10 resultados para Protein design
em AMS Tesi di Dottorato - Alm@DL - Università di Bologna
Resumo:
Uropathogenic Escherichia coli (UPEC) accounts for approximately 85% of all urinary tract infections (UTIs), causing a global economic burden. E. coli is one of the pathogens mentioned in the ESKAPEE list drafted by OMS, meaning that the increasing antibiotic resistance acquired by UPEC is and will be a serious health problem in the future. Amongst the immunogenic antigens exposed on the surface of UPEC, FimH represent a potential target for vaccine development, since it is involved in the early stages of infection. As already demonstrated, immunizations with FimH elicit functional antibodies that prevent UPEC infections even though the number of doses required to elicit a strong immune response is not optimal. In this work, we aimed to stabilize FimH as a soluble recombinant antigen exploiting the donor strand complementation mechanism by generating different chimeric constructs constituted by FimH and FimG donor strand. To explore the potential of self-assembling nanoparticles to display FimH through genetic fusion, different constructs have been computationally designed and produced. In this work a structure-based design, using available crystal structures of FimH and three different NPs was performed to generate different constructs with optimized properties. Despite the different conditions tested, all the constructs designed (single antigen or chimeric NPs), resulted to be un-soluble proteins in E. coli. To overcome this issue a mammalian expression system has been tested. Soluble antigen expression was achieved for all constructs tested in the culture supernatants. Three novel chimeric NPs have been characterized by transmission electron microscopy (TEM) confirming the presence of correctly assembled NPs displaying UPEC antigen. In vivo study has shown a higher immunogenicity of the E. coli antigen when displayed on NPs surface compared to the single recombinant antigen. The antibodies elicited by chimeric NPs showed a higher functionality in the inhibition of bacterial adhesion.
Resumo:
The continuous increase of genome sequencing projects produced a huge amount of data in the last 10 years: currently more than 600 prokaryotic and 80 eukaryotic genomes are fully sequenced and publically available. However the sole sequencing process of a genome is able to determine just raw nucleotide sequences. This is only the first step of the genome annotation process that will deal with the issue of assigning biological information to each sequence. The annotation process is done at each different level of the biological information processing mechanism, from DNA to protein, and cannot be accomplished only by in vitro analysis procedures resulting extremely expensive and time consuming when applied at a this large scale level. Thus, in silico methods need to be used to accomplish the task. The aim of this work was the implementation of predictive computational methods to allow a fast, reliable, and automated annotation of genomes and proteins starting from aminoacidic sequences. The first part of the work was focused on the implementation of a new machine learning based method for the prediction of the subcellular localization of soluble eukaryotic proteins. The method is called BaCelLo, and was developed in 2006. The main peculiarity of the method is to be independent from biases present in the training dataset, which causes the over‐prediction of the most represented examples in all the other available predictors developed so far. This important result was achieved by a modification, made by myself, to the standard Support Vector Machine (SVM) algorithm with the creation of the so called Balanced SVM. BaCelLo is able to predict the most important subcellular localizations in eukaryotic cells and three, kingdom‐specific, predictors were implemented. In two extensive comparisons, carried out in 2006 and 2008, BaCelLo reported to outperform all the currently available state‐of‐the‐art methods for this prediction task. BaCelLo was subsequently used to completely annotate 5 eukaryotic genomes, by integrating it in a pipeline of predictors developed at the Bologna Biocomputing group by Dr. Pier Luigi Martelli and Dr. Piero Fariselli. An online database, called eSLDB, was developed by integrating, for each aminoacidic sequence extracted from the genome, the predicted subcellular localization merged with experimental and similarity‐based annotations. In the second part of the work a new, machine learning based, method was implemented for the prediction of GPI‐anchored proteins. Basically the method is able to efficiently predict from the raw aminoacidic sequence both the presence of the GPI‐anchor (by means of an SVM), and the position in the sequence of the post‐translational modification event, the so called ω‐site (by means of an Hidden Markov Model (HMM)). The method is called GPIPE and reported to greatly enhance the prediction performances of GPI‐anchored proteins over all the previously developed methods. GPIPE was able to predict up to 88% of the experimentally annotated GPI‐anchored proteins by maintaining a rate of false positive prediction as low as 0.1%. GPIPE was used to completely annotate 81 eukaryotic genomes, and more than 15000 putative GPI‐anchored proteins were predicted, 561 of which are found in H. sapiens. In average 1% of a proteome is predicted as GPI‐anchored. A statistical analysis was performed onto the composition of the regions surrounding the ω‐site that allowed the definition of specific aminoacidic abundances in the different considered regions. Furthermore the hypothesis that compositional biases are present among the four major eukaryotic kingdoms, proposed in literature, was tested and rejected. All the developed predictors and databases are freely available at: BaCelLo http://gpcr.biocomp.unibo.it/bacello eSLDB http://gpcr.biocomp.unibo.it/esldb GPIPE http://gpcr.biocomp.unibo.it/gpipe
Resumo:
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.
