Machine-learning methods for structure prediction of β-barrel membrane proteins

Different types of proteins exist with diverse functions that are essential for living organisms. An important class of proteins is represented by transmembrane proteins which are specifically designed to be inserted into biological membranes and devised to perform very important functions in the cell such as cell communication and active transport across the membrane. Transmembrane β-barrels (TMBBs) are a sub-class of membrane proteins largely under-represented in structure databases because of the extreme difficulty in experimental structure determination. For this reason, computational tools that are able to predict the structure of TMBBs are needed. In this thesis, two computational problems related to TMBBs were addressed: the detection of TMBBs in large datasets of proteins and the prediction of the topology of TMBB proteins. Firstly, a method for TMBB detection was presented based on a novel neural network framework for variable-length sequence classification. The proposed approach was validated on a non-redundant dataset of proteins. Furthermore, we carried-out genome-wide detection using the entire Escherichia coli proteome. In both experiments, the method significantly outperformed other existing state-of-the-art approaches, reaching very high PPV (92%) and MCC (0.82). Secondly, a method was also introduced for TMBB topology prediction. The proposed approach is based on grammatical modelling and probabilistic discriminative models for sequence data labeling. The method was evaluated using a newly generated dataset of 38 TMBB proteins obtained from high-resolution data in the PDB. Results have shown that the model is able to correctly predict topologies of 25 out of 38 protein chains in the dataset. When tested on previously released datasets, the performances of the proposed approach were measured as comparable or superior to the current state-of-the-art of TMBB topology prediction.

Computational analyses on the structure-function relation in ion channels

Ion channels are protein molecules, embedded in the lipid bilayer of the cell membranes. They act as powerful sensing elements switching chemicalphysical stimuli into ion-fluxes. At a glance, ion channels are water-filled pores, which can open and close in response to different stimuli (gating), and one once open select the permeating ion species (selectivity). They play a crucial role in several physiological functions, like nerve transmission, muscular contraction, and secretion. Besides, ion channels can be used in technological applications for different purpose (sensing of organic molecules, DNA sequencing). As a result, there is remarkable interest in understanding the molecular determinants of the channel functioning. Nowadays, both the functional and the structural characteristics of ion channels can be experimentally solved. The purpose of this thesis was to investigate the structure-function relation in ion channels, by computational techniques. Most of the analyses focused on the mechanisms of ion conduction, and the numerical methodologies to compute the channel conductance. The standard techniques for atomistic simulation of complex molecular systems (Molecular Dynamics) cannot be routinely used to calculate ion fluxes in membrane channels, because of the high computational resources needed. The main step forward of the PhD research activity was the development of a computational algorithm for the calculation of ion fluxes in protein channels. The algorithm - based on the electrodiffusion theory - is computational inexpensive, and was used for an extensive analysis on the molecular determinants of the channel conductance. The first record of ion-fluxes through a single protein channel dates back to 1976, and since then measuring the single channel conductance has become a standard experimental procedure. Chapter 1 introduces ion channels, and the experimental techniques used to measure the channel currents. The abundance of functional data (channel currents) does not match with an equal abundance of structural data. The bacterial potassium channel KcsA was the first selective ion channels to be experimentally solved (1998), and after KcsA the structures of four different potassium channels were revealed. These experimental data inspired a new era in ion channel modeling. Once the atomic structures of channels are known, it is possible to define mathematical models based on physical descriptions of the molecular systems. These physically based models can provide an atomic description of ion channel functioning, and predict the effect of structural changes. Chapter 2 introduces the computation methods used throughout the thesis to model ion channels functioning at the atomic level. In Chapter 3 and Chapter 4 the ion conduction through potassium channels is analyzed, by an approach based on the Poisson-Nernst-Planck electrodiffusion theory. In the electrodiffusion theory ion conduction is modeled by the drift-diffusion equations, thus describing the ion distributions by continuum functions. The numerical solver of the Poisson- Nernst-Planck equations was tested in the KcsA potassium channel (Chapter 3), and then used to analyze how the atomic structure of the intracellular vestibule of potassium channels affects the conductance (Chapter 4). As a major result, a correlation between the channel conductance and the potassium concentration in the intracellular vestibule emerged. The atomic structure of the channel modulates the potassium concentration in the vestibule, thus its conductance. This mechanism explains the phenotype of the BK potassium channels, a sub-family of potassium channels with high single channel conductance. The functional role of the intracellular vestibule is also the subject of Chapter 5, where the affinity of the potassium channels hEag1 (involved in tumour-cell proliferation) and hErg (important in the cardiac cycle) for several pharmaceutical drugs was compared. Both experimental measurements and molecular modeling were used in order to identify differences in the blocking mechanism of the two channels, which could be exploited in the synthesis of selective blockers. The experimental data pointed out the different role of residue mutations in the blockage of hEag1 and hErg, and the molecular modeling provided a possible explanation based on different binding sites in the intracellular vestibule. Modeling ion channels at the molecular levels relates the functioning of a channel to its atomic structure (Chapters 3-5), and can also be useful to predict the structure of ion channels (Chapter 6-7). In Chapter 6 the structure of the KcsA potassium channel depleted from potassium ions is analyzed by molecular dynamics simulations. Recently, a surprisingly high osmotic permeability of the KcsA channel was experimentally measured. All the available crystallographic structure of KcsA refers to a channel occupied by potassium ions. To conduct water molecules potassium ions must be expelled from KcsA. The structure of the potassium-depleted KcsA channel and the mechanism of water permeation are still unknown, and have been investigated by numerical simulations. Molecular dynamics of KcsA identified a possible atomic structure of the potassium-depleted KcsA channel, and a mechanism for water permeation. The depletion from potassium ions is an extreme situation for potassium channels, unlikely in physiological conditions. However, the simulation of such an extreme condition could help to identify the structural conformations, so the functional states, accessible to potassium ion channels. The last chapter of the thesis deals with the atomic structure of the !- Hemolysin channel. !-Hemolysin is the major determinant of the Staphylococcus Aureus toxicity, and is also the prototype channel for a possible usage in technological applications. The atomic structure of !- Hemolysin was revealed by X-Ray crystallography, but several experimental evidences suggest the presence of an alternative atomic structure. This alternative structure was predicted, combining experimental measurements of single channel currents and numerical simulations. This thesis is organized in two parts, in the first part an overview on ion channels and on the numerical methods adopted throughout the thesis is provided, while the second part describes the research projects tackled in the course of the PhD programme. The aim of the research activity was to relate the functional characteristics of ion channels to their atomic structure. In presenting the different research projects, the role of numerical simulations to analyze the structure-function relation in ion channels is highlighted.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

