Towards in silico prediction of immunogenic epitopes

As torrents of new data now emerge from microbial genomics, bioinformatic prediction of immunogenic epitopes remains challenging but vital. In silico methods often produce paradoxically inconsistent results: good prediction rates on certain test sets but not others. The inherent complexity of immune presentation and recognition processes complicates epitope prediction. Two encouraging developments – data driven artificial intelligence sequence-based methods for epitope prediction and molecular modeling methods based on three-dimensional protein structures – offer hope for the future.

Towards the in silico identification of class II restricted T-cell epitopes:a partial least squares iterative self-consistent algorithm for affinity prediction

Motivation: The immunogenicity of peptides depends on their ability to bind to MHC molecules. MHC binding affinity prediction methods can save significant amounts of experimental work. The class II MHC binding site is open at both ends, making epitope prediction difficult because of the multiple binding ability of long peptides. Results: An iterative self-consistent partial least squares (PLS)-based additive method was applied to a set of 66 pep- tides no longer than 16 amino acids, binding to DRB1*0401. A regression equation containing the quantitative contributions of the amino acids at each of the nine positions was generated. Its predictability was tested using two external test sets which gave r pred =0.593 and r pred=0.655, respectively. Furthermore, it was benchmarked using 25 known T-cell epitopes restricted by DRB1*0401 and we compared our results with four other online predictive methods. The additive method showed the best result finding 24 of the 25 T-cell epitopes. Availability: Peptides used in the study are available from http://www.jenner.ac.uk/JenPep. The PLS method is available commercially in the SYBYL molecular modelling software package. The final model for affinity prediction of peptides binding to DRB1*0401 molecule is available at http://www.jenner.ac.uk/MHCPred. Models developed for DRB1*0101 and DRB1*0701 also are available in MHC- Pred

Efficient HIV-1 inhibition by a 16 nt-long RNA aptamer designed by combining in vitro selection and in silico optimisation strategies

The human immunodeficiency virus type-1 (HIV-1) genome contains multiple, highly conserved structural RNA domains that play key roles in essential viral processes. Interference with the function of these RNA domains either by disrupting their structures or by blocking their interaction with viral or cellular factors may seriously compromise HIV-1 viability. RNA aptamers are amongst the most promising synthetic molecules able to interact with structural domains of viral genomes. However, aptamer shortening up to their minimal active domain is usually necessary for scaling up production, what requires very time-consuming, trial-and-error approaches. Here we report on the in vitro selection of 64 nt-long specific aptamers against the complete 5' -untranslated region of HIV-1 genome, which inhibit more than 75% of HIV-1 production in a human cell line. The analysis of the selected sequences and structures allowed for the identification of a highly conserved 16 nt-long stem-loop motif containing a common 8 nt-long apical loop. Based on this result, an in silico designed 16 nt-long RNA aptamer, termed RNApt16, was synthesized, with sequence 5'-CCCCGGCAAGGAGGGG-3-'. The HIV-1 inhibition efficiency of such an aptamer was close to 85%, thus constituting the shortest RNA molecule so far described that efficiently interferes with HIV-1 replication.

AllerTOP v.2 - a server for in silico prediction of allergens

Allergy is an overreaction by the immune system to a previously encountered, ordinarily harmless substance - typically proteins - resulting in skin rash, swelling of mucous membranes, sneezing or wheezing, or other abnormal conditions. The use of modified proteins is increasingly widespread: their presence in food, commercial products, such as washing powder, and medical therapeutics and diagnostics, makes predicting and identifying potential allergens a crucial societal issue. The prediction of allergens has been explored widely using bioinformatics, with many tools being developed in the last decade; many of these are freely available online. Here, we report a set of novel models for allergen prediction utilizing amino acid E-descriptors, auto- and cross-covariance transformation, and several machine learning methods for classification, including logistic regression (LR), decision tree (DT), naïve Bayes (NB), random forest (RF), multilayer perceptron (MLP) and k nearest neighbours (kNN). The best performing method was kNN with 85.3% accuracy at 5-fold cross-validation. The resulting model has been implemented in a revised version of the AllerTOP server (http://www.ddg-pharmfac.net/AllerTOP). © Springer-Verlag 2014.