Resumo:
The aspartic protease BACE1 (β-amyloid precursor protein cleaving enzyme, β-secretase) is recognized as one of the most promising targets in the treatment of Alzheimer's disease (AD). The accumulation of β-amyloid peptide (Aβ) in the brain is a major factor in the pathogenesis of AD. Aβ is formed by initial cleavage of β-amyloid precursor protein (APP) by β-secretase, therefore BACE1 inhibition represents one of the therapeutic approaches to control progression of AD, by preventing the abnormal generation of Aβ. For this reason, in the last decade, many research efforts have focused at the identification of new BACE1 inhibitors as drug candidates. Generally, BACE1 inhibitors are grouped into two families: substrate-based inhibitors, designed as peptidomimetic inhibitors, and non-peptidomimetic ones. The research on non-peptidomimetic small molecules BACE1 inhibitors remains the most interesting approach, since these compounds hold an improved bioavailability after systemic administration, due to a good blood-brain barrier permeability in comparison to peptidomimetic inhibitors. Very recently, our research group discovered a new promising lead compound for the treatment of AD, named lipocrine, a hybrid derivative between lipoic acid and the AChE inhibitor (AChEI) tacrine, characterized by a tetrahydroacridinic moiety. Lipocrine is one of the first compounds able to inhibit the catalytic activity of AChE and AChE-induced amyloid-β aggregation and to protect against reactive oxygen species. Due to this interesting profile, lipocrine was also evaluated for BACE1 inhibitory activity, resulting in a potent lead compound for BACE1 inhibition. Starting from this interesting profile, a series of tetrahydroacridine analogues were synthesised varying the chain length between the two fragments. Moreover, following the approach of combining in a single molecule two different pharmacophores, we designed and synthesised different compounds bearing the moieties of known AChEIs (rivastigmine and caproctamine) coupled with lipoic acid, since it was shown that dithiolane group is an important structural feature of lipocrine for the optimal inhibition of BACE1. All the tetrahydroacridines, rivastigmine and caproctamine-based compounds, were evaluated for BACE1 inhibitory activity in a FRET (fluorescence resonance energy transfer) enzymatic assay (test A). With the aim to enhancing the biological activity of the lead compound, we applied the molecular simplification approach to design and synthesize novel heterocyclic compounds related to lipocrine, in which the tetrahydroacridine moiety was replaced by 4-amino-quinoline or 4-amino-quinazoline rings. All the synthesized compounds were also evaluated in a modified FRET enzymatic assay (test B), changing the fluorescent substrate for enzymatic BACE1 cleavage. This test method guided deep structure-activity relationships for BACE1 inhibition on the most promising quinazoline-based derivatives. By varying the substituent on the 2-position of the quinazoline ring and by replacing the lipoic acid residue in lateral chain with different moieties (i.e. trans-ferulic acid, a known antioxidant molecule), a series of quinazoline derivatives were obtained. In order to confirm inhibitory activity of the most active compounds, they were evaluated with a third FRET assay (test C) which, surprisingly, did not confirm the previous good activity profiles. An evaluation study of kinetic parameters of the three assays revealed that method C is endowed with the best specificity and enzymatic efficiency. Biological evaluation of the modified 2,4-diamino-quinazoline derivatives measured through the method C, allow to obtain a new lead compound bearing the trans-ferulic acid residue coupled to 2,4-diamino-quinazoline core endowed with a good BACE1 inhibitory activity (IC50 = 0.8 mM). We reported on the variability of the results in the three different FRET assays that are known to have some disadvantages in term of interference rates that are strongly dependent on compound properties. The observed results variability could be also ascribed to different enzyme origin, varied substrate and different fluorescent groups. The inhibitors should be tested on a parallel screening in order to have a more reliable data prior to be tested into cellular assay. With this aim, preliminary cellular BACE1 inhibition assay carried out on lipocrine confirmed a good cellular activity profile (EC50 = 3.7 mM) strengthening the idea to find a small molecule non-peptidomimetic compound as