Trasporto di materia in membrane polimeriche e nanocomposite per la separazione di gas

Membrane-based separation processes are acquiring, in the last years, an increasing importance because of their intrinsic energetic and environmental sustainability: some types of polymeric materials, showing adequate perm-selectivity features, appear rather suitable for these applications, because of their relatively low cost and easy processability. In this work have been studied two different types of polymeric membranes, in view of possible applications to the gas separation processes, i.e. Mixed Matrix Membranes (MMMs) and high free volume glassy polymers. Since the early 90’s, it has been understood that the performances of polymeric materials in the field of gas separations show an upper bound in terms of permeability and selectivity: in particular, an increase of permeability is often accompanied by a decrease of selectivity and vice-versa, while several inorganic materials, like zeolites or silica derivates, can overcome this limitation. As a consequence, it has been developed the idea of dispersing inorganic particles in polymeric matrices, in order to obtain membranes with improved perm-selectivity features. In particular, dispersing fumed silica nanoparticles in high free volume glassy polymers improves in all the cases gases and vapours permeability, while the selectivity may either increase or decrease, depending upon material and gas mixture: that effect is due to the capacity of nanoparticles to disrupt the local chain packing, increasing the dimensions of excess free volume elements trapped in the polymer matrix. In this work different kinds of MMMs were fabricated using amorphous Teflon® AF or PTMSP and fumed silica: in all the cases, a considerable increase of solubility, diffusivity and permeability of gases and vapours (n-alkanes, CO2, methanol) was observed, while the selectivity shows a non-monotonous trend with filler fraction. Moreover, the classical models for composites are not able to capture the increase of transport properties due to the silica addition, so it has been necessary to develop and validate an appropriate thermodynamic model that allows to predict correctly the mass transport features of MMMs. In this work, another material, called poly-trimethylsilyl-norbornene (PTMSN) was examined: it is a new generation high free volume glassy polymer that, like PTMSP, shows unusual high permeability and selectivity levels to the more condensable vapours. These two polymer differ each other because PTMSN shows a more pronounced chemical stability, due to its structure double-bond free. For this polymer, a set of Lattice Fluid parameters was estimated, making possible a comparison between experimental and theoretical solubility isotherms for hydrocarbons and alcoholic vapours: the successfully modelling task, based on application of NELF model, offers a reliable alternative to direct sorption measurement, which is extremely time-consuming due to the relevant relaxation phenomena showed by each sorption step. For this material also dilation experiments were performed, in order to quantify its dimensional stability in presence of large size, swelling vapours.

