A multidisciplinary approach to the study of protein dynamics and signal transmission

Allostery is a phenomenon of fundamental importance in biology, allowing regulation of function and dynamic adaptability of enzymes and proteins. Despite the allosteric effect was first observed more than a century ago allostery remains a biophysical enigma, defined as the “second secret of life”. The challenge is mainly associated to the rather complex nature of the allosteric mechanisms, which manifests itself as the alteration of the biological function of a protein/enzyme (e.g. ligand/substrate binding at the active site) by binding of “other object” (“allos stereos” in Greek) at a site distant (> 1 nanometer) from the active site, namely the effector site. Thus, at the heart of allostery there is signal propagation from the effector to the active site through a dense protein matrix, with a fundamental challenge being represented by the elucidation of the physico-chemical interactions between amino acid residues allowing communicatio n between the two binding sites, i.e. the “allosteric pathways”. Here, we propose a multidisciplinary approach based on a combination of computational chemistry, involving molecular dynamics simulations of protein motions, (bio)physical analysis of allosteric systems, including multiple sequence alignments of known allosteric systems, and mathematical tools based on graph theory and machine learning that can greatly help understanding the complexity of dynamical interactions involved in the different allosteric systems. The project aims at developing robust and fast tools to identify unknown allosteric pathways. The characterization and predictions of such allosteric spots could elucidate and fully exploit the power of allosteric modulation in enzymes and DNA-protein complexes, with great potential applications in enzyme engineering and drug discovery.

Characterization of L-type Calcium Channel Binding-Site of a new class of Calcium modulators by a Multidisciplinary approach

Many potential diltiazem related L-VDCC blockers were developed using a multidisciplinary approach. This current study was to investigate and compare diltiazem with to the newly developed compounds by mouse Langendorff-perfused heart, Ca2+-transient and on recombinant L-VDCC. Twenty particular compounds were selected by the ligand-based virtual screening procedure (LBVS). From these compounds, five of them (5b, M2, M7, M8 and P1) showed a potent and selective inotropic activity on guinea-pig left atria driven 1 Hz. Further assays displayed an interesting negative inotropic effect of M2, M8, P1 and M7 on guinea pig isolated left papillary muscle driven at 1 Hz, a relevant vasorelaxant activity of 5b, M2, M7, M8 and P1 on K+-depolarized guinea-pig ileum longitudinal smooth muscle and a significant inhibition of contraction of 5b, M2, M8 and P1 on carbachol stimulated ileum longitudinal smooth muscle. Wild-type human heart and rabbit lung α1 subunits were expressed (combined with the regulatory α2δ and β3 subunits) in Xenopus Leavis oocytes using a two-electrode voltage clamp technique. Diltiazem is a benzothiazepine Ca2+ channel blocker used clinically for its antihypertensive and antiarrhythmic effects. Previous radioligand binding assays revealed a complex interaction with the benzothiazepine binding site for M2, M7 and M8. (Carosati E. et al. J. Med Chem. 2006, 49; 5206). In agreement with this findings, the relative order of increased rates of contraction and relaxation at lower concentrations s(≤10-6M) in unpaced hearts was M7>M2>M8>P1. Similar increases in Ca2+ transient were observed in cardiomyocytes. Diltiazem showed negative inotropic effects whereas 5b had no significant effect. Diltiazem blocks Ca2+current in a use-dependent manner and facilitates the channel by accelerating the inactivation and decelerating the recovery from inactivation. In contrast to diltiazem, the new analogs had no pronounced use-dependence. Application of 100 μM M8, M2 showed ~ 10% tonic block; in addition, M8, M2 and P1 shifted the steady state inactivation in hyperpolarized direction and the current inactivation time was significantly decreased compared with control (219.6 ± 11.5 ms, 226 ± 14.5 vs. 269 ± 12.9 vs. 199.28 ± 8.19 ms). Contrary to diltiazem, the recovery from the block by M8 and M2 was comparable to control. Only P1 showed a significantly decrease of the time for the recovery from inactivation. All of the compounds displayed the same sensitivity on the Ca2+ channel rabbit lung α1 except P1. Taken together, these findings suggest that M8, M2 and P1 might directly decrease the binding affinity or allow rapid dissociation from the benzothiazepine binding site.