A methodological evaluation and predictive in silico investigation into the multi-functionality of arginine in directly compressed tablets

The acceleration of solid dosage form product development can be facilitated by the inclusion of excipients that exhibit poly-/multi-functionality with reduction of the time invested in multiple excipient optimisations. Because active pharmaceutical ingredients (APIs) and tablet excipients present diverse densification behaviours upon compaction, the involvement of these different powders during compaction makes the compaction process very complicated. The aim of this study was to assess the macrometric characteristics and distribution of surface charges of two powders: indomethacin (IND) and arginine (ARG); and evaluate their impact on the densification properties of the two powders. Response surface modelling (RSM) was employed to predict the effect of two independent variables; Compression pressure (F) and ARG percentage (R) in binary mixtures on the properties of resultant tablets. The study looked at three responses namely; porosity (P), tensile strength (S) and disintegration time (T). Micrometric studies showed that IND had a higher charge density (net charge to mass ratio) when compared to ARG; nonetheless, ARG demonstrated good compaction properties with high plasticity (Y=28.01MPa). Therefore, ARG as filler to IND tablets was associated with better mechanical properties of the tablets (tablet tensile strength (σ) increased from 0.2±0.05N/mm2 to 2.85±0.36N/mm2 upon adding ARG at molar ratio of 8:1 to IND). Moreover, tablets' disintegration time was shortened to reach few seconds in some of the formulations. RSM revealed tablet porosity to be affected by both compression pressure and ARG ratio for IND/ARG physical mixtures (PMs). Conversely, the tensile strength (σ) and disintegration time (T) for the PMs were influenced by the compression pressure, ARG ratio and their interactive term (FR); and a strong correlation was observed between the experimental results and the predicted data for tablet porosity. This work provides clear evidence of the multi-functionality of ARG as filler, binder and disintegrant for directly compressed tablets.

AllerTOP - a server for in silico prediction of allergens

Background: Allergy is a form of hypersensitivity to normally innocuous substances, such as dust, pollen, foods or drugs. Allergens are small antigens that commonly provoke an IgE antibody response. There are two types of bioinformatics-based allergen prediction. The first approach follows FAO/WHO Codex alimentarius guidelines and searches for sequence similarity. The second approach is based on identifying conserved allergenicity-related linear motifs. Both approaches assume that allergenicity is a linearly coded property. In the present study, we applied ACC pre-processing to sets of known allergens, developing alignment-independent models for allergen recognition based on the main chemical properties of amino acid sequences.Results: A set of 684 food, 1,156 inhalant and 555 toxin allergens was collected from several databases. A set of non-allergens from the same species were selected to mirror the allergen set. The amino acids in the protein sequences were described by three z-descriptors (z1, z2 and z3) and by auto- and cross-covariance (ACC) transformation were converted into uniform vectors. Each protein was presented as a vector of 45 variables. Five machine learning methods for classification were applied in the study to derive models for allergen prediction. The methods were: discriminant analysis by partial least squares (DA-PLS), logistic regression (LR), decision tree (DT), naïve Bayes (NB) and k nearest neighbours (kNN). The best performing model was derived by kNN at k = 3. It was optimized, cross-validated and implemented in a server named AllerTOP, freely accessible at http://www.pharmfac.net/allertop. AllerTOP also predicts the most probable route of exposure. In comparison to other servers for allergen prediction, AllerTOP outperforms them with 94% sensitivity.Conclusions: AllerTOP is the first alignment-free server for in silico prediction of allergens based on the main physicochemical properties of proteins. Significantly, as well allergenicity AllerTOP is able to predict the route of allergen exposure: food, inhalant or toxin. © 2013 Dimitrov et al.; licensee BioMed Central Ltd.

Construção de bibliotecas de cDNAs subtraídos a partir das sementes de Mamona submetidas à estresse hídrico e análise in silico de transcritos potencialmente expressos sob condições de estresse: Metalotioneina, proteína reprimida por auxina de 12.5 kDa e Glutelina tipo-A3