Composti organostannici nell'ambiente marino e membrane biologiche: risposte molecolari e biochimiche nei molluschi bivalvi

Organotin compounds are worldwide diffused environmental contaminants, mainly as consequence of their extensive past use as biocides in antifouling paints. In spite of law restrictions, due to unwanted effects, organotin still persist in waters, being poorly degraded, easily resuspended from sediments and bioaccumulated in exposed organisms. The widespread toxicity and the possible threat to humans, likely to be organotin-exposed through contaminated seafood, make organotin interactions with biomolecules an intriguing biochemical topic, apart from a matter of ecotoxicological concern. Among organotins, tributyltin (TBT) is long known as the most dangerous and abundant chemical species in the Mediterranean Sea. Due to its amphiphilic nature, provided by three lipophilic arms and an electrophilic tin core, TBT can be easily incorporated in biomembranes and affect their functionality. Accordingly, it is known as a membrane-active toxicant and a mitochondrial poison. Up to now the molecular action modes of TBT are still partially unclear and poorly explored in bivalve mollusks, even if the latter play a not neglectable role in the marine trophic chain and efficiently accumulate organotins. The bivalve mollusk Mytilus galloprovincialis, selected for all experiments, is widely cultivated in the Mediterranean and currently used in ecotoxicological studies. Most work of this thesis was devoted to TBT effects on mussel mitochondria, but other possible targets of TBT were also considered. A great deal of literature points out TBT as endocrine disrupter and the masculinization of female marine gastropods, the so-called imposex, currently signals environmental organotin contamination. The hormonal status of TBT-exposed mussels and the possible interaction between hormones and contaminants in modulating microsomal hydroxilases, involved in steroid hormone and organotin detoxification, were the research topics in the period spent in Barcelona (Marco Polo fellowship). The variegated experimental approach, which consisted of two exposure experiments and in vitro tests, and the choice of selected tissues of M. galloprovincialis, the midgut gland for mitochondrial and microsomal preparations for subsequent laboratory assays and the gonads for the endocrine evaluations, aimed at drawing a clarifying pattern on the molecular mechanisms involved in organotin toxicity. TBT was promptly incorporated in midgut gland mitochondria of adult mussels exposed to 0.5 and 1.0 μg/L TBT, and partially degraded to DBT. TBT incorporation was accompanied by a decrease in the mitochondrial oligomycin-sensitive Mg-ATPase activity, while the coexistent oligomycin-insensitive fraction was unaffected. Mitochondrial fatty acids showed a clear rise in n-3 polyunsaturated fatty acids after 120 hr of TBT exposure, mainly referable to an increase in 22:6 level. TBT was also shown to inhibit the ATP hydrolytic activity of the mitochondrial F1FO complex in vitro and to promote an apparent loss of oligomycin sensitivity at higher than 1.0 μM concentration. The complex dose-dependent profile of the inhibition curve lead to the hypothesis of multiple TBT binding sites. At lower than 1.0 μM TBT concentrations the non competitive enzyme inhibition by TBT was ascribed to the non covalent binding of TBT to FO subunit. On the other hand the observed drop in oligomycin sensitivity at higher than 1.0 μM TBT could be related to the onset of covalent bonds involving thiolic groups on the enzyme structure, apparently reached only at high TBT levels. The mitochondrial respiratory complexes were in vitro affected by TBT, apart from the cytocrome c oxidase which was apparently refractory to the contaminant. The most striking inhibitory effect was shown on complex I, and ascribed to possible covalent bonds of TBT with –SH groups on the enzyme complexes. This mechanism, shouldered by the progressive decrease of free cystein residues in the presence of increasing TBT concentrations, suggests that the onset of covalent tin-sulphur bonds in distinct protein structures may constitute the molecular basis of widespread TBT effects on mitochondrial complexes. Energy production disturbances, in turn affecting energy consuming mechanisms, could be involved in other cellular changes. Mussels exposed to a wide range of TBT concentrations (20 - 200 and 2000 ng/L respectively) did not show any change in testosterone and estrogen levels in mature gonads. Most hormones were in the non-biologically active esterified form both in control and in TBT-treated mussels. Probably the endocrine status of sexually mature mussels could be refractory even to high TBT doses. In mussel digestive gland the high biological variability of microsomal 7-benzyloxy-4-trifluoromethylcoumarin-O-Debenzyloxylase (BFCOD) activity, taken as a measure of CYP3A-like efficiency, probably concealed any enzyme response to TBT exposure. On the other hand the TBT-driven enhancement of BFCOD activity in vitro was once again ascribed to covalent binding to thiol groups which, in this case, would stimulate the enzyme activity. In mussels from Barcelona harbour, a highly contaminated site, the enzyme showed a decreased affinity for the 7-benzyloxy-4-trifluoromethylcoumarin (BCF) substrate with respect to mussel sampled from Ebro Delta, a non-polluted marine site. Contaminant exposure may thus alter the kinetic features of enzymes involved in detoxification mechanisms. Contaminants and steroid hormones were clearly shown to mutually interact in the modulation of detoxification mechanisms. The xenoestrogen 17α-ethylenyl estradiol (EE2) displayed a non-competitive mixed inhibition of CYP3A-like activity by a preferential bond to the free enzyme both in Barcelona harbour and Ebro Delta mussels. The possible interaction with co-present contaminants in Barcelona harbour mussels apparently lessened the formation of the ternary complex enzyme-EE2-BCF. The whole of data confirms TBT as membrane toxicant in mussels as in other species and stresses TBT covalent binding to protein thiols as a widespread mechanism of membrane-bound-enzyme activity modulation by the contaminant.