Combinatorial and Robust Optimisation Models and Algorithms for Railway Applications

This thesis deals with an investigation of combinatorial and robust optimisation models to solve railway problems. Railway applications represent a challenging area for operations research. In fact, most problems in this context can be modelled as combinatorial optimisation problems, in which the number of feasible solutions is finite. Yet, despite the astonishing success in the field of combinatorial optimisation, the current state of algorithmic research faces severe difficulties with highly-complex and data-intensive applications such as those dealing with optimisation issues in large-scale transportation networks. One of the main issues concerns imperfect information. The idea of Robust Optimisation, as a way to represent and handle mathematically systems with not precisely known data, dates back to 1970s. Unfortunately, none of those techniques proved to be successfully applicable in one of the most complex and largest in scale (transportation) settings: that of railway systems. Railway optimisation deals with planning and scheduling problems over several time horizons. Disturbances are inevitable and severely affect the planning process. Here we focus on two compelling aspects of planning: robust planning and online (real-time) planning.

Kinematic description of the rupture from strong motion data: strategies for a robust inversion

We present a non linear technique to invert strong motion records with the aim of obtaining the final slip and rupture velocity distributions on the fault plane. In this thesis, the ground motion simulation is obtained evaluating the representation integral in the frequency. The Green’s tractions are computed using the discrete wave-number integration technique that provides the full wave-field in a 1D layered propagation medium. The representation integral is computed through a finite elements technique, based on a Delaunay’s triangulation on the fault plane. The rupture velocity is defined on a coarser regular grid and rupture times are computed by integration of the eikonal equation. For the inversion, the slip distribution is parameterized by 2D overlapping Gaussian functions, which can easily relate the spectrum of the possible solutions with the minimum resolvable wavelength, related to source-station distribution and data processing. The inverse problem is solved by a two-step procedure aimed at separating the computation of the rupture velocity from the evaluation of the slip distribution, the latter being a linear problem, when the rupture velocity is fixed. The non-linear step is solved by optimization of an L2 misfit function between synthetic and real seismograms, and solution is searched by the use of the Neighbourhood Algorithm. The conjugate gradient method is used to solve the linear step instead. The developed methodology has been applied to the M7.2, Iwate Nairiku Miyagi, Japan, earthquake. The estimated magnitude seismic moment is 2.6326 dyne∙cm that corresponds to a moment magnitude MW 6.9 while the mean the rupture velocity is 2.0 km/s. A large slip patch extends from the hypocenter to the southern shallow part of the fault plane. A second relatively large slip patch is found in the northern shallow part. Finally, we gave a quantitative estimation of errors associates with the parameters.

Methodological improvement of 3D fluoroscopic analysis for the robust quantification of 3D kinematics of human joints