BACE1 inhibitor. In conclusion, the present study allowed to identify a new lead compound endowed with BACE1 inhibitory activity in submicromolar range. Further lead optimization to the obtained derivative is needed in order to obtain a more potent and a selective BACE1 inhibitor based on 2,4-diamino-quinazoline scaffold. A side project related to the synthesis of novel enzymatic inhibitors of BACE1 in order to explore the pseudopeptidic transition-state isosteres chemistry was carried out during research stage at Università de Montrèal (Canada) in Hanessian's group. The aim of this work has been the synthesis of the δ-aminocyclohexane carboxylic acid motif with stereochemically defined substitution to incorporating such a constrained core in potential BACE1 inhibitors. This fragment, endowed with reduced peptidic character, is not known in the context of peptidomimetic design. In particular, we envisioned an alternative route based on an organocatalytic asymmetric conjugate addition of nitroalkanes to cyclohexenone in presence of D-proline and trans-2,5-dimethylpiperazine. The enantioenriched obtained 3-(α-nitroalkyl)-cyclohexanones were further functionalized to give the corresponding δ-nitroalkyl cyclohexane carboxylic acids. These intermediates were elaborated to the target structures 3-(α-aminoalkyl)-1-cyclohexane carboxylic acids in a new readily accessible way.
Resumo:
Alzheimer's disease (AD) and cancer represent two of the main causes of death worldwide. They are complex multifactorial diseases and several biochemical targets have been recognized to play a fundamental role in their development. Basing on their complex nature, a promising therapeutical approach could be represented by the so-called "Multi-Target-Directed Ligand" approach. This new strategy is based on the assumption that a single molecule could hit several targets responsible for the onset and/or progression of the pathology. In particular in AD, most currently prescribed drugs aim to increase the level of acetylcholine in the brain by inhibiting the enzyme acetylcholinesterase (AChE). However, clinical experience shows that AChE inhibition is a palliative treatment, and the simple modulation of a single target does not address AD aetiology. Research into newer and more potent anti-AD agents is thus focused on compounds whose properties go beyond AChE inhibition (such as inhibition of the enzyme β-secretase and inhibition of the aggregation of beta-amyloid). Therefore, the MTDL strategy seems a more appropriate approach for addressing the complexity of AD and may provide new drugs for tackling its multifactorial nature. In this thesis, it is described the design of new MTDLs able to tackle the multifactorial nature of AD. Such new MTDLs designed are less flexible analogues of Caproctamine, one of the first MTDL owing biological properties useful for the AD treatment. These new compounds are able to inhibit the enzymes AChE, beta-secretase and to inhibit both AChE-induced and self-induced beta-amyloid aggregation. In particular, the most potent compound of the series is able to inhibit AChE in subnanomolar range, to inhibit β-secretase in micromolar concentration and to inhibit both AChE-induced and self-induced beta-amyloid aggregation in micromolar concentration. Cancer, as AD, is a very complex pathology and many different therapeutical approaches are currently use for the treatment of such pathology. However, due to its multifactorial nature the MTDL approach could be, in principle, apply also to this pathology. Aim of this thesis has been the development of new molecules owing different structural motifs able to simultaneously interact with some of the multitude of targets responsible for the pathology. The designed compounds displayed cytotoxic activity in different cancer cell lines. In particular, the most potent compounds of the series have been further evaluated and they were able to bind DNA resulting 100-fold more potent than the reference compound Mitonafide. Furthermore, these compounds were able to trigger apoptosis through caspases activation and to inhibit PIN1 (preliminary result). This last protein is a very promising target because it is overexpressed in many human cancers, it functions as critical catalyst for multiple oncogenic pathways and in several cancer cell lines depletion of PIN1 determines arrest of mitosis followed by apoptosis induction. In conclusion, this study may represent a promising starting pint for the development of new MTDLs hopefully useful for cancer and AD treatment.