Estresses ambientais abióticos são fatores que causam respostas ao nível molecular, fisiológico e morfológico em plantas, dependendo também de sua intensidade e duração. É visto que algumas espécies apresentam tolerância a condições estressantes e ao mesmo tempo são fontes naturais de matéria prima para indústria. Nesse contexto encontra-se a mamona (Ricinus comunnis L.), principal fonte de óleo de rícino valorizado por suas aplicações farmacêuticas e principalmente industriais, vem sendo usada como cultura em regiões onde a disponibilidade de água é reduzida, usada como fonte de renda para agricultura da região nordeste brasileira. Visto que pouco se sabe sobre as respostas moleculares que levam essa planta a tolerar regiões secas e como as sementes, principais foco de interesse, respondem a essa escassez, nesse trabalho foram construídas duas bibliotecas de cDNAs, onde a partir de uma abordagem subtrativa, continham RNAs diferencialmente expressos em sementes de plantas mamona submetidas ao estresse hídrico durante 5 dias (biblioteca L7), e a outra RNAs diferencialmente expressos em sementes controle (biblioteca L5). A biblioteca L7 apresentou a maior variedade de transcritos com um total de 182. A maior parte das funções estabelecidas pelo sistema Gene Ontology - GO, foram direcionadas aos “Processos Metabólicos” (526), em segundo “Respostas a estímulos” (57), o terceiro termo mais abundante foram referentes a “Desenvolvimento”(26). Já na biblioteca L5, foram encontrados 91 transcritos, com maior parte de suas funções referentes a “Processos Metabólicos”(413), em segundo “Respostas a estímulos” (8) e em terceiro Regulação (6). Alguns dos transcritos da biblioteca L7 foram escolhidos para análise por repetirem-se mais de 3x e não aparecerem na biblioteca L5, o que indica uma possível regulação positiva sobre estresse. As análises sobre Metalotioneína (4x), mostraram que a sequência de proteica apresentava os domínios conservados que a caracterizava como tipo II, onde são encontrados dois domínios funcionais ricos em cisteína com posições altamente conservadas, desempenhando a função de ligar-se a metais pesados, correlacionadas assim como a atividade de eliminação EROs e defesa contra o estresse oxidativo, além de apresentar homologia com a sequência de Bruguiera gymnorhiza, uma planta de mangue adaptada a ambientes salinos. Analisamos também os transcritos da referente a proteína AUXIN-REPRESSED 12.5 KDA (3x), apontada como sendo reprimida pelo hormônio auxina e associada ao processo de dormência da semente, é descrito em uma família gênica onde vários membros pertencem as vias de resposta ao estresse. Por último, analisamos a proteína GLUTELIN TYPE-A 3 (5x), uma importante proteína de armazenamento com caráter hidrofílico, possivelmente direcionada para o vacúolo. Em nosso trabalho foi possível observar um aumento de transcritos em relação a subtração controle, possivelmente reflexo do aumento do metabolismo da semente, tanto para resposta defensiva ao estresse hídrico quanto para o amadurecimento rápido da semente onde foram observados transcritos referentes a resposta oxidativa, controle hormonal, proteínas de reserva e produção de óleo.

In silico methods to evaluate Fracture Risk and Bone Mineral Density changes in patients undergoing Total Hip Replacement

La sostituzione totale d’anca è uno degli interventi chirurgici con le più alte percentuali di successo. Esistono due varianti di protesi d’anca che differiscono in base al metodo di ancoraggio all’osso: cementate (fissaggio tramite cemento osseo) e non cementate (fissaggio tramite forzamento). Ad oggi, i chirurghi non hanno indicazioni quantitative di supporto per la scelta fra le due tipologie di impianto, decidendo solo in base alla loro esperienza. Due delle problematiche che interessano le protesi non cementate sono la possibilità di frattura intra-operatoria durante l’inserimento forzato e il riassorbimento osseo nel periodo di tempo successivo all’intervento. A partire da rilevazioni densitometriche effettuate su immagini da TC di pazienti sottoposti a protesi d’anca non cementata, sono stati sviluppati due metodi: 1) per la valutazione del rischio di frattura intra-operatorio tramite analisi agli elementi finiti; 2) per la valutazione della variazione di densità minerale ossea (tridimensionalmente attorno alla protesi) dopo un anno dall’operazione. Un campione di 5 pazienti è stato selezionato per testare le procedure. Ciascuno dei pazienti è stato scansionato tramite TC in tre momenti differenti: una acquisita prima dell’operazione (pre-op), le altre due acquisite 24 ore (post 24h) e 1 anno dopo l’operazione (post 1y). I risultati ottenuti hanno confermato la fattibilità di entrambi i metodi, riuscendo inoltre a distinguere e a quantificare delle differenze fra i vari pazienti. La fattibilità di entrambe le metodologie suggerisce la loro possibilità di impiego in ambito clinico: 1) conoscere la stima del rischio di frattura intra-operatorio può servire come strumento di guida per il chirurgo nella scelta dell’impianto protesico ottimale; 2) conoscere la variazione di densità minerale ossea dopo un anno dall’operazione può essere utilizzato come strumento di monitoraggio post-operatorio del paziente.

Familial amyloid polyneuropathy: TTR sequencing and "in silico" analysis

Familial amyloid polyneuropathy (FAP) or paramiloidosis is an autosomal dominant neurodegenerative disease with onset on adult age that is characterized by mutated protein deposition in the form of amyloid substance. FAP is due to a point alteration in the transthyretin (TTR) gene and until now more than 100 amyloidogenic mutations have been described in TTR gene. FAP shows a wide variation in age-at-onset (AO) (19-82 years, in Portuguese cases) and the V30M mutation often runs through several generation of asymptomatic carriers, before expressing in a proband, but the protective effect disappear in a single generation, with offspring of late-onset cases having early onset. V30M mutation does not explain alone the symptoms and AO variability of the disease observed in the same family. Our aim in this study was to identify genetic factors associated with AO variability and reduced penetrance which can have important clinical implications. To accomplish this we genotyped 230 individuals, using a directautomated sequencing approach in order to identify possible genetic modifiers within the TTR locus. After genotyping, we assessed a putative association of the SNPs found with AO and an intensive in silico analysis was performed in order to understand a possible regulation of gene expression. Although we did not find any significant association between SNPs and AO, we found very interesting and unreported results in the in silico analysis since we observed some alterations in the mechanism of splicing, transcription factors binding and miRNAs binding. All of these mechanisms when altered can lead to dysregulation of gene expression, which can have an impact in AO and phenotypic variability. These putative mechanisms of regulation of gene expression within the TTR gene could be used in the future as potential therapeutical targets, and could improve genetic counselling and follow-up of mutation carriers.

In silico metabolic modelling of Saccharomyces cerevisiae for the overproduction of succinate using OptKnock and OptGene

Succinate is a naturally occurring metabolite in organism’s cell and is industrially important chemical with various applications in food and pharmaceutical industry. It is also widely used to produce bio-degradable plastics, surfactants, detergents etc. In last decades, emphasis has been given to bio-based chemical production using industrial biotechnology route rather than fossil-based production considering sustainability and environment friendly economy. In this thesis I am presenting a computational model for silico metabolic engineering of Saccharomyces cerevisiae for large scale production of succinate. For metabolic modelling, I have used OptKnock and OptGene optimization algorithms to identify the reactions to delete from the genome-scale metabolic model of S. cerevisiae to overproduce succinate by coupling with organism’s growth. Both OptKnock and OptGene proposed numerous straightforward and non-intuitive deletion strategies when number of constraints including growth constraint to the model were applied. The most interesting strategy identified by both algorithms was deletion combination of pyruvate decarboxylase and Ubiquinol:ferricytochrome c reductase(respiratory enzyme) reactions thereby also suggesting anaerobic fermentation of the organism in glucose medium. Such strategy was never reported earlier for growth-coupled succinate production in S.cerevisiae.

Three-dimensional, in-silico breast phantom for multimodality image simulations

We report on the construction of anatomically realistic three-dimensional in-silico breast phantoms with adjustable sizes, shapes and morphologic features. The concept of multiscale spatial resolution is implemented for generating breast tissue images from multiple modalities. Breast epidermal boundary and subcutaneous fat layer is generated by fitting an ellipsoid and 2nd degree polynomials to reconstructive surgical data and ultrasound imaging data. Intraglandular fat is simulated by randomly distributing and orienting adipose ellipsoids within a fibrous region immediately within the dermal layer. Cooper’s ligaments are simulated as fibrous ellipsoidal shells distributed within the subcutaneous fat layer. Individual ductal lobes are simulated following a random binary tree model which is generated based upon probabilistic branching conditions described by ramification matrices, as originally proposed by Bakic et al [3, 4]. The complete ductal structure of the breast is simulated from multiple lobes that extend from the base of the nipple and branch towards the chest wall. As lobe branching progresses, branches are reduced in height and radius and terminal branches are capped with spherical lobular clusters. Biophysical parameters are mapped onto the complete anatomical model and synthetic multimodal images (Mammography, Ultrasound, CT) are generated for phantoms of different adipose percentages (40%, 50%, 60%, and 70%) and are analytically compared with clinical examples. Results demonstrate that the in-silico breast phantom has applications in imaging performance evaluation and, specifically, great utility for solving image registration issues in multimodality imaging.

