-nucleus collisions is to get information on the value of the impact parameter b. This work consists in the application of pattern recognition techniques aimed at associating values of b to groups of events. To this end, a support vec- tor machine (SVM) classifier is adopted to analyze multifragmentation reactions. This method allows to backtracing the values of b through a particular multidimensional analysis. The SVM classification con- sists of two main phase. In the first one, known as training phase, the classifier learns to discriminate the events that are generated by two different model:Classical Molecular Dynamics (CMD) and Heavy- Ion Phase-Space Exploration (HIPSE) for the reaction: 58Ni +48 Ca at 25 AMeV. To check the classification of events in the second one, known as test phase, what has been learned is tested on new events generated by the same models. These new results have been com- pared to the ones obtained through others techniques of backtracing the impact parameter. Our tests show that, following this approach, the central collisions and peripheral collisions, for the CMD events, are always better classified with respect to the classification by the others techniques of backtracing. We have finally performed the SVM classification on the experimental data measured by NUCL-EX col- laboration with CHIMERA apparatus for the previous reaction.

Enabling computationally intensive bioinformatics applications on the Grid platform

Bioinformatics is a recent and emerging discipline which aims at studying biological problems through computational approaches. Most branches of bioinformatics such as Genomics, Proteomics and Molecular Dynamics are particularly computationally intensive, requiring huge amount of computational resources for running algorithms of everincreasing complexity over data of everincreasing size. In the search for computational power, the EGEE Grid platform, world's largest community of interconnected clusters load balanced as a whole, seems particularly promising and is considered the new hope for satisfying the everincreasing computational requirements of bioinformatics, as well as physics and other computational sciences. The EGEE platform, however, is rather new and not yet free of problems. In addition, specific requirements of bioinformatics need to be addressed in order to use this new platform effectively for bioinformatics tasks. In my three years' Ph.D. work I addressed numerous aspects of this Grid platform, with particular attention to those needed by the bioinformatics domain. I hence created three major frameworks, Vnas, GridDBManager and SETest, plus an additional smaller standalone solution, to enhance the support for bioinformatics applications in the Grid environment and to reduce the effort needed to create new applications, additionally addressing numerous existing Grid issues and performing a series of optimizations. The Vnas framework is an advanced system for the submission and monitoring of Grid jobs that provides an abstraction with reliability over the Grid platform. In addition, Vnas greatly simplifies the development of new Grid applications by providing a callback system to simplify the creation of arbitrarily complex multistage computational pipelines and provides an abstracted virtual sandbox which bypasses Grid limitations. Vnas also reduces the usage of Grid bandwidth and storage resources by transparently detecting equality of virtual sandbox files based on content, across different submissions, even when performed by different users. BGBlast, evolution of the earlier project GridBlast, now provides a Grid Database Manager (GridDBManager) component for managing and automatically updating biological flatfile databases in the Grid environment. GridDBManager sports very novel features such as an adaptive replication algorithm that constantly optimizes the number of replicas of the managed databases in the Grid environment, balancing between response times (performances) and storage costs according to a programmed cost formula. GridDBManager also provides a very optimized automated management for older versions of the databases based on reverse delta files, which reduces the storage costs required to keep such older versions available in the Grid environment by two orders of magnitude. The SETest framework provides a way to the user to test and regressiontest Python applications completely scattered with side effects (this is a common case with Grid computational pipelines), which could not easily be tested using the more standard methods of unit testing or test cases. The technique is based on a new concept of datasets containing invocations and results of filtered calls. The framework hence significantly accelerates the development of new applications and computational pipelines for the Grid environment, and the efforts required for maintenance. An analysis of the impact of these solutions will be provided in this thesis. This Ph.D. work originated various publications in journals and conference proceedings as reported in the Appendix. Also, I orally presented my work at numerous international conferences related to Grid and bioinformatics.

Synthesis of Modified Amino Acids and Insertion in Peptides and Mimetics. Structural Aspects and Impact on Biological Activity.

I studied the effects exerted by the modifications on structures and biological activities of the compounds so obtained. I prepared peptide analogues containing unusual amino acids such as halogenated, alkylated (S)- or (R)-tryptophans, useful for the synthesis of mimetics of the endogenous opioid peptide endomorphin-1, or 2-oxo-1,3-oxazolidine-4-carboxylic acids, utilized as pseudo-prolines having a clear all-trans configuration of the preceding peptide bond. The latter gave access to a series of constrained peptidomimetics with potential interest in medicinal chemistry and in the field of the foldamers. In particular, I have dedicated much efforts to the preparation of cyclopentapeptides containing D-configured, alfa-, or beta-aminoacids, and also of cyclotetrapeptides including the retro-inverso modification. The conformational analyses confirmed that these cyclic compounds can be utilized as rigid scaffolds mimicking gamma- or beta-turns, allowing to generate new molecular and 3D diversity. Much work has been dedicated to the structural analysis in solution and in the receptor-bound state, fundamental for giving a rationale to the experimentally determined bioactivity, as well as for predicting the activity of virtual compounds (in silico pre-screen). The conformational analyses in solution has been done mostly by NMR (2D gCosy, Roesy, VT, molecular dynamics, etc.). A special section is dedicated to the prediction of plausible poses of the ligands when bound to the receptors by Molecular Docking. This computational method proved to be a powerful tool for the investigation of ligand-receptor interactions, and for the design of selective agonists and antagonists. Another practical use of cyclic peptidomimetics was the synthesis and biological evaluation of cyclic analogues of endomorphin-1 lacking in a protonable amino group. The studies revealed that a inverse type II beta-turn on D-Trp-Phe constituted the bioactive conformation.

Modeling and simulations of some anisotropic soft-matter systems: from biaxial to chiral materials

We have modeled various soft-matter systems with molecular dynamics (MD) simulations. The first topic concerns liquid crystal (LC) biaxial nematic (Nb) phases, that can be possibly used in fast displays. We have investigated the phase organization of biaxial Gay-Berne (GB) mesogens, considering the effects of the orientation, strength and position of a molecular dipole. We have observed that for systems with a central dipole, nematic biaxial phases disappear when increasing dipole strength, while for systems characterized by an offset dipole, the Nb phase is stabilized at very low temperatures. In a second project, in view of their increasing importance as nanomaterials in LC phases, we are developing a DNA coarse-grained (CG) model, in which sugar and phosphate groups are represented with Lennard-Jones spheres, while bases with GB ellipsoids. We have obtained shape, position and orientation parameters for each bead, to best reproduce the atomistic structure of a B-DNA helix. Starting from atomistic simulations results, we have completed a first parametrization of the force field terms, accounting for bonded (bonds, angles and dihedrals) and non-bonded interactions (H-bond and stacking). We are currently validating the model, by investigating stability and melting temperature of various sequences. Finally, in a third project, we aim to explain the mechanism of enantiomeric discrimination due to the presence of a chiral helix of poly(gamma-benzyl L-glutamate) (PBLG), in solution of dimethylformamide (DMF), interacting with chiral or pro-chiral molecules (in our case heptyl butyrate, HEP), after tuning properly an atomistic force field (AMBER). We have observed that DMF and HEP molecules solvate uniformly the PBLG helix, but the pro-chiral solute is on average found closer to the helix with respect to the DMF. The solvent presents a faster isotropic diffusion, twice as HEP, also indicating a stronger interaction of the solute with the helix.

Computational strategies to include protein flexibility in Ligand Docking and Virtual Screening

The dynamic character of proteins strongly influences biomolecular recognition mechanisms. With the development of the main models of ligand recognition (lock-and-key, induced fit, conformational selection theories), the role of protein plasticity has become increasingly relevant. In particular, major structural changes concerning large deviations of protein backbones, and slight movements such as side chain rotations are now carefully considered in drug discovery and development. It is of great interest to identify multiple protein conformations as preliminary step in a screening campaign. Protein flexibility has been widely investigated, in terms of both local and global motions, in two diverse biological systems. On one side, Replica Exchange Molecular Dynamics has been exploited as enhanced sampling method to collect multiple conformations of Lactate Dehydrogenase A (LDHA), an emerging anticancer target. The aim of this project was the development of an Ensemble-based Virtual Screening protocol, in order to find novel potent inhibitors. On the other side, a preliminary study concerning the local flexibility of Opioid Receptors has been carried out through ALiBERO approach, an iterative method based on Elastic Network-Normal Mode Analysis and Monte Carlo sampling. Comparison of the Virtual Screening performances by using single or multiple conformations confirmed that the inclusion of protein flexibility in screening protocols has a positive effect on the probability to early recognize novel or known active compounds.

Chiroptical properties of bioactive molecules: sensitivity to conformation and solvation

Chiroptical spectroscopies play a fundamental role in pharmaceutical analysis for the stereochemical characterisation of bioactive molecules, due to the close relationship between chirality and optical activity and the increasing evidence of stereoselectivity in the pharmacological and toxicological profiles of chiral drugs. The correlation between chiroptical properties and absolute stereochemistry, however, requires the development of accurate and reliable theoretical models. The present thesis will report the application of theoretical chiroptical spectroscopies in the field of drug analysis, with particular emphasis on the huge influence of conformational flexibility and solvation on chiroptical properties and on the main computational strategies available to describe their effects by means of electronic circular dichroism (ECD) spectroscopy and time-dependent density functional theory (TD-DFT) calculations. The combination of experimental chiroptical spectroscopies with state-of-the-art computational methods proved to be very efficient at predicting the absolute configuration of a wide range of bioactive molecules (fluorinated 2-arylpropionic acids, β-lactam derivatives, difenoconazole, fenoterol, mycoleptones, austdiol). The results obtained for the investigated systems showed that great care must be taken in describing the molecular system in the most accurate fashion, since chiroptical properties are very sensitive to small electronic and conformational perturbations. In the future, the improvement of theoretical models and methods, such as ab initio molecular dynamics, will benefit pharmaceutical analysis in the investigation of non-trivial effects on the chiroptical properties of solvated systems and in the characterisation of the stereochemistry of complex chiral drugs.

Computational insight into materials properties

The aim of the work was to explore the practical applicability of molecular dynamics at different length and time scales. From nanoparticles system over colloids and polymers to biological systems like membranes and finally living cells, a broad range of materials was considered from a theoretical standpoint. In this dissertation five chemistry-related problem are addressed by means of theoretical and computational methods. The main results can be outlined as follows. (1) A systematic study of the effect of the concentration, chain length, and charge of surfactants on fullerene aggregation is presented. The long-discussed problem of the location of C60 in micelles was addressed and fullerenes were found in the hydrophobic region of the micelles. (2) The interactions between graphene sheet of increasing size and phospholipid membrane are quantitatively investigated. (3) A model was proposed to study structure, stability, and dynamics of MoS2, a material well-known for its tribological properties. The telescopic movement of nested nanotubes and the sliding of MoS2 layers is simulated. (4) A mathematical model to gain understaning of the coupled diffusion-swelling process in poly(lactic-co-glycolic acid), PLGA, was proposed. (5) A soft matter cell model is developed to explore the interaction of living cell with artificial surfaces. The effect of the surface properties on the adhesion dynamics of cells are discussed.

Atomistic simulations of liquid crystals in the bulk and at their interfaces

In this thesis, we have dealt with several problems concerning liquid crystals (LC) phases, either in the bulk or at their interfaces, by the use of atomistic molecular dynamics (MD) simulations. We first focused our attention on simulating and characterizing the bulk smectic phase of 4-n-octyl-4'-cyanobiphenyl (8CB), allowing us to investigate the antiparallel molecular arrangement typical of SmAd smectic phases. A second topic of study was the characterization of the 8CB interface with vacuum by simulating freely suspended thin films, which allowed us to determine the influence of the interface on the orientational and positional order. Then we investigated the LC-water and LC-electrolyte water solution interface. This interface has recently found application in the development of sensors for several compounds, including biological molecules, and here we tried to understand the re-orientation mechanism of LC molecules at the interface which is behind the functioning of these sensors. The characterization of this peculiar interface has incidentally led us to develop a polarizable force field for the pentyl-cyanobiphenyl mesogen, whose process of parametrization and validation is reported here in detail. We have shown that this force field is a significant improvement over its previous, static charge non polarizable version in terms of density, orientational order parameter and translational diffusion.

Synthesis of constrained peptidomimetics for therapeutic, diagnostic and theranostic applications

This thesis work deals, principally, with the development of different chemical protocols ranging from environmental sustainability peptide synthesis to asymmetric synthesis of modified tryptophans to a series of straightforward procedures for constraining peptide backbones without the need for a pre-formed scaffold. Much efforts have been dedicated to the structural analysis in a biomimetic environment, fundamental for predicting the in vivo conformation of compounds, as well as for giving a rationale to the experimentally determined bioactivity. The conformational analyses in solution has been done mostly by NMR (2D gCosy, Roesy, VT, titration experiments, molecular dynamics, etc.), FT-IR and ECD spectroscopy. As a practical application, 3D rigid scaffolds have been employed for the synthesis of biological active compounds based on peptidomimetic and retro-mimetic structures. These mimics have been investigated for their potential as antiflammatory agents and actually the results obtained are very promising. Moreover, the synthesis of Amo ring permitted the development of an alternative high effective synthetic pathway for obtaining Linezolid antibiotic. The final section is, instead, dedicated to the construction of a new biosensor based on zeolite L SAMs functionalized with the integrin ligand c[RGDfK], that has showed high efficiency for the selective detection of tumor cells. Such kind of sensor could, in fact, enable the convenient, non-invasive detection and diagnosis of cancer in early stages, from a few drops of a patient's blood or other biological fluids. In conclusion, the researches described herein demonstrate that the peptidomimetic approach to 3D definite structures, allows unambiguous investigation of the structure-activity relationships, giving an access to a wide range bioactive compounds of pharmaceutical interest to use not only as potential drugs but also for diagnostic and theranostic applications.