Design, synthesis and biological evaluation of substituted naphthalene diimides as anticancer agents
Resumo:
It has been proved that naphthalene diimide (NDI) derivatives display anticancer properties as intercalators and G-quadruplex-binding ligands, leading to DNA damage, senescence and down-regulation of oncogene expression. This thesis deals with the design and synthesis of disubstituted and tetrasubstituted NDI derivatives endowed with anticancer activity, interacting with DNA together with other targets implicated in cancer development. Disubstituted NDI compounds have been designed with the aim to provide potential multitarget directed ligands (MTDLs), in order to create molecules able to simultaneously interact with some of the different targets involved in this pathology. The most active compound, displayed antiproliferative activity in submicromolar range, especially against colon and prostate cancer cell lines, the ability to bind duplex and quadruplex DNA, to inhibit Taq polymerase and telomerase, to trigger caspase activation by a possible oxidative mechanism, to downregulate ERK 2 protein and to inhibit ERKs phosphorylation, without acting directly on microtubules and tubuline. Tetrasubstituted NDI compounds have been designed as G-quadruplex-binding ligands endowed with anticancer activity. In order to improve the cellular uptake of the lead compound, the N-methylpiperazine moiety have been replaced with different aromatic systems and methoxypropyl groups. The most interesting compound was 1d, which was able to interact with the G-quadruplexes both telomeric and in HSP90 promoter region, and it has been co-crystallized with the human telomeric G-quadruplex, to directly verify its ability to bind this kind of structure, and also to investigate its binding mode. All the morpholino substituted compounds show antiproliferative activity in submicromolar values mainly in pancreatic and lung cancer cell lines, and they show an improved biological profile in comparison with that of the lead compound. In conclusion, both these studies, may represent a promising starting point for the development of new interesting molecules useful for the treatment of cancer, underlining the versatility of the NDI scaffold.
Resumo:
In 2017, Chronic Respiratory Diseases accounted for almost four million deaths worldwide. Unfortunately, current treatments are not definitive for such diseases. This unmet medical need forces the scientific community to increase efforts in the identification of new therapeutic solutions. PI3K delta plays a key role in mechanisms that promote airway chronic inflammation underlying Asthma and COPD. The first part of this project was dedicated to the identification of novel PI3K delta inhibitors. A first SAR expansion of a Hit, previously identified by a HTS campaign, was carried out. A library of 43 analogues was synthesised taking advantage of an efficient synthetic approach. This allowed the identification of an improved Hit of nanomolar enzymatic potency and moderate selectivity for PI3K delta over other PI3K isoforms. However, this compound exhibited low potency in cell-based assays. Low cellular potency was related to sub optimal phys-chem and ADME properties. The analysis of the X-ray crystal structure of this compound in human PI3K delta guided a second tailored SAR expansion that led to improved cellular potency and solubility. The second part of the thesis was focused on the rational design and synthesis of new macrocyclic Rho-associated protein kinases (ROCKs) inhibitors. Inhibition of these kinases has been associated with vasodilating effects. Therefore, ROCKs could represent attractive targets for the treatment of pulmonary arterial hypertension (PAH). Known ROCK inhibitors suffer from low selectivity across the kinome. The design of macrocyclic inhibitors was considered a promising strategy to obtain improved selectivity. Known inhibitors from literature were evaluated for opportunities of macrocyclization using a knowledge-based approach supported by Computer Aided Drug Design (CADD). The identification of a macrocyclic ROCK inhibitor with enzymatic activity in the low micro molar range against ROCK II represented a promising result that validated this innovative approach in the design of new ROCKs inhibitors.