MediPlEx - a tool to combine in silico & experimental gene expression profiles of the model legume Medicago truncatula

Background: Expressed Sequence Tags (ESTs) are in general used to gain a first insight into gene activities from a species of interest. Subsequently, and typically based on a combination of EST and genome sequences, microarray-based expression analyses are performed for a variety of conditions. In some cases, a multitude of EST and microarray experiments are conducted for one species, covering different tissues, cell states, and cell types. Under these circumstances, the challenge arises to combine results derived from the different expression profiling strategies, with the goal to uncover novel information on the basis of the integrated datasets. Findings: Using our new analysis tool, MediPlEx (MEDIcago truncatula multiPLe EXpression analysis), expression data from EST experiments, oligonucleotide microarrays and Affymetrix GeneChips® can be combined and analyzed, leading to a novel approach to integrated transcriptome analysis. We have validated our tool via the identification of a set of well-characterized AM-specific and AM-induced marker genes, identified by MediPlEx on the basis of in silico and experimental gene expression profiles from roots colonized with AM fungi. Conclusions: MediPlEx offers an integrated analysis pipeline for different sets of expression data generated for the model legume Medicago truncatula. As expected, in silico and experimental gene expression data that cover the same biological condition correlate well. The collection of differentially expressed genes identified via MediPlEx provides a starting point for functional studies in plant mutants.

Construção de modelos de interação in silico e in vitro do inibidor do tipo Kunitz de Adenanthera pavonina L. para as enzimas cisteínicas e serínicas

Serines proteinases inhibitors (PIs) are widely distributed in nature and are able to inhibit both in vitro and in vivo enzymatic activites. Seed PIs in than leguminous are classified in seven families, Bowman-Birk and Kunitz type families that most studied representing an important role in the first line of defense toward insects pests. Some Kunitz type inhibitors possess activities serine and cysteine for proteinases named bifunctional inhibitor, as ApTKI the inhibitor isolate from seed of Adenanthera pavonina. The A. pavonina inhibitor presenting the uncommon property and was used for interaction studies between proteinases serine (trypsin) and cysteine (papain). In order to determinate the in vitro interaction of ApTKI against enzymes inhibitor purification was carried cut by using chromatographic techniques and inhibition assays. The 3D model of the bifunctional inhibitor ApTKI was constructed SWISS-MODEL program by homology modeling using soybean trypsin inhibitor (STI, pdb:1ba7), as template which presented 40% of identity to A. pavonina inhibitor. Model quality was evaluated by PROCHECK program. Moreover in silico analyzes of formed complex between the enzymes and ApTKI was evaluated by HEX 4.5 program. In vitro results confirmed the inhibitory assays, where the inhibitor presented the ability to simultaneously inhibit trypsin and papain. The residues encountered in the inhibitor model of folder structural three-dimensional that make contact to enzymes target coud explain the specificity pattern against serine and cysteine proteinases

Determinação de motivos de ligação à quitina em vicilinas de Canavalia ensiformis e Vigna unguiculata através de métodos in silico e relação com suas toxicidades para o bruquídeo Callosobruchus maculatus (Coleoptera:Bruchidae)

Chitin is an important structural component of the cellular wall of fungi and exoskeleton of many invertebrate plagues, such as insects and nematodes. In digestory systems of insects it forms a named matrix of peritrophic membrane. One of the most studied interaction models protein-carbohydrate is the model that involves chitin-binding proteins. Among the involved characterized domains already in this interaction if they detach the hevein domain (HD), from of Hevea brasiliensis (Rubber tree), the R&R consensus domain (R&R), found in cuticular proteins of insects, and the motif called in this study as conglicinin motif (CD), found in the cristallography structure of the β-conglicinin bounded with GlcNac. These three chitin-binding domains had been used to determine which of them could be involved in silico in the interaction of Canavalia ensiformis and Vigna unguiculata vicilins with chitin, as well as associate these results with the WD50 of these vicilins for Callosobruchus maculatus larvae. The technique of comparative modeling was used for construction of the model 3D of the vicilin of V. unguiculata, that was not found in the data bases. Using the ClustalW program it was gotten localization of these domains in the vicilins primary structure. The domains R&R and CD had been found with bigger homology in the vicilins primary sequences and had been target of interaction studies. Through program GRAMM models of interaction ( dockings ) of the vicilins with GlcNac had been gotten. The results had shown that, through analysis in silico, HD is not part of the vicilins structures, proving the result gotten with the alignment of the primary sequences; the R&R domain, although not to have structural similarity in the vicilins, probably it has a participation in the activity of interaction of these with GlcNac; whereas the CD domain participates directly in the interaction of the vicilins with GlcNac. These results in silico show that the amino acid number, the types and the amount of binding made for the CD motif with GlcNac seem to be directly associates to the deleterious power that these vicilins show for C. maculatus larvae. This can give an initial step in the briefing of as the vicilins interact with alive chitin in and exert its toxic power for insects that possess peritrophic membrane

Porównawcza analiza strukturalno-funkcjonalna in silico białek STAT i IRF, w celu identyfikacji związków chemicznych, działających jako specyficzne inhibitory funkcjonalne

Wydział Biologii: Instytut Biologii Molekularnej i Biotechnologii