3D video-fluoroscopy is an accurate but cumbersome technique to estimate natural or prosthetic human joint kinematics. This dissertation proposes innovative methodologies to improve the 3D fluoroscopic analysis reliability and usability. Being based on direct radiographic imaging of the joint, and avoiding soft tissue artefact that limits the accuracy of skin marker based techniques, the fluoroscopic analysis has a potential accuracy of the order of mm/deg or better. It can provide fundamental informations for clinical and methodological applications, but, notwithstanding the number of methodological protocols proposed in the literature, time consuming user interaction is exploited to obtain consistent results. The user-dependency prevented a reliable quantification of the actual accuracy and precision of the methods, and, consequently, slowed down the translation to the clinical practice. The objective of the present work was to speed up this process introducing methodological improvements in the analysis. In the thesis, the fluoroscopic analysis was characterized in depth, in order to evaluate its pros and cons, and to provide reliable solutions to overcome its limitations. To this aim, an analytical approach was followed. The major sources of error were isolated with in-silico preliminary studies as: (a) geometric distortion and calibration errors, (b) 2D images and 3D models resolutions, (c) incorrect contour extraction, (d) bone model symmetries, (e) optimization algorithm limitations, (f) user errors. The effect of each criticality was quantified, and verified with an in-vivo preliminary study on the elbow joint. The dominant source of error was identified in the limited extent of the convergence domain for the local optimization algorithms, which forced the user to manually specify the starting pose for the estimating process. To solve this problem, two different approaches were followed: to increase the optimal pose convergence basin, the local approach used sequential alignments of the 6 degrees of freedom in order of sensitivity, or a geometrical feature-based estimation of the initial conditions for the optimization; the global approach used an unsupervised memetic algorithm to optimally explore the search domain. The performances of the technique were evaluated with a series of in-silico studies and validated in-vitro with a phantom based comparison with a radiostereometric gold-standard. The accuracy of the method is joint-dependent, and for the intact knee joint, the new unsupervised algorithm guaranteed a maximum error lower than 0.5 mm for in-plane translations, 10 mm for out-of-plane translation, and of 3 deg for rotations in a mono-planar setup; and lower than 0.5 mm for translations and 1 deg for rotations in a bi-planar setups. The bi-planar setup is best suited when accurate results are needed, such as for methodological research studies. The mono-planar analysis may be enough for clinical application when the analysis time and cost may be an issue. A further reduction of the user interaction was obtained for prosthetic joints kinematics. A mixed region-growing and level-set segmentation method was proposed and halved the analysis time, delegating the computational burden to the machine. In-silico and in-vivo studies demonstrated that the reliability of the new semiautomatic method was comparable to a user defined manual gold-standard. The improved fluoroscopic analysis was finally applied to a first in-vivo methodological study on the foot kinematics. Preliminary evaluations showed that the presented methodology represents a feasible gold-standard for the validation of skin marker based foot kinematics protocols.

A clustering method for robust and reliable large scale functional and structural protein sequence annotation

Bioinformatics, in the last few decades, has played a fundamental role to give sense to the huge amount of data produced. Obtained the complete sequence of a genome, the major problem of knowing as much as possible of its coding regions, is crucial. Protein sequence annotation is challenging and, due to the size of the problem, only computational approaches can provide a feasible solution. As it has been recently pointed out by the Critical Assessment of Function Annotations (CAFA), most accurate methods are those based on the transfer-by-homology approach and the most incisive contribution is given by cross-genome comparisons. In the present thesis it is described a non-hierarchical sequence clustering method for protein automatic large-scale annotation, called “The Bologna Annotation Resource Plus” (BAR+). The method is based on an all-against-all alignment of more than 13 millions protein sequences characterized by a very stringent metric. BAR+ can safely transfer functional features (Gene Ontology and Pfam terms) inside clusters by means of a statistical validation, even in the case of multi-domain proteins. Within BAR+ clusters it is also possible to transfer the three dimensional structure (when a template is available). This is possible by the way of cluster-specific HMM profiles that can be used to calculate reliable template-to-target alignments even in the case of distantly related proteins (sequence identity < 30%). Other BAR+ based applications have been developed during my doctorate including the prediction of Magnesium binding sites in human proteins, the ABC transporters superfamily classification and the functional prediction (GO terms) of the CAFA targets. Remarkably, in the CAFA assessment, BAR+ placed among the ten most accurate methods. At present, as a web server for the functional and structural protein sequence annotation, BAR+ is freely available at http://bar.biocomp.unibo.it/bar2.0.