Resumo:
In Cystic Fibrosis (CF) the deletion of phenylalanine 508 (F508del) in the CFTR anion channel is associated to misfolding and defective gating of the mutant protein. Among the known proteins involved in CFTR processing, one of the most promising drug target is the ubiquitin ligase RNF5, which normally promotes F508del-CFTR degradation. In this context, a small molecule RNF5 inhibitor is expected to chemically mimic a condition of RNF5 silencing, thus preventing mutant CFTR degradation and causing its stabilization and plasma membrane trafficking. Hence, by exploiting a virtual screening (VS) campaign, the hit compound inh-2 was discovered as the first-in-class inhibitor of RNF5. Evaluation of inh-2 efficacy on CFTR rescue showed that it efficiently decreases ubiquitination of mutant CFTR and increases chloride current in human primary bronchial epithelia. Based on the promising biological results obtained with inh-2, this thesis reports the structure-based design of potential RNF5 inhibitors having improved potency and efficacy. The optimization of general synthetic strategies gave access to a library of analogues of the 1,2,4-thiadiazol-5-ylidene inh-2 for SAR investigation. The new analogues were tested for their corrector activity in CFBE41o- cells by using the microfluorimetric HS-YFP assay as a primary screen. Then, the effect of putative RNF5 inhibitors on proliferation, apoptosis and the formation of autophagic vacuoles was evaluated. Some of the new analogs significantly increased the basal level of autophagy, reproducing RNF5 silencing effect in cell. Among them, one compound also displayed a greater rescue of the F508del-CFTR trafficking defect than inh-2. Our preliminary results suggest that the 1,2,4-thiadiazolylidene could be a suitable scaffold for the discovery of potential RNF5 inhibitors able to rescue mutant CFTRs. Biological tests are still ongoing to acquire in-depth knowledge about the mechanism of action and therapeutic relevance of this unprecedented pharmacological strategy.
Resumo:
Neuronal microtubules assembly and dynamics are regulated by several proteins including (MT)-associated protein tau, whose aberrant hyperphosphorylation promotes its dissociation from MTs and its abnormal deposition into neurofibrillary tangles, a common neurotoxic hallmarks of neurodegenerative tauopathies. To date, no disease-modifying drugs have been approved to combat CNS tau-related diseases. The multifactorial etiology of these conditions represents one of the major limits in the discovery of effective therapeutic options. In addition, tau protein functions are orchestrated by diverse post-translational modifications among which phosphorylation mediated by PKs plays a leading role. In this context, conventional single-target therapies are often inadequate in restoring perturbed networks and fraught with adverse side-effects. This thesis reports two distinct approaches to hijack MT defects in neurons. The first is focused on the rational design and synthesis of first-in-class triple inhibitors of GSK-3β, FYN, and DYRK1A, three close-related PKs, which act as master regulators of aberrant tau hyperphosphorylation. A merged multi-target pharmacophore strategy was applied to simultaneously modulate all three targets and achieve a disease-modifying effect. Optimization of ARN25068 by a computationally and crystallographic driven SAR exploration, allowed to rationalize the key structural modifications to maintain a balanced potency against all three targets and develop a new generation of quite well-balanced analogs exhibiting improved physicochemical properties, a good in vitro ADME profile, and promising cell-based anti-tau phosphorylation activity. In Part II, MT-stabilizing compounds have been developed to compensate MT defects in tau-related pathologies. Intensive chemical effort has been devoted to scaling up BL-0884, identified as a promising MT-normalizing TPD, which exhibited favorable ADME-PK, including brain penetration, oral bioavailability, and brain pharmacodynamic activity. A suitable functionalization of the exposed hydroxyl moiety of BL-0884 was carried out to generate corresponding esters and amides possessing a wide range of applications as prodrugs and active targeting for cancer chemotherapy.
Resumo:
Neuroinflammation represents a key hallmark of neurodegenerative diseases and is the result of a complex network of signaling cascades within microglial cells. A positive feedback loop exists between inflammation, microglia activation and protein misfolding processes, that, together with oxidative stress and excitotoxicity, lead to neuronal degeneration. Therefore, targeting this vicious cycle can be beneficial for mitigating neurodegeneration and cognitive decline in central nervous system disorders. At molecular level, GSK-3B and Fyn kinases play a crucial role in microglia activation and their deregulation has been associated to many neurodegenerative diseases. Thus, we envisioned their combined targeting as an effective approach to disrupt this toxic loop. Specifically in this project, a hit compound, based on a 7-azaindole-3-aminothiazole structure, was first identified in a virtual screening campaign, and displayed a weak dual inhibitory activity on GSK-3B and Fyn, unbalanced towards the former. Then, in a commitment to uncover the structural features required for modulating the activity on the two targets, we systematically manipulated this compound by inserting various substitution patterns in different positions. The most potent compounds obtained were advanced to deeper investigations to test their ability of tackling the inflammatory burden also in cellular systems and to unveil their binding modes within the catalytic pocket. The new class of molecules synthesized emerged as a valuable tool to deepen our understanding of the complex network governing the inflammatory events in neurodegenerative disorders.