The Domon Family of Plant Plasma Membrane B-Type Cytochromes: Heterologous Expression, Biochemical Characterization and Physiological Roles in Vivo

The DOMON domain is a domain widespread in nature, predicted to fold in a β-sandwich structure. In plants, AIR12 is constituted by a single DOMON domain located in the apoplastic space and is GPI-modified for anchoring to the plasma membrane. Arabidopsis thaliana AIR12 has been heterologously expressed as a recombinant protein (recAtAIR12) in Pichia pastoris. Spectrophotometrical analysis of the purified protein showed that recAtAir12 is a cytochrome b. RecAtAIR12 is highly glycosylated, it is reduced by ascorbate, superoxide and naftoquinones, oxidised by monodehydroascorbate and oxygen and insensitive to hydrogen peroxide. The addition of recAtAIR12 to permeabilized plasma membranes containing NADH, FeEDTA and menadione, caused a statistically significant increase in hydroxyl radicals as detected by electron paramagnetic resonance. In these conditions, recAtAIR12 has thus a pro-oxidant role. Interestingly, AIR12 is related to the cytochrome domain of cellobiose dehydrogenase which is involved in lignin degradation, possibly via reactive oxygen species (ROS) production. In Arabidopsis the Air12 promoter is specifically activated at sites where cell separations occur and ROS, including •OH, are involved in cell wall modifications. air12 knock-out plants infected with Botrytis cinerea are more resistant than wild-type and air12 complemented plants. Also during B. cinerea infection, cell wall modifications and ROS are involved. Our results thus suggest that AIR12 could be involved in cell wall modifying reactions by interacting with ROS and ascorbate. CyDOMs are plasma membrane redox proteins of plants that are predicted to contain an apoplastic DOMON fused with a transmembrane cytochrome b561 domain. CyDOMs have never been purified nor characterised. The trans-membrane portion of a soybean CyDOM was expressed in E. coli but purification could not be achieved. The DOMON domain was expressed in P. pastoris and shown to be itself a cytochrome b that could be reduced by ascorbate.

Development and Detailed Characterization of Innovative, High-Performance Membrane Materials for CO2 Capture Processes

The scope of this dissertation is to study the transport phenomena of small molecules in polymers and membranes for gas separation applications, with particular attention to energy efficiency and environmental sustainability. This work seeks to contribute to the development of new competitive selective materials through the characterization of novel organic polymers such as CANALs and ROMPs, as well as through the combination of selective materials obtaining mixed matrix membranes (MMMs), to make membrane technologies competitive with the traditional ones. Kinetic and thermodynamic aspects of the transport properties were investigated in ideal and non-ideal scenarios, such as mixed-gas experiments. The information we gathered contributed to the development of the fundamental understanding related to phenomenon like CO2-induced plasticization and physical aging. Among the most significant results, ZIF-8/PPO MMMs provided materials whose permeability and selectivity were higher than those of the pure materials for He/CO2 separation. The CANALs featured norbornyl benzocyclobutene backbone and thereby introduced a third typology of ladder polymers in the gas separation field, expanding the structural diversity of microporous materials. CANALs have a completely hydrocarbon-based and non-polar rigid backbone, which makes them an ideal model system to investigate structure-property correlations. ROMPs were synthesized by means of the ring opening metathesis living polymerization, which allowed the formation of bottlebrush polymers. CF3-ROMP reveled to be ultrapermeable to CO2, with unprecedented plasticization resistance properties. Mixed-gas experiments in glassy polymer showed that solubility-selectivity controls the separation efficiency of materials in multicomponent conditions. Finally, it was determined that plasticization pressure in not an intrinsic property of a material and does not represent a state of the system, but rather comes from the contribution of solubility coefficient and diffusivity coefficient in the framework of the solution-diffusion model.