Cancer and aging: a multidisciplinary medicinal chemistry approach on relevant biological targets such as proteasome, sirtuins and interleukin 6

It is well known that ageing and cancer have common origins due to internal and environmental stress and share some common hallmarks such as genomic instability, epigenetic alteration, aberrant telomeres, inflammation and immune injury. Moreover, ageing is involved in a number of events responsible for carcinogenesis and cancer development at the molecular, cellular, and tissue levels. Ageing could represent a “blockbuster” market because the target patient group includes potentially every person; at the same time, oncology has become the largest therapeutic area in the pharmaceutical industry in terms of the number of projects, clinical trials and research and development (R&D) spending, but cancer remains one of the leading causes of mortality worldwide. The overall aim of the work presented in this thesis was the rational design of new compounds able to modulate activity of relevant targets involved in cancer and aging-related pathologies, namely proteasome and immunoproteasome, sirtuins and interleukin 6. These three targets play different roles in human cells, but the modulation of its activity using small molecules could have beneficial effects on one or more aging-related diseases and cancer. We identified new moderately active and selective non-peptidic compounds able to inhibit the activity of both standard and immunoproteasome, as well as novel and selective scaffolds that would bind and inhibit SIRT6 selectively and can be used to sensitize tumor cells to commonly used anticancer agents such gemcitabine and olaparib. Moreover, our virtual screening approach led us also to the discovery of new putative modulators of SIRT3 with interesting in-vitro and cellular activity. Although the selectivity and potency of the identified chemical scaffolds are susceptible to be further improved, these compounds can be considered as highly promising leads for the development of future therapeutics.

Robust Nonlinear Output Regulation by Identification Tools

The present thesis focuses on the problem of robust output regulation for minimum phase nonlinear systems by means of identification techniques. Given a controlled plant and an exosystem (an autonomous system that generates eventual references or disturbances), the control goal is to design a proper regulator able to process the only measure available, i.e the error/output variable, in order to make it asymptotically vanishing. In this context, such a regulator can be designed following the well known “internal model principle” that states how it is possible to achieve the regulation objective by embedding a replica of the exosystem model in the controller structure. The main problem shows up when the exosystem model is affected by parametric or structural uncertainties, in this case, it is not possible to reproduce the exact behavior of the exogenous system in the regulator and then, it is not possible to achieve the control goal. In this work, the idea is to find a solution to the problem trying to develop a general framework in which coexist both a standard regulator and an estimator able to guarantee (when possible) the best estimate of all uncertainties present in the exosystem in order to give “robustness” to the overall control loop.

Ultra-Low Temperature Partial Oxidation: Detailed Kinetics, Safety, and Environmental Issues

The innovation in several industrial sectors has been recently characterized by the need for reducing the operative temperature either for economic or environmental related aspects. Promising technological solutions require the acquisition of fundamental-based knowledge to produce safe and robust systems. In this sense, reactive systems often represent the bottleneck. For these reasons, this work was focused on the integration of chemical (i.e., detailed kinetic mechanism) and physical (i.e., computational fluid dynamics) models. A theoretical-based kinetic mechanism mimicking the behaviour of oxygenated fuels and their intermediates under oxidative conditions in a wide range of temperature and pressure was developed. Its validity was tested against experimental data collected in this work by using the heat flux burner, as well as measurements retrieved from the current literature. Besides, estimations deriving from existing models considered as the benchmark in the combustion field were compared with the newly generated mechanism. The latter was found to be the most accurate for the investigated conditions and fuels. Most influential species and reactions on the combustion of butyl acetate were identified. The corresponding thermodynamic parameter and rate coefficients were quantified through ab initio calculations. A reduced detailed kinetic mechanism was produced and implemented in an open-source computational fluid dynamics model to characterize pool fires caused by the accidental release of aviation fuel and liquefied natural gas, at first. Eventually, partial oxidation processes involving light alkenes were optimized following the quick, fair, and smoot (QFS) paradigm. The proposed procedure represents a comprehensive and multidisciplinary approach for the construction and validation of accurate models, allowing for the characterization of developing industrial sectors and techniques.

Surgery after biological therapy in locally advanced NSCLC with molecular driver: feasibility and effectiveness of a new multidisciplinary approach

Introduction: Surgical outcomes after biological therapy have not been investigated yet and no information about timing, postoperative complications and survival have been recorded. Methods: This is a prospective study which compares a group of stage IIIA and IIIB NSCLC patients treated with biological therapy with patients undergoing standard induction chemotherapy. Data reported are preliminary results on the safety and effectiveness of surgery after target therapy. Results: We compared 22 patients treated with standard chemotherapy (Group 1) and 6 patients who received target therapy (Group 2). No differences were observed with an important bias due to the limited number of cases. The median time of resection was 159.8 ± 62.8 for group 1 and 201 ± 57.8 for group 2 (p=0.194). Complete resection was obtained in all Group 1-cases. Post-operative complication rate was 22% vs 16% (p=1). Pathologists reported necrosis >50% in 13% in group 1, Fibrosis >50% was presents respectively in 27% and 33% of patients (p=1). Residual vital tumor was >50% in 77% of patients undergone CT and in 66% of patients undergone TT (p=0.622). A total of 6 (31%) patients in the CT-group developed recurrence, 3 in the TT- group (64.2%), p was 0.634. No difference was observed both in terms of OS (P=0.29, Figure 3) and in term of DFS (P=0.106, Figure 4). Discussion: There is no consensus in the use of target therapy for advanced tumor in association with surgery. EGFR-tyrosine kinase inhibitors showed higher and more rapid response and our study wants to demonstrate that surgery after target therapy gives full access to the advantage of definitive local treatment. In our series, despite fibrosis, radical surgery has been achieved in all patients operated. The intraoperative blood loss, operation time, postoperative hospital stay and postoperative complication rate seems to be similar.

Towards the conservation of vulnerable marine large predators: morphometric, molecular and microchemical variation of historical sawfish rostra from Mediterranean collections

Sawfishes (Chondrichthyes, Pristidae) are considered one of the most endangered families among elasmobranchs. Extensive efforts are required worldwide to gather solid information on historical and recent changes in the composition/range of species. In this study, we have implemented an integrative approach to characterize the species diversity and the abundance of historical rostra of sawfishes from museums and private collections of the Mediterranean area. The identification at the species level of 172 dried rostra was carried out through the integration of both traditional and geometric morphometric techniques with molecular tools, allowing the assessment of a robust methodical approach to discriminate species. In addition, we analysed 35 rostral teeth to clarify the past distribution of sawfish species considering the isotopic composition of oxygen and carbon. The morphometric, molecular, and geographical characterization of samples was accompanied by the preliminary evaluation of growth structures and the inspection of the strontium isotope composition in two teeth to unravel movement patterns of individuals across different salinities of water. Results were integrated with currently available data from public repositories and showed that the historical specimens belonged to four nominal species: Pristis zijsron (81), Anoxypristis cuspidata (39), P. pristis (30), and P. pectinata (22). An identification error of 5.41% emerged in the morphological distinction of rostra between juvenile individuals of P. pectinata and P. zijsron. The new approach of carbon and oxygen isotopes, implemented for the first time in these taxa, permitted the identification of the high-probability habitat preferences of these benthopelagic elasmobranchs in about 50% of the analysed specimens. Using this multidisciplinary approach, we successfully assigned the numerous museum rostra with lacking data to a given species and identified their candidate geographical origin, retrieving novel information and data for understanding the species distribution and ecology of past, sometimes locally/regionally extinct sawfish faunas.

Robust Adaptive Control with Applications to Multi-Agent Systems and Mobile Robotics

This thesis deals with robust adaptive control and its applications, and it is divided into three main parts. The first part is about the design of robust estimation algorithms based on recursive least squares. First, we present an estimator for the frequencies of biased multi-harmonic signals, and then an algorithm for distributed estimation of an unknown parameter over a network of adaptive agents. In the second part of this thesis, we consider a cooperative control problem over uncertain networks of linear systems and Kuramoto systems, in which the agents have to track the reference generated by a leader exosystem. Since the reference signal is not available to each network node, novel distributed observers are designed so as to reconstruct the reference signal locally for each agent, and therefore decentralizing the problem. In the third and final part of this thesis, we consider robust estimation tasks for mobile robotics applications. In particular, we first consider the problem of slip estimation for agricultural tracked vehicles. Then, we consider a search and rescue application in which we need to drive an unmanned aerial vehicle as close as possible to the unknown (and to be estimated) position of a victim, who is buried under the snow after an avalanche event. In this thesis, robustness is intended as an input-to-state stability property of the proposed identifiers (sometimes referred to as adaptive laws), with respect to additive disturbances, and relative to a steady-state trajectory that is associated with a correct estimation of the unknown parameter to be found.

Multidisciplinary approach to manage the striped venus clam (Chamelea gallina) fisheries

To responsively manage the striped venus clam (Chamelea gallina) fisheries, a multidisciplinary approach has been adopted through the investigation of new and updated biological aspects (e.g. age, growth, reproduction, size at first maturity, fecundity) and the interaction gear- target or non-target species (e.g. reburial ability, survival potential and exerted damage). The striped venus clam is an important socio-economic species in the Italian fishery context, highly regulated by national and international laws aiming at guaranteeing both social and ecological sustainability. Studies on growth and reproduction revealed that the size at first maturity is reached within the first year of life, whereas the present Minimum Conservation Reference Size of 22 mm is reached at two year of age. The annual reproductive cycle, which is driven by rises in seawater temperature and chlorophyll-a concentration, spans during the warmer months (late spring-summer) with multiple spawning events of different intensity occurring over the spawning period, and the number of potentially emitted gametes is positively related to shell size. Reburial tests conducted on undamaged specimens highlighted the ability of clams to rebury in the sediment once discarded, independently from the size. On the other hand, survival experiments in the laboratory and at sea, on both damaged and undamaged individuals, served to demonstrate that the species has a high survival rate, thus supporting the claim that discarded individuals can contribute to restock the natural populations. Moreover, the evaluation and quantification of damage induced by dredging on the discarded macro-benthic fauna living associated with C. gallina highlighted that soft-shelled or soft-bodied species are the most affected by the fishing process and subjected to a higher mortality. All these findings are of pivotal importance to rationally support the management measures to be adopted in the striped venus clam fishery.

Multidisciplinary approach to horse welfare in different management systems

From its domestication until nowadays, the horse has assumed multiple roles in human society. Over time, this condition and the lack of specific regulation have led to the development of different kinds of management systems for this species. This Ph.D. research project aims to investigate horses' welfare in different management practices and housing systems, considering a multidisciplinary approach, taking into account biological function, naturalness, and affective dimension. The results are presented in five articles that evidence risk factors that can mine horse welfare, and examine tools and parameters that can be employed for its assessment. Our research shows the importance of considering the evolutionary history and the species-specific and behavioural needs of horses in their management and housing. Sociality, free movement, diet composition and foraging routine, and the workload that these animals undergo are important factors that should be taken into account. Furthermore, this research has evidenced the importance of employing different parameters (e.g., behaviour, endocrinological parameters, and immune activity) in welfare assessment and proposes the use of horsehair DHEA (dehydroepiandrosterone) as a possible useful additional non-invasive measure for the investigation of long-term stress conditions. Finally, our results underline the importance of considering the affective dimension in welfare research. Recently, Judgement Bias Tests (JBT), which are based on the influence of affective states on the decision-making process, have been widely employed in animal welfare research. However, our studies show that the use of spatial JBT in horses can have some limitations. Still today several management systems do not fulfill species-specific needs of horses, thus the implementation of specific regulations could ameliorate horse welfare. A multidisciplinary approach to welfare assessment is fundamental, but it should be always remembered the individual and its own characteristics, which can influence not only physiological, immunological, and behavioural responses but also emotional and cognitive